Satellite Communication Lab Manual

LAB MANUAL

SATELLITE COMMUNICATION

[Document title]

Submitted To: Engr. Iftikhar Rasheed

Department of Telecommunication Engineering University College of Engineering & Technology

The Islamia University of Bahawalpur

LABORATORY WORK BOOK

For The Course Satellite Communication (TE-422)

Student Name: ______________ Roll No. __________________

Prepared By: Engr. Iftikhar Rasheed Lecturer, Telecommunications Engineering


The Islamia University of Bahawalpur, Pakistan

LABORATORY WORK BOOK

For The Course Satellite Communication (TE-422)

Student Name: ______________ Roll No. __________________

Prepared By: Engr. Iftikhar Rasheed Lecturer, Telecommunications Engineering


The Islamia University of Bahawalpur, Pakistan

LAB EXPERIMENTS LIST OF CONTENTS

Serial No

Name of the Experiment

Lab 1

Analysis of a Direct Sequence Spread Spectrum (DSSS) Technique

Lab 2

Analysis of a Frequency Hopping Spread Spectrum (FHSS) Technique

Lab 3

Evaluation of SNR in Satellite Links

Lab 4

Analysis of QPSK Modulation Techniques for LEO Satellite Downlink Communication

Lab 5

Analysis of BPSK Modulation Techniques for LEO Satellite Downlink Communication

Lab 6

Analysis of a GPS Receiver

Lab 7

To Study the Parasitic Elements of Antenna

Lab 8

To Analyze the Effect of Ground Reflections

Lab 9

To Study the Block Diagram of Master Antenna TV System

Lab 10

Study of Community Antenna TV System

Lab 11

Satellite Image Processing with MATLAB

Lab 12

Satellite Orbital Decay- Law of Atmospheres

Lab 13

Semi -Empirical Modeling

Lab 14

Orbital Drag

Lab 15

Space Weather Effects

The Islamia University of Bahawalpur University College of Engineering & Technology Telecom Engineering Department

LAB EXPERIMENT NO.01 Subject Name: --------------------------------------------------- ------------

Course Code: --------------------

Student Name: ------------------------------------------------------ ---------

Roll No. --------------------------

Semester: ----------------------------------------------------------- ----------------

Date: ----------------------------------------------- ----------

Lab Instructor Signature: --------------------

Marks Obtained: ----------------

Analysis of a Direct Sequence Spread Spectrum (DSSS) Technique EQUIPMENT EQUIPMENT REQUIRED:

1) Personal Computer equipped with Pentium -4 or or above processor. 2) Simulation software (MATLAB, C, C++). THEORY:

In satellite communications, spread-spectrum techniques offer several advantages because they have the inherent capability capabilit y of reducing multipath fading and intra -system as well as inter- system interference. Spread-spectrum techniques also permit easy multiple accesses in the form of CDMA. An approach to spread spectrum is the Direct Sequence Spread Spectrum Technique. DSSS involves multiplying the baseband data signal by a wider bandwidth signal, which takes the form of a pseudorandom binary code. The advantage if it is resistance to si gnal jamming. Direct sequence contrasts with the other spread spectrum process, known as frequency hopping spread spectrum, or frequency hopping code division multiple access (FHCDMA), in which a broad slice of the bandwidth spectrum is divided into many possible broadcast frequencies. In general, frequency -hopping devices use less power and are cheaper, but the performance of DS- CDMA systems is usually better and more reliable. Direct sequence spread spectrum, also known as direct sequence code division multiple access (DS-CDMA), and is one of two approaches to spread spectrum modulation for digital signal transmission over the airwaves. In direct sequence spread spectrum, the stream of information to be transmitted is divided into small pieces, each of which is allocated across to a frequency channel across the spectrum. A data signal at the point of transmission is combined with a higher data-rate bit sequence (also known as a chipping code) that divides the data according to a spreading ratio. The redundant chipping code Page 1 of 49

The Islamia University of Bahawalpur University College of Engineering & Technology Telecom Engineering Department helps the signal resist interference and also enables the original data to be recovered if data bits are damaged during transmission. SYSTEM MODEL:

Consider the system below (Fig-1) where b[n] is the message signal, s[n] is the spreading function (or pseudorandom code), q[n] is the transmitted bits, r [n] are the received bits.

RESULTS:

OBSERVATIONS:

_____________________ ________________________________ ______________________ ______________________ ______________________ _____________________ __________ _____________________ ________________________________ ______________________ ______________________ ______________________ _____________________ __________ _____________________ ________________________________ ______________________ ______________________ ______________________ _____________________ __________ _____________________ ________________________________ ______________________ ______________________ ______________________ _____________________ __________

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LAB EXPERIMENT NO.02 Subject Name: --------------------------------

Course Code: --------------------

Student Name: --------------------------------

Roll No. --------------------------

Semester: --------------------------------------

Date: -----------------------------



Analysis of a Frequency Hopping Spread Spectrum (FHSS) Technique EQUIPMENT REQUIRED:

1) Personal Computer equipped with Pentium -4 or above processor. 2) Simulation software (MATLAB, C, C++). THEORY:

In satellite communications, spread-spectrum techniques offer several advantages because they have the inherent capability of reducing multipath fading and intra- system as well as inter- system interference. Spread-spectrum techniques also permit easy multiple access in the form of CDMA. Another approach to spread spectrum is the Frequency Hopping (FH). In FHSS the spreading code is used to control a frequency agile local oscillator, the output of which is used to up- convert the modulated IF carrier to a higher frequency band. The resulting RF output is referred to as a hopping sequence. A replica of the spreading code is applied at the receiver to recover the wanted information. SYSTEM MODEL:

Consider the system below:-

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The Islamia University of Bahawalpur University College of Engineering & Technology Telecom Engineering Department The Hop Code generator generates the hopping pattern of the FHSS system. A similar hopping pattern is at the receiver . OBSERVATIONS: ___________________________________________________________________________ ___________________________________________________________________________ ___________________________________________________________________________ ___________________________________________________________________________

WORK SHEET:

Q 1: What are the advantages of Frequency Hopping Spread Spectrum? ___________________________________________________________________________ ___________________________________________________________________________ ___________________________________________________________________________

Q 2: How FHSS reduces the multipath fading in satellite communication? ___________________________________________________________________________ ___________________________________________________________________________ ___________________________________________________________________________

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Course Code: --------------------

Student Name: --------------------------------

Roll No. --------------------------

Semester: --------------------------------------

Date: -----------------------------



Evaluation of SNR in Satellite Links EQUIPMENT REQUIRED:


The important parameter for a communication system is the signal to noise ratio. It is often stated that the carrier to noise ratio is C/N. C is just the available signal power at the receiving antenna terminals and N the available noise power at the same point. The carrier power and for the noise power we get:

This equation is often expressed in logarithmic terms and forms the basis for the link budget. Before introducing (1) in logarithmic terms, it is important to realize that dB-measures are relative figures. If we however introduce a known reference, the dB figures become absolute measures. You will find dBm (rel. to 1 mW), dB μV (rel. to 1 μV), dBW (rel. to 1 W), dBHz (rel. to 1 Hz) and so on. Often two or more terms in (1) are combined. Gir/Ts is one example. Eq 1 is sometimes expressed as C/No. In this case the noise bandwidth in the denominator on the right side is excluded. (1) in logarithmic terms:

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The Islamia University of Bahawalpur University College of Engineering & Technology Telecom Engineering Department Ls could include Polarization Loss, Pointing Loss, and Atmospheric Attenuation and so on. What you need to take into account depend upon the frequency. WORK SHEET:

Q 1: How SNR affects the satellite links? ___________________________________________________________________________ ___________________________________________________________________________ ___________________________________________________________________________

Q 2: What do you understand from the equation of C/N? ___________________________________________________________________________ ___________________________________________________________________________ ___________________________________________________________________________

Q 3: How C/N is implemented in link budget calculation? ___________________________________________________________________________ ___________________________________________________________________________ ___________________________________________________________________________

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Course Code: --------------------

Student Name: --------------------------------

Roll No. --------------------------

Semester: --------------------------------------

Date: -----------------------------



Analysis of QPSK Modulation Techniques for LEO Satellite Downlink Communications EQUIPMENT REQUIRED:


The discussion explains the methodology and the simulation results of the performances of modulation techniques under the implications of highly dynamic LEO satellite downlink. Modulation schemes that can possibly serve the objectives are the phase shift keying type modulations. Hence, the performance of quadrature phase shift keying (QPSK), offset QPSK (OQPSK) have been investigated through simulations considering the LEO satellite communication downlink channel properties. The modulators and demodulators are synthesized using computer programs. The simulations demonstrated the necessity of applying non-coherent demodulators in order to fight with the multipath fading present in the downlink channel. When LEO communication is considered, reliability and robustness of the link should have the highest priority. Therefore, achieving high data rates has to be accompanied by a robust and reliable system. In order to study the performance of various Modulation schemes, it is essential to understand clearly the constraints applied by tbe.LE0 communication link. Hence, the characteristic properties of downlink have to be examined carefully, which was one of the necessary parts of the research. Therefore synthesized demodulators need to cover these two crucial circuits. Final objective was to compare the performances of the mentioned modulation schemes under LEO satellite communication environment and, if it is possible, to demonstrate better one or ones that might be used in future mission.

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The Islamia University of Bahawalpur University College of Engineering & Technology Telecom Engineering Department SIMULATED CIRCUIT:

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The Islamia University of Bahawalpur University College of Engineering & Technology Telecom Engineering Department OBSERVATIONS: ___________________________________________________________________________ ___________________________________________________________________________ ___________________________________________________________________________

WORK SHEET:

Q 1: Why QPSK is preferred on other modulation techniques? ___________________________________________________________________________ ___________________________________________________________________________ ___________________________________________________________________________

Q 2: What is the effect on BER as Eb/No is changed in QPSK? ___________________________________________________________________________ ___________________________________________________________________________ ___________________________________________________________________________

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Course Code: --------------------

Student Name: --------------------------------

Roll No. --------------------------

Semester: --------------------------------------

Date: -----------------------------



Analysis of BPSK Modulation Techniques for LEO Satellite Downlink Communications EQUIPMENT REQUIRED:


The discussion explains the methodology and the simulation results of the performances of modulation techniques under the implications of highly dynamic LEO satellite downlink. Modulation schemes that can possibly serve the objectives are the phase shift keying type modulations. Hence, the performance of binary phase shift keying (BPSK), has been investigated through simulations considering the LEO satellite communication downlink channel properties. The modulators and demodulators are synthesized using computer programs. The simulations demonstrated the necessity of applying non-coherent demodulators in order to fight with the multipath fading present in the downlink channel. When LEO communication is considered, reliability and robustness of the link should have the highest priority. Therefore, achieving high data rates has to be accompanied by a robust and reliable system. In order to study the performance of various Modulation schemes, it is essential to understand clearly the constraints applied by tbe.LE0 communication link. Hence, the characteristic properties of downlink have to be examined carefully, which was one of the necessar y parts of the research. Modulation schemes that can possibly serve the objectives are the phase shift keying type modulations. Synthesized demodulators need to cover these two crucial circuits. Final objective was to compare the performances of the mentioned modulation schemes under LEO satellite communication environment and, if it is possible, to demonstrate better one or ones that might be used in future mission.

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The Islamia University of Bahawalpur University College of Engineering & Technology Telecom Engineering Department SIMULATED CIRCUIT:

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The Islamia University of Bahawalpur University College of Engineering & Technology Telecom Engineering Department OBSERVATIONS: ___________________________________________________________________________ ___________________________________________________________________________ ___________________________________________________________________________

WORK SHEET:

Q 1: Why BPSK is preferred on other modulation techniques? ___________________________________________________________________________ ___________________________________________________________________________ ___________________________________________________________________________

Q 2: What is the effect on BER as Eb/No is changed in BPSK? ___________________________________________________________________________ ___________________________________________________________________________ ___________________________________________________________________________

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Course Code: --------------------

Student Name: --------------------------------

Roll No. --------------------------

Semester: --------------------------------------

Date: -----------------------------



Analysis of a GPS Receiver THEORY:

The GPS system consists of a constellation of 24 satellites. While not officially declared fully operational, for all practical purposes the system is now fully operational. These satellites orbit the earth at an altitude of about 10,900 miles and at an inclination of 55 degrees. As I will demonstrate in my next column, this orbit translates to an orbital period of 12 hours. The orbits are distributed around the earth in such a way that at least 4 satellites are always visible from virtually any point on the surface of the earth. This provides a means of precisely determining the position of the user in longitude, latitude, and altitude. The satellites operate at two frequencies, known as L1 and L2. These two frequencies are 1575.42 MHz and 1227.6 MHz, respectively. The whole system operates at a system clock frequency of 10.23 MHz, which is an exact submultiple of the L1 and L2 frequencies. The two transmission frequencies are modulated with a pseudo-random signal to produce spread spectrum signals. The L1 channel is modulated with both a 1.023 Mbps pseudo-random code known as the C/A (course/acquisition) code and a 10.23 Mbps PN code known as the P (precision) code. The L2 channel is only modulated with the P code. The two codes are considerably different in characteristics. The L1 code repeats every 1023 bits, or every 1 millisecond. The P code, on the other hand, only repeats itself every 267 days. Furthermore, the P code can be encrypted by the Department of Defense, so as to make it unavailable to civilian (or unauthorized) users. This limits the best accuracy obtainable by unauthorized users to about 30 meters, while allowing authorized users to achieve accuracies of up to 3 meters. Additionally, the DOD, at its discretion, can disseminate slightly inaccurate information pertaining to the location of the satellites, so as to further degrade the accuracy obtainable by unauthorized users to about 100 meters. These accuracy degradation capabilities are important, since hostile nations could use the information against us in times of war. As time has gone by, however, more potential applications have been developed for GPS and many techniques have been developed to augment the accuracy available to unauthorized users. Techniques like carrier phase tracking and differential GPS can allow users to obtain centimeter level accuracy, especially in cases where measurements are being made at a Page 13 of 49

The Islamia University of Bahawalpur University College of Engineering & Technology Telecom Engineering Department fixed location. However, it is well established that even aircraft positions can be determined to an accuracy of better than several meters, even in real time. Other applications include moving map displays in cars and trucks. Attitudes of aircraft and spacecraft can also be determined with GPS. GPS equipment is currently set-up in the San Francisco area to allow researchers to measure the amount of shifting in the earth's surface during the next earthquake. GPS was also recently used to measure the height of Mount Everest and K2. Forest fire fighters use GPS to define the extent of fires and townships are using GPS equipped vans to map roads in a small fraction of the time that would be required for conventional surveying techniques. GPS Receiver:

The Global Positioning System (GPS) works on the principle that if you know your distance from several locations, then you can calculate your location. The known locations are the 24 satellites located in six orbital planes at an altitude of 20,200Km. These satellites circle the Earth every 12 hours and broadcast a data stream at the primary frequency L1 of 1.575GHz which carries the coarse -acquisition (C/A) encoded signal to the ground. The GPS receiver measures the time of arrival of the C/A code to a fraction of a millisecond, and thus determines the distance to the satellite. The Core Subsystems include: 

Front End The GPS L1 signals (Maximum = 24 signals) at 1.575GHz are received at the antenna and amplified by the Low-Noise-Amplifier (LNA). The RF frontend further filters, mixes, and amplifies (AGC) the signal down to the IF frequency where it is digitally sampled by an ADC. 



Baseband Processor/CPU The ADC samples of GPS C/A code signals are correlated by the DSP and then formulated to make range measurements to the GPS satellites. The DSP is interfaced with a general-purpose CPU, which handles tracking channels and controls user interfaces. TI OMAP integrates both DSP and ARM processor on the same chip. 

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Memory The processor runs applications stored in memory. The OS is stored in nonvolatile memory such as EE/FLASH/ROM. Applications may be loaded in FLASH or DRAM. 

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User Interface Allows user to input/output data from the receiver using input commands via microphone, touch screen, and output MP3 to the earplug. 

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Connectivity Allows the receiver to connect to the USB port. 

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The Islamia University of Bahawalpur University College of Engineering & Technology Telecom Engineering Department WORK SHEET:

Q 1: What is the meaning of GPS trilateration? ___________________________________________________________________________ ___________________________________________________________________________ ___________________________________________________________________________

Q 2: How PDOP affect the precision of GPS? ___________________________________________________________________________ ___________________________________________________________________________ ___________________________________________________________________________

Q 3: How GDOP affect the GPS precision? ___________________________________________________________________________ ___________________________________________________________________________ ___________________________________________________________________________

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Course Code: --------------------

Student Name: --------------------------------

Roll No. --------------------------

Semester: --------------------------------------

Date: -----------------------------



To Study the Parasitic Elements of Antenna EQUIPMENT REQUIRED:

1) Connected up the hardware of antenna lab 2) Load the discovery software 3) Load the NEC-win software PROCEDURE: Two Dipole Elements: 1. Identify one of the Yagi boom assemblies and mount it on the top of the generator

tower. 2. Ensure that all of the elements are removed except for the dipole and that this is

mounted above the tower support. 3. Launch a signal strength vs. angle 2D polar graph window and immediately switch on

the motor enable switch. 4. Ensure that the receiver and generator antennas are aligned with each other and that

the spacing between then is about one meter. 5. Set the dipole length to 10cm. 6. Acquire a new plot at 1500MHz. 7. Observe the polar plot obtained. 8. Identify one of the un-driven dipole antenna system. 9. Move the driven dipole forward on the boom by about 2.5cm and mount a second un-

driven dipole length to 10cm.

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The Islamia University of Bahawalpur University College of Engineering & Technology Telecom Engineering Department 10. Acquire a second new plot at 1500MHz. 11. Change the spacing between the two elements of the antenna to 2.5cm. 12. Acquire a third new pole at 1500MHz. Changing the Length of Parasitic Antenna: 13. Set the spacing between the two elements to 2.5cm and ensure the length of both the elements are 10cm. 14. Launch a new signal strength vs. angle 2D polar graph window. 15. Acquire a new plot at 1500MHz. 16. Extend the length of un-driven element to 11cm. 17. Acquire a second new plot at 1500MHz. 18. Reduce the length of the un-driven element to 8cm. 19. Acquire a third new plot at 1500MHz. Software Simulation: 1. Run NEC-Win and click open the file on the tool bar. Open file dipole-1. 2. Check that Y-coordinates for the dipole are -0.05 and +0.05 and ensure that no

ground is set. 3. Click on the cell of the table that has the figure 1 in it under wire on the left hand

column of the table. This will high light the wire 1 row. 4. Click on the copy button on the tool bar to paste into the wire2 row. 5. The second dipole must now be placed 2.5cm to be -0.025 to do this. Verify that you

have done this correctly by looking at NEC-Vu. 6. The second dipole is not going to be driven so you need to remove the source icon

into the bin at bottom right band corner. Then click OK. 7. Save this two elements antenna as 2e11. 8. Look at plots of this antenna. 9. Now change the length of second dipole to give a total length of 11cm. 10. Save this antenna as 2e12. 11. Look at the plots of antenna. 12. Now change the length of second dipole to give a total length of 8cm. 13. Save this antenna as 2e13.

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The Islamia University of Bahawalpur University College of Engineering & Technology Telecom Engineering Department 14. Look at the plots for this antenna and add the 2e11 and 2e12 files. Give them different

colors so that you can identify. 15. With the length of second dipole the direction of maximum radiations is from the

driven elements towards the parasitic elements. In this case the parasitic element is called director. 16. With the length of second dipole longer then the drive dipole the direction of

maximum radiations is from the patristic element towards the driven element. In this case the parasitic element is called reflector. WORK SHEET:

Q1: Has the polar pattern changed by adding the second element in hardware modeling? ___________________________________________________________________________ ___________________________________________________________________________ ___________________________________________________________________________

Q2: Has the gain and directivity changed by adding the second element in hardware? ___________________________________________________________________________ ___________________________________________________________________________ ___________________________________________________________________________

Q3: What changes has the alteration in length mode to the gain and directivity? ___________________________________________________________________________ ___________________________________________________________________________ ___________________________________________________________________________

Q4: How do these theoretical simulated plots compare with the real plots in hardware modeling? ___________________________________________________________________________ ___________________________________________________________________________ ___________________________________________________________________________

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Course Code: --------------------

Student Name: --------------------------------

Roll No. --------------------------

Semester: --------------------------------------

Date: -----------------------------



To Analyze the Effect of Ground Reflections EQUIPMENT REQUIRED: 1) Loaded the NEC-Win plus software in PC.

DISCUSSION:

The ground around and under antenna is a part of environment in which any actual antenna must operate. This interaction can be analyzed depending in where they occur relative to two areas surroundings the antenna the reactive near field and the radiating for field. The reactive near field only exists very close to the antenna itself. In this region the antenna acts as though it were a large lumped constant inductor or capacitor, where energy is stored but very little is actually radiated. The interaction with ground in this area creates mutual impedance of an antenna, but also often increases losses. In this radiating for field, the presence of ground profoundly influences the radiation pattern of antenna. The interaction is different depending on the antenna polarization with respect to the ground. For horizontally polarized antennas the shape of the radiated pattern in the elevation plane strongly depend on the nature of ground itself as well as on the height of the antenna above ground. PROCEDURE:

For single dipole above perfect ground: 1. Run NEC-Win and construct single dipole and save as dipole-1. If already saved them click open file on the tool bar. Open the file dipole-1. 2. Change Z1 and Z2 to 0.025m. 3. Click on file then save as in the ground box just below the toolbar set the ground to perfect ground and ensure that the frequency is set to 1500MHz. 4. Click run on NEC button and then examine the azimuth and elevation plots produced, dipole over real ground: 5. Construct single dipole with previous readings as constructed for single dipole above perfect ground in as save as dipole 2 again.

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The Islamia University of Bahawalpur University College of Engineering & Technology Telecom Engineering Department 6. Click on presents at ground box select real ground. 7. Click on presents at the top left hand corner of dial ogue box that appears. 8. Select urban button and industrial area and then click OK. 9. Click the run NEC and then save dipole3. 10. Click the polar plot button and add file select the file dipole 2when prompted. 11. Choose different colors for plots of two antenna system. 12. Examine the elevation plot first. WORK SHEET:

Q1: Are the plots different from those with no ground in single dipole? ___________________________________________________________________________ ___________________________________________________________________________ ___________________________________________________________________________

Q2: Are the plots similar in shape in the perfect ground and real ground in elevation? ___________________________________________________________________________ ___________________________________________________________________________ ___________________________________________________________________________

Q3: Are the plots similar in shape in the perfect ground and real ground in azimuth? ___________________________________________________________________________ ___________________________________________________________________________ ___________________________________________________________________________

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Course Code: --------------------

Student Name: --------------------------------

Roll No. --------------------------

Semester: --------------------------------------

Date: -----------------------------



To Study the Block Diagram of Master Antenna TV System

MASTER ANTENNA TV SYSTEM:

A master antenna TV (MATV) system is used to provide reception of DBS TV/FM channels to a small group of users, for example, to the tenants in an apartment building .It consist of a single outdoor unit (antenna and LNA/C)feeding a number of indoor units, as shown in Fig. It is basically similar to the home system already described, but with each user having access to all the channels independently of the other users.

The advantage is that only one outdoor unit is required, but as shown, separate LNA/Cs and feeder cables are required for each sense of polarization. Compared with the single user system, a larger antenna is also required (2- to 3-m diameter) in order to maintain a goof signal-to-noise ratio at all the indoor units.

Where more than a few subscribers are involved, the distribution used is similar to the community antenna (CATV) described in the foll owing section. In the figure given below there are various components of master antenna TV system are shown and it also differentiate between the input and output units of the system.

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The Islamia University of Bahawalpur University College of Engineering & Technology Telecom Engineering Department BLOCK DIAGRAM:

WORK SHEET:

Q1: What do you mean by LHC and RHC polarization? ___________________________________________________________________________ ___________________________________________________________________________ ___________________________________________________________________________ Page 22 of 49

The Islamia University of Bahawalpur University College of Engineering & Technology Telecom Engineering Department Q2: What is function of polarization diplexer? ___________________________________________________________________________ ___________________________________________________________________________ ___________________________________________________________________________ Q3: What is the function of power divider? ___________________________________________________________________________ ___________________________________________________________________________ ___________________________________________________________________________

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Course Code: --------------------

Student Name: --------------------------------

Roll No. --------------------------

Semester: --------------------------------------

Date: -----------------------------



Study of Community Antenna TV System THEORY:

The CATV system employs a single outdoor unit, with separate feeds avail able for each sense of polarization, like a MATV system, so that all channels are made available simultaneously at the indoor receiver for each user, all the carriers are demodulated in a common receiver – filter system, as shown in Fig. The channels are then combined into a standard multiplexed signal for transmission over cable to the subscribers. In remote areas where a cable distribution system may not be installed, the signal can be re broadcasted from a low-over VHF TV transmitter. Figure shows a remote TV station which employs an 8-m (26.2 ft) antenna for reception of the satellite TV signal in the C-band. With the CATV system, local programming material also be distributed to subscribers, an option which is not permitted in the MATV system. BLOCK DIAGRAM:

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The Islamia University of Bahawalpur University College of Engineering & Technology Telecom Engineering Department WORK SHEET:

Q1: What are the applications of community antenna TV system? ___________________________________________________________________________ ___________________________________________________________________________ ___________________________________________________________________________

Q2: Write down the function of wideband receiver? ___________________________________________________________________________ ___________________________________________________________________________ ___________________________________________________________________________

Q3: What is the function of channel filters and combiner? ___________________________________________________________________________ ___________________________________________________________________________ ___________________________________________________________________________

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Course Code: --------------------

Student Name: --------------------------------

Roll No. --------------------------

Semester: --------------------------------------

Date: -----------------------------



Satellite Image Processing with MATLAB INTRODUCTION:

MATLAB (MATrix LABoratory) integrates computation, visualization, and programming in an easy-to-use environment where problems and solutions are expressed in familiar mathematical notation. MATLAB features a family of application-specific solutions called toolboxes. Toolboxes are comprehensive collections of MATLAB functions (M-files) that extend the MATLAB environment to solve particular classes of problems. Areas in which toolboxes are available include signal processing, control systems, neural networks, fuzzy logic, wavelets, simulation, image processing and many others. Image processing tool box has extensive functions for many operations for image restoration, enhancement and information extraction. Some of the basic features of the image processing tool box are explained and demonstrated with the help of a satellite imagery obtained from IRS (Indian Remote Sensing Satellite). Basic Operations with MATLAB Image Processing Tool Box: 

Read and Display an Image:

Clear the MATLAB workspace of any variables and close the open figure windows. To read an image, use the imread command. Let's read in a JPEG image named image4. JPG, and store it in an array named I. I= imread ( ‘image4. JPG’); Now call imshow to display I. imshow (I)Image is displayed as shown below in Fig.

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The Islamia University of Bahawalpur University College of Engineering & Technology Telecom Engineering Department Image is displayed as shown in Fig above. This image is IRS LISS III Band 4 (Near Infrared) data showing a portion of Uttara Kannada district in Karnataka. Some features in the image are; (i) Arabian Sea on the left (ii) Kalinadi in top half (iii)Dense vegetation. Small white patches in the image are clouds. 

Check the Image in Memory:

Enter the whos command to see how I is stored in memory. Whos MATLAB responds with; Name Size Bytes Class I 342x342 116964 uint8 Grand total is 116964 elements using 116964 bytes 

Histogram Equalization:

As can be seen, image4.JPG is in low contrast i.e., although pixels can be in the intensity range of 0-255 they are distributed in a narrow range. To see the distribution of intensities in image4.JPG in its current state, a histogram can be created by calling the imhist function. (Precede the call to imhist with the figure command so that the histogram does not overwrite the display of the image in the current figure window.) Figure, imhist (I) % Display a histogram of I in a new figure (Fig. 2).

Figure 2. Histogram of raw image Images in MATLAB and the Image Processing Toolbox

The basic data structure in MATLAB is the array of an ordered set of real or complex elements. This object is naturally suited to the representation of images, real-valued, Page 27 of 49

The Islamia University of Bahawalpur University College of Engineering & Technology Telecom Engineering Department ordered sets of color or intensity data. MATLAB stores most images as two-dimensional arrays, in which each element of the matrix corresponds to a single pixel in the displayed image. For example, an image composed of 200 rows and 300 columns of different colored dots would be stored in MATLAB as a 200-by-300 matrix. Some images, such as RGB, require a three- dimensional arra y, where the first plane in the third dimension represents the red pixel intensities, the second plane represents the red and green pixel intensities, and the third plane represents the blue pixel intensities. This convention makes working with images in MATLAB similar to working with any other type of matrix data, and renders the full power of MATLAB available for image processing applications. For example, a single pixel can be selected from an image matrix using normal matrix subscripting. I (2,15) This command returns the value of the pixel at row 2, column 15 of the image MATLAB supports the following graphics file formats: BMP (Microsoft Windows Bitmap) HDF (Hierarchical Data Format) JPEG (Joint Photographic Experts Group) PCX (Paintbrush) PNG (Portable Network Graphics) TIFF (Tagged Image File Format) XWD (X Window Dump) Converting Image Storage Classes:

Uint8 and uint16 data can be converted to double precision using the MATLAB function, double. However, converting between storage classes changes the way MATLAB and the toolbox interpret the image data. If it is desired to interpret the resulting array properly as image data, the original data should be rescaled or offset to suit the conversion. For easier conversion of storage classes, use one of these toolbox functions: im2double, im2uint8, and im2uint16. These functions automaticall y handle the rescaling and offsetting of the original data. For example, the following command converts a double precision RGB (Red Green Blue) image with data in the range [0, 1] to a uint8 RGB image with data in the range [0,255]. RGB2 = im2uint8(RGB1); Converting Graphics File Formats :

To change the graphics format of an image, use imread to read in the image and then save the image with imwrite, specifying the appropriate format. For example, to convert an image from a BMP to a PNG, read the BMP image using imread, convert the storage class if necessary, and then write the image using imwrite, with 'PNG' specified as your target format. bitmap = imread('image4.BMP','bmp'); imwrite(bitmap,'image4.png','png'); Page 28 of 49

The Islamia University of Bahawalpur University College of Engineering & Technology Telecom Engineering Department Image Arithmetic:

Image arithmetic is the implementation of standard arithmetic operations, such as addition, subtraction, multiplication, and division, on images. Image arithmetic has many uses in image processing both as a preliminary step and in more complex operations. For example, image subtraction can be used to detect differences between two or more images of the same scene or object. 

Adding Images: To add two images or add a constant value to an image, use the imadd function. imadd adds the value of each pixel in one of the input images with the corresponding pixel in the other input image and returns the sum in the corresponding pixel of the output image.

Figure 3. Image after adding two images Image addition has many uses in image processing. For example, the following code fragment uses addition to superimpose one image on top of another. The images must be of the same size and class. I = imread('image3.JPG'); J = imread('image4.JPG'); K = imadd(I,J); imshow(K) 

Subtracting Images :

To subtract one image from another, or subtract a constant value from an image, use the imsubtract function. imsubtract subtracts each pixel value in one of the input images from the corresponding pixel in the other input image and returns the result in the corresponding pixel in an output image. X= imread('image5.JPG'); J= imread('image4.JPG'); Page 29 of 49

The Islamia University of Bahawalpur University College of Engineering & Technology Telecom Engineering Department K= imsubtract(X,J); 

Multiplying Images:

To multiply two images, use the immultiply function. immultiply does an element-byelement Multiplication of each corresponding pixel in a pair of input images and returns the product of these multiplications in the corresponding pixel in an output image. Image multiplication by a Constant, referred to as scaling, is a common image processing operation. 

Dividing Images:

To divide two images, use the imdivide function. The imdivide function does an element-byelement division of each corresponding pixel in a pair of input images. Special Display Techniques:

In addition to imshow, the toolbox includes functions that perform specialized display operations, or exercise more direct control over the display format. 

Adding a Color bar:

The color bar function can be used to add a color bar to an axes object. If a color bar is added to an axes object that contains an image object, the color bar indicates the data values that the different colors or intensities in the image correspond to as shown in Figure 5. F=imread('image5.JPG'); imshow(F),



Image Resizing:

To change the size of an image, use the imresize function. imresize accepts two primary arguments viz. Page 30 of 49

The Islamia University of Bahawalpur University College of Engineering & Technology Telecom Engineering Department (i ) (ii)

The image to be resized and The magnification factor.

The command below decreases the size of the image by 0.5 times. F = imread('image5.JPG'); J = imresize(F,0.5); Analyzing and Enhancing Images:

The Image Processing Toolbox supports a range of standard image processing operations for analyzing and enhancing images. Its functions simplify several cate gories of tasks, including: 

Obtaining pixel values and statistics, which are numerical summaries of data in an image.

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Analyzing images to extract information about their essential structure.

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Enhancing images to make certain features easier to see or to reduce noise.

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Pixel Selection:

The toolbox includes two functions that provide information about the color data values of image pixels specified. The pixval function interactively displays the data values for pixels as the curso is moved over the image. pixval can also display the Euclidean distance between two pixels. The impixel function returns the data values for a selected pixel or set of pixels. You can supply the coordinates of the pixels as input arguments, or you can select pixels using a mouse. Image Analysis

Image analysis techniques return information about the structure of an image. 

Edge Detection:

One can use the edge function to detect edges, which are those places in an image that correspond to object boundaries. To find edges, this function looks for places in the image where the intensity changes rapidly, using one of these two criteria: 1. Places where the first derivative of the intensity is larger in magnitude than some threshold. 2. Places where the second derivative of the intensity with a zero crossing edge provides a number of derivative estimators, each of which implements one of the above definitions.

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The Islamia University of Bahawalpur University College of Engineering & Technology Telecom Engineering Department For some of these estimators, it can be specified whether the operation should be sensitive to horizontal or vertical edges, or both. Edge returns a binary image containing 1's where edges are found and 0's elsewhere. The most powerful edge-detection method that edge provides is the Canny method. The Canny method differs from the other edge-detection methods in that it uses two different. The example below illustrates the power of the Canny edge detector. It shows the results of applying the Sobel and Canny edge detectors to the image4.JPG image(Figure). F = imread('image5.JPG'); BW1 = edge(F,'sobel'); BW2 = edge(F,'canny'); imshow(BW1); figure, imshow(BW2)

Figure 6. Edge detection Image

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The Islamia University of Bahawalpur University College of Engineering & Technology Telecom Engineering Department Image Enhancement:

Image enhancement techniques are used to improve an image, where "improve" is sometimes defined objectively (e.g., increase the signalto- noise ratio), and sometimes subjectively (e.g., make certain features easier to see by modifying the colors or intensities). 

Intensity Adjustment :

Intensity adjustment is a technique for mapping an image's intensity values to a new range. For example, image4.JPG is a low contrast image. The histogram of image4.JPG, indicates that there are very few values above 80. If the data values are remapped to fill the entire intensity range [0,255], one can increase the contrast of the image. This kind of adjustment can be achieved with the imadjust function in addition to the histeq function already explained. The general syntax of imadjust is. J = imadjust(I,[low_in high_in],[low_out high_out]) Where, low_in and high_in are the intensities in the input image, which are mapped to low_out, and high_out in the output image. For example, the code below performs the adjustment described above. I=imread('image4.JPG'); J = imadjust(I,[0.0 0.3],[0 1]); The first vector passed to imadjust, [0.0 0.3], specifies the low and high intensity values of image. The second vector, [0 1], specifies the scale over which you want to map them. Thus, the example maps the intensity value 0.0 in the input image to 0 in the output image, and 0.3 to 1. Note that one must specify the intensities as values between 0 and 1 regardless of the class of I. If I is in uint8, the values supplied are multiplied by 255 to determine the actual values to use. To use imadjust, one must typically perform two steps: 1. View the histogram of the image to determine the i ntensity value limits. 2. Specify these limits as a fraction between 0.0 and 1.0 so that you can pass them to imadjust in the [low_in high_in] vector.

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Course Code: --------------------

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Roll No. --------------------------

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Date: -----------------------------



Satellite Orbital Decay- Law of Atmospheres OBJECTIVE:

Explore effects of atmosphere drag on motion of satellites that are in low enough orbits to be affected by the Earth’s atmosphere. In this lab, you will analyze how the solar activity can affect the atmosphere and cause changes in the thickness of atmospheric layers. This in turn affects the orbit of the satellites. PROCEDURE:        

Compare and contrast ideal and model atmospheres Study the atmosphere’s density and temperature profile Develop basic physics to describe satellite motion Calculate boundary values for problem Write a program using Excel to describe satellite motion Plot characteristics of satellites (in near circular orbit) under the influence of drag Explore effects of time-varying atmosphere heating Collision avoidance and re-entry prediction

Law of Atmospheres:

The challenge is to use excel to model how the density of atmosphere decreases in the troposphere. Density is the mass of air per volume (=M/Vol). The atmosphere in the troposphere is relatively dense, and particles in the atmosphere collide frequently (they move with some average velocity v and have an average temperature T). This implies that we can use the ideal gas law (remember PV=nkT?) In fact the more accurate form of the law of atmospheres is:

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The Islamia University of Bahawalpur University College of Engineering & Technology Telecom Engineering Department Where m is the mass of the gas molecule, g the gravitational acceleration, and k the Boltzmann constant. Now type this formula into the Excel spread sheet and then plot how the density of the atmosphere, ρ, varies with altitude, h. The “Simple Law of Atmospheres” assumes that all quantities in the exponent (the particle mass, m, the temperature, T , and the gravitational acceleration, g ) remain constant, and that the only variable is the altitude, h.  



Double click on Satellite-Lab to open the Excel spread sheet. Click on “Simple Atmosphere” at the bottom of the page. You will see a spreadsheet with some constants highlighted in green and a formula highlighted in yellow. You will need to calculate the purple values. Let’s start with the height. You could type in all values f rom 0, 1, 2, 3… to 1000, but you can also have Excel do this for you. If you know how to use Excel just put those values into column [A], if not follow the instructions in the different type font below: 

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









Next let us convert km to meters and store all the values in column [B]. 

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Click the cell directly underneath “h in km” [A11]. Type “0” followed by for h=0 at sea level. Now increase the altitude in steps of 1km, click on the cell underneath the “0”, on cell [A12] Type “=” then click on the previous cell, on [A11], at this stage Excel will insert “A11” Type “+1”, then click to enter the formula. Put the cursor on back on cell [A12], and left-click. Go to the bottom right of the cell; when the cursor turns to a “thin cross”, pull down the mouse until h=1,000km. Voila, column [A] is done.

Click the cell directly underneath “h in meters”, on cell [B11] Type “=” then click on cell [A11] — at this stage Excel will insert “A11” Type “*1000”, then click to enter the formula. Like before, put the cursor on cell [B11], and left-click; go to the bottom right of the cell; and when the cursor turns to a “thin cross”, pull down the mouse until h=1,000,000m.

You now have written your first Excel program. Calculating the density is a little more complicated, but the general idea is the same. For every altitude, h, which is stored in column [B], we want to calculate the corresponding value of the density and put it into column [C]. Let’s calculate the density. Recall the formula; put in h=0 Page 35 of 49

The Islamia University of Bahawalpur University College of Engineering & Technology Telecom Engineering Department meters and solve. We can calculate this even without a calculator since the exponent 

is equal to zero. So  at h=0 is o (i.e., o =1.21 kg/m3). Next we need to determine the density at an altitude of 1km, then at 2km. So insert 1km (convert km to meters first – 1km=1000m) into the above formula. You ’ll get:



Rewrite the above formula, but substitute 1, 2, or 3 with “i” – “i” then corresponds to each ith value of density ( i) and altitude (hi).

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Insert this formula into Excel. If you do not know Excel, follow the instructions below: 

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Click on cell “C11” Type in “=1.21” Click the cell to the right of “h=1” (This is cell “C12”) Type “=1.21”, then type “*exp(-” Click on cell “B12”, which is the altitude in meters — Excel will insert “B12” Type “*”, then at cell “D3” click on “4.8079E-26” the value of m — Excel will inser t “m0” Type “*”, then at cell “D4” click on “9.8” the value of g — Excel will insert“g_surface” Type “/”, then at cell “D5” click on “1.38E-23” the value of k — Excel will inser t “k_ B” Type “/”, then at cell “D6” click on “293” the value of T — Excel will inser t “T” Type “)”, then click . Your formula is now typed into the “ 1” cell. Select that cell and after getting the small cross in the lower right, pull down the mouse until h=1000km. Scroll back to the top and check the values of same values as what you calculated before.

1

& 2 – they should have the

Now check out the graph. Put your cursor to the bottom of the Excel sheet and click on “Alt. vs. Mass Density (simple)”. The graph should appear. It shows how density changes with altitude. The graph is actually displayed below. Look at the green line.

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The above plot shows the altitude versus mass density for three different temperatures. Which of a, b, c (the green, blue and red lines) has the highest temperature? Explain. ___________________________________________________________________________ ___________________________________________________________________________ ___________________________________________________________________________

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The Islamia University of Bahawalpur University College of Engineering & Technology Telecom Engineering Department 



The satellite will be flying at an altitude of 350 km. Read off the value for the density ______________________ The best vacuum produced on Earth has a density of ~10 -20 g/cm3 (or 10-23 kg/m3). Compare this value to the density in which the mass is flying.

___________________________________________________________________________ ___________________________________________________________________________ ___________________________________________________________________________ ___________________________________________________________________________

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Course Code: --------------------

Student Name: --------------------------------

Roll No. --------------------------

Semester: --------------------------------------

Date: -----------------------------



Semi -Empirical Modeling Theory:

Empirical models are models that orginate or are based on factual information or directly sensed information. There are four possibilities of dealing with poorly behaved theoretical models.    

Rethinking the theory, i.e., the “Simple Atmosphere” from Part I Expanding upon the theoretical model Creating and using an empirical model from data Tweaking the theoretical model and iteratively adding observational data, e) doing semi-empirical modeling

i.e.

Let’s first look at the formula for the “simple atmosphere” again and decide what it really tells us. In the exponent we have a balance between “mgh” and “kT ” So we actually have three more variables: m, g , and T (in addition to the altitude h).

In previous lab we assumed that all these values remain constant as we go to higher and higher altitudes. What do you think, is this a reasonable assumption? Can you assume that the gravitational acceleration is constant at higher altitudes? Explain. ___________________________________________________________________________ ___________________________________________________________________________ ___________________________________________________________________________

Can you assume that the composition of individual molecules remains constant? Explain. [Hint: What is the chemical composition of the different atmospheric layers? And what do you think might happen if these molecules have different masses?] Can you assume that the temperature remains constant? Explain. Page 39 of 49

The Islamia University of Bahawalpur University College of Engineering & Technology Telecom Engineering Department ___________________________________________________________________________ ___________________________________________________________________________ ___________________________________________________________________________ Can you assume that the temperature remains constant? Explain. ___________________________________________________________________________ ___________________________________________________________________________ ___________________________________________________________________________ 

If you said “no” to the above questions you were correct! The three assumptions of the “simple law of atmospheres” are not completely correct. So how does the gravitational acceleration change with altitude? This is something you can figure out yourself – Remember Newton’s second law? And remember the formula for Newton’s universal Law of Gravitation? Look up those formulae and write them into the two boxes below. F= ___________________ F= ___________________



Combine them and solve for the acceleration. Recall that the radius is actually the distance to the center of the Earth, so substitute R=Re + h, where Re is the Earth ’s radius and h the altitude. a = ___________________

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

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Next we can change the simple law of atmospheres to substitute for the altitude dependence of the gravitational acceleration. Insert the above expression for g (or actually a):

= ______________________ Let’s analyze how a changing gravitational acceleration affects your model. On the bottom of the Excel sheet click on the sheet saying “Atmospher e”. Look at column [E] – it should be the same as what you calculated in part I. Just for practice, repeat the previous exercise of typing hi into column [B], and i into column [E] of this sheet. Next, type the above formula (equation 7) into column [H], starting at cell [H11]. To practice try it yourself. If all fails follow the instructions below. Click the cell [H11]; Type “=1.21”, then type “*exp(-” 

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





Type “*”, then click on “4.8079E-26” the value of m — Excel will insert “m_o” Type “/”, then click on “1.38E-23” the value of k — Excel will insert “kB” Type “/”, then click on “293” the value of T — Excel will insert “T” Type “*”, then click on “6.67E-6” the value of G — Excel will insert “G_” Page 40 of 49

The Islamia University of Bahawalpur University College of Engineering & Technology Telecom Engineering Department 







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





Type “*”, then click on “5.97E+24” the value of Me — Excel will insert “Me” Type “*”, then click on “h=0”, cell [B11] — Excel will insert “B11” Type “+”, then click on “h=0”, cell [B11] — Excel will insert “B11” Type “)^2)”, then click Click on cell [H11] and pull down formula until h=1000km.

Let’s “look” at the effect of inserting a variable acceleration. Go to the bottom of the Excel sheet and click on “Altitude vs. Mass Density” and look at the plot. The green line corresponds to the “simple law of Atmospheres”, the grey one to the Law corrected for a variable gravitational acceleration. Look at the grey line and compares it to the green line.

So all in all, the assumption of a constant acceleration was not perfect, but what do you recon. Was it a reasonable assumption nevertheless? __________ And to be honest, we would not have known this unless we had really calculated and plotted this. Okay, let’s look at the other assumptions. It turns out that the temperature of the atmosphere is NOT constant (the temperature is much cooler at an altitude where planes fly an increases, decreases and then increases again – see plot below). This behavior is too complex to be described by another theoretical law. So we are going to do a trick. For every altitude, we will insert the measured value of the temperature. Guess what – we have actually done this for you; and even plotted it – the blue line above incorporates this temperature dependence. We have combined a theoretical model with real data and we have now produced a semi empirical model. Page 41 of 49




Since the chemical composition (thus the mass per molecule) changes somehow (let’s not worry about the details), we will need to insert measured values for the mass as a function of altitude. The good news is you get a break (again) because we have done this for you! (The data are in column [D] in the “Atmosphere” spread sheet, and the vales corrected for varying molecular mass are in column [K].) Like in the case for temperature, this part is semi-empirical. The black line in Figure is now our “ best” model – it is called the “MSIS” model (the red line incorporates an “additional” change in temperature as you will discover in the next section). This final model, the MSIS model is used by professional scientists at NOAA, the National Oceanic and Atmospheric Association.

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Course Code: --------------------

Student Name: --------------------------------

Roll No. --------------------------

Semester: --------------------------------------

Date: -----------------------------



Orbital Drag THEORY:

Because the atmosphere extends beyond 1000 km, it can interfere with the motion of near earth satellites, for example the space satellite in near-Earth orbit. The atmosphere will cause an air drag, which will cause the satellite’s orbit to decay and eventually down the satellite (in fact, as the satellite re-enters, there is a good possibility of it burning up in the lower parts of the atmosphere). A satellite in circular orbit ex periences an acceleration given by; a= __________________________ Insert the expression for the acceleration into Newton’s 2nd Law F2nd = _______________________ Newton’s Law of Gravitation is F2nd = FG = ___________________ Combine both equations and solve for the velocity V= __________________________ By squaring both sides and then multiplying by ½ m you get the associated kinetic energy: Ekin = ½ m v2 = ________________________ Look up the expression for potential energy: Epot = Why is the potential energy negative? What does that mean? ___________________________________________________________________________ ___________________________________________________________________________ Page 43 of 49

The Islamia University of Bahawalpur University College of Engineering & Technology Telecom Engineering Department The total mechanical energy of the satellite is the sum of its kinetic and potential energy. Etot = Ekin + Epot = ______________________________ Remember that the altitude is the height above the Earth ’s Surface + the Earth’s radius. Solving the above equation for altitude we get: h = r – Re = ______________________________________ So now we have the expressions we need – the total energy of the satellite as it flies with velocity v at an altitude of h. We also know that as the satellite moves through the atmosphere it will experience a drag due to the resistance of air. Basically the air drag robs the satellite of its total mechanical energy. Will this increase or decrease the kinetic energy of the shuttle? (Do not guess, think) ___________ And does this correspond to a higher or lower kinetic energy?

_____

What about the potential energy? How fast does it decrease compared to the mechanical energy? ___________________________________________________________________________ ___________________________________________________________________________ Drag Force is FD = ½ A CD v2 Where A is the area of the satellite and CD the drag coefficient. The work done by the drag then is WD = FD s = ½  A CD v2 s Where s is the distance traveled (for one orbit s=2πr=2π(Re + h)). Let’s conceptually think about this formula – it depends on the front surface area of the satellite perpendicular to the direction of motion, and on the volume V = As which the satellite displaces as it travels the distance s. It also depends on the ambient air density through which the satellite travels, and on the square of the velocity. (Remember the kinetic energy is also dependent on the square velocity since E = ½ mv2. Also recall that m = ρ V = ρ As.) CD is the drag coefficient and depends on the properties of the medium, in this case the air. Now we have all the formulae we need for the Excel spread sheet. Next you will write these formulae into the flow chart on the next page.

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Course Code: --------------------

Student Name: --------------------------------

Roll No. --------------------------

Semester: --------------------------------------

Date: -----------------------------



Space Weather Effects THEORY: Space weather effects in the upper atmosphere come from many sources, however we know that variability of the Sun is a leading cause of upper atmospheric variability. You may have heard of an 11- year solar cycle during which the number of sunspots rises and falls. Associated with the number of sunspots is an increase the output of solar radiation at short wave lengths (X-rays and Ultra-Violet rays). These rays are really high energy photons that can interact with and hear the earth’s upper atmosphere. Indeed the earth’s upper atmosphere is much hotter, by several hundred degrees, during and just after the maximum in the number of sunspots. As you already know, a hot atmosphere is an expanded atmosphere. An expanded atmosphere has more mass at higher levels and this can interfere with satellite orbits. The heating of the upper atmosphere due to absorption of high energy photons is usually a gradual process that occurs over many months. Even if there is a noticeable “flare” of radiative energy from the Sun the atmosphere will only absorb a small amount of the energy on the sunlit side of the earth. Recent investigations into other aspects of solar interactions with the earth’s atmosphere have revealed that the accumulation of energy from solar photons can be augmented by a process in which mass actually escapes from the Sun’s atmosphere and collides with the Earth’s protective magnetic field. These solar coronal mass ejections (CMEs) create large currents and associated magnetic fields in our upper atmosphere, and much like running a current through a curling iron, the atmosphere heats up. Such CME-earth collisions can cause very rapid heating over short intervals. Of course there are times when a sudden addition solar radiative input is followed by a CME event within a few hours or days. Two such events can cause rapid expansion of the earth’s atmosphere and real trouble in tracking the location of satellites. The diagram below shows an example of such an event that occurred in 1989 when over 1500 objects in space become “lost” to satellite tracking. It took many weeks to identify and find all of the Page 46 of 49

The Islamia University of Bahawalpur University College of Engineering & Technology Telecom Engineering Department satellites. The subsequent figure shows the rate at which energy comes to the upper atmosphere from several sources. The spikes in total power are f rom CME’s.

Fig. 1: Taken from the Air University Space Primer Let’s assume a flare occurs on the Sun and within a few minutes the energy reaches the earth. About two days later a CME collides with the earth and also deposits energy. We can envision this with the following diagram. Below is a diagram that represents how the satellite might respond to rapidly changing heating rates.

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The Islamia University of Bahawalpur University College of Engineering & Technology Telecom Engineering Department Below is a diagram that shows the real data of when flare and CMEs actually happened.

WORK SHEET:

Q1: What would you expect would happen to the density of the atmosphere through which the satellite is flying? Explain. What effect might this have on the satellite’s orbit? Explain. ___________________________________________________________________________ ___________________________________________________________________________ ___________________________________________________________________________ Go to the spreadsheet page entitled “Atmosphere.” In the cell for "Percentage of Temperature increase for MSIS Model (X%):" [E5] enter 10 for a 10% increase in the temperature. Q2: Go to the page entitled “Altitude vs. Mass Density” and examine the curves on the graph. How are they different from the previous graphs? Describe. Draw the new curves into the previous graphs. Comment whether the graphs are consistent with the answer you provided to question 1. ___________________________________________________________________________ ___________________________________________________________________________

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Satellite Communication Lab Manual

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