CALIFORNIA STATE UNIVERSITY, NORTHRIDGE. Decoding Signals From Weather Satellites Using Software Defined Radio

Transcription

1 CALIFORNIA STATE UNIVERSITY, NORTHRIDGE Decoding Signals From Weather Satellites Using Software Defined Radio A graduate project submitted in partial fulfillment of the requirements For the degree of Master of Science in Electrical Engineering By Min Jae Lee May 2018

2 The graduate project of Min Jae Lee is approved: Dr. Nagwa Bekir Date Professor James A Flynn Date Dr. Xiaojun Geng, Chair Date California State University, Northridge ii

3 Acknowledgement I would like to thank Dr. Xiaojun Geng, Professor James Flynn, and Dr. Nagwa Bekir for being a part of my committee. I would also like to thank Dr. Sharlene Katz for helping me to get started on this project. iii

4 Table of Contents Signature Page... ii Acknowledgement... iii List of Figures... vii List of Tables... x ABSTRACT... xi Chapter 1: Introduction... 1 Chapter 2: Satellite Application NOAA 15 Satellite NOAA 18 Satellite NOAA 19 Satellite METEOR M2 Satellite Satellite Signals Automatic Picture Transmission Low Rate Picture Transmission Satellite Tracking Satellite Tracking Software GPREDICT Orbitron N2YO Chapter 3: Antenna Half Wave Dipole Antenna Turnstile Antenna iv

5 3.2.1 Normal Mode Axial Mode Turnstile Antenna Polarization Turnstile Antenna Specification Double Crossed Dipole Antenna Quadrifilar Helix Antenna Chapter 4: Software Defined Radio History of Software Defined Radio Ideal Software Defined Radio Software Defined Radio Receiver Architecture Traditional Super-Heterodyne Receiver SDR Application Commercial SDRs HackRF One RTL-SDR Chapter 5: Decoding Process of APT and LRTP Signals Recording APT Signal Resampling APT Signal Decoding APT Signal Decoding LRPT Signal Chapter 6: Results NOAA NOAA v

6 6.3. NOAA METEOR M Conclusions References vi

7 List of Figures Figure 2.1: Communication Satellite... 3 Figure 2.2: Navigational Satellite... 4 Figure 2.3: Polar Orbiting Environmental Satellite (POES)... 5 Figure 2.4: Circularly Polarized Wave... 8 Figure 2.5: QPSK Signal Figure 2.6: QPSK Constellation Diagram Figure 2.7: Two Line Element Set (TLE) Figure 2.8: GPREDICT Satellite Tracking Software Figure 2.9: GPREDICT Satellite Prediction Figure 2.10: Orbitron Satellite Tracking Software Figure 2.11: N2YO Satellite Tracking Website Figure 2.12: N2YO Displaying METOER M Figure 2.13: N2YO s Future Pass Prediction of METEOR M Figure 3.1: Half wave Dipole Antenna Figure 3.2: Current and Voltage distribution of Half-Wave Dipole Figure 3.3: Diagram of a Turnstile Antenna Figure 3.4: Actual Figure of Turnstile Antenna Used for This Project Figure 3.5: Actual Figure of Double Crossed Dipole Antenna Figure 3.6: Diagram of a Double Crossed Dipole Antenna Figure 3.7: 3D Radiation Pattern of Double Crossed Dipole Antenna Figure 3.8: Quadrifilar Helix Antenna Figure 4.1: Software Defined Radio Receiver Architecture vii

8 Figure 4.2: Traditional Super-Heterodyne Receiver Architecture Figure 4.3: Comparison of Common Commercial SDRs Figure 4.4: Images of HackRF One Figure 4.5: Images of RTL-SDR Figure 5.1: Recording of APT Signal Using GNU Radio Figure 5.2: Using Audacity to Resample Recorded Signal Figure 5.3: WXtoImg Software Figure 5.4: Flow Graph for Decoding LRPT Signal Figure 5.5: SDR# Software Figure 5.6: LRPTrx Software Figure 5.7: LRPTofflinedecoder Figure 5.8: Rectified Image using SmoothMeteor Figure 5.9: LRPT Image Processor Figure 6.1: Signal from NOAA 15 (Date: 03/30, Time: 8:01 AM, Max Elevation: 69 ) 48 Figure 6.2: Signal from NOAA 15 as it Approaches No Line of Sight (Date: 03/30, Time: 8:01 AM, Max Elevation: 69 ) Figure 6.3: Image from NOAA 15 (Date: 03/30, Time: 8:01AM, Max Elevation: 69 ).. 50 Figure 6.4: Multispectral Effect on the Image from NOAA Figure 6.5: Thermal Effect on the Image from NOAA Figure 6.6: Signal from NOAA 18 (Date: 03/18, Time: 9:04 AM, Max Elevation: 83 ) 53 Figure 6.7: Image from NOAA 18 (Date: 03/18, Time: 9:04AM, Max Elevation: 83 ).. 54 Figure 6.8: Multispectral Effect on the Image from NOAA Figure 6.9: Thermal Effect on the Image from NOAA viii

9 Figure 6.10: Signal from NOAA 19 (Date: 03/25, Time: 4:21 PM, Max Elevation: 85 ) 57 Figure 6.11: Image from NOAA 19 (Date: 03/25, Time: 4:21 PM, Max Elevation: 85 ) 58 Figure 6.12: Multispectral Effect on the Image from NOAA Figure 6.13: Thermal Effect on the Image from NOAA Figure 6.14: Signal from METEOR M2 (Date: 03/19, Time: 10:14AM, Max Elevation: 75 ) Figure 6.15: Constellation Diagram for Demodulated METEOR M2 Signal Figure 6.16: Signal from METEOR M2 as it Approaches No Line of Sight (Date: 03/19, Time: 10:14AM, Max Elevation: 75 ) Figure 6.17: Constellation Diagram for Weak METEOR M2 Signal Figure 6.18: Image from METEOR M Figure 6.19: Image from METEOR M2 with Color Effect Figure 6.20: Infrared Image from METEOR M Figure 6.21: Image from METEOR M2 with Thermal Effect Figure 6.22: Image from METEOR M2 with Vegetation ix

10 List of Tables Table 2.1: Two Line Element Set Format Definition for Line Table 2.2: Two Line Element Set Format Definition for Line Table 3.1: Antenna Specifications x

11 ABSTRACT Decoding Signals From Weather Satellites Using Software Defined Radio By Min Jae Lee Masters of Science in Electrical Engineering Ever since the first successful launch, tremendous advancements in satellites have been accomplished. Currently, there are over a thousand functioning satellites orbiting the Earth which shows how much people depend on it. Satellites play a huge role in people s everyday life as there are numerous applications associated with satellites. Some of the more common applications for satellites include communication and navigation, but weather satellite will be the main topic for this project. Specifically, the weather satellites considered in this project include NOAA 15, NOAA 18, NOAA19, and METEOR M2. These weather satellites transmit a coded signal that contains parts of the Earth as an image. In this project, the signals transmitted by the weather satellites mentioned above are received and captured with antennas and decoded using a software defined radio. A proper antenna design is crucial for a good satellite reception as well as the location of the antenna placement. With a good satellite reception, many different software were used to decode the signals for this project. xi

12 Chapter 1 Introduction TIROS-1 was the first successful weather satellite launched by NASA on April 1, 1960, and ever since, weather satellites have been primarily used to monitor the weather conditions and the climate of the Earth. The weather satellites for this project works by taking an image while in orbit and transmitting a signal called automatic picture transmission or low rate picture transmission. The main objective of this project is to receive the satellite signals, and decode them and produce an image showing the current weather conditions of the Earth. In chapter 2, different types of satellites and its applications will be mentioned. It will also present satellite tracking and different types of software used to accomplish the tracking. To achieve a good satellite reception, a proper antenna is needed to detect and received the signal. Chapter 3 will discuss choosing and designing the proper antenna for weather satellite reception. Many different types of antennas have the capability to receive this satellite signal, but one particular antenna was chosen for this project. After the signal is received and stored in a file, it has to be modified and decoded in order to get the final results. Software defined radio (SDR) will be used to decode the signals; in chapter 4, specification about the SDRs used in this project will be discussed. Chapter 5 goes over the decoding process for different satellite signals. Finally, Chapter 6 shows the resulting images of the decoded signals from four different satellites which display the weather conditions of the Earth. 1

13 Chapter 2 Satellite Satellite is such a familiar term to everyone regardless of their educational or professional background. Satellites are used by many people from all over the world, knowingly or not, because it has numerous applications. A formal definition of a satellite is any natural or artificial object moving in a curved path around a star, planet, or the moon, especially in a periodic elliptical revolution. In the present context, a satellite is referred only to artificial object that has been purposely placed into orbit and has payloads depending upon the intended application. Currently, there are over 1,000 functional satellites orbiting Earth and it wasn t until the first successful launch of a satellite in 1957 called Sputnik 1 that forced other countries, especially America, to invest more resources in spaceflight capability, which allowed more satellites to be placed into orbit. At first, the idea of satellite was to place an object in space which would orbit the Earth as the same rate as the rotation of the Earth, so that the satellite would appear to be stationary with respect to Earth, but there are satellites which are not stationary with respect to Earth s surface due to the intended application Application Satellites are used every day and it has various applications with the growing number of satellites orbiting the Earth. Different applications for satellites include: Communication Earth Observation Military 2

14 Navigation Weather Forecast The communication satellite is one of the most important types of satellites that are used widely. From one location of the Earth, a source transmits a radio frequency signal directed to the satellite, and the satellites amplify the received signal through a transponder and relay the signal to a receiver that is on a different location of the Earth. Figure 2.1: Communication Satellite [1] Fig. 2.1 displays a closed link of two stations through a communication satellite. The common applications of communication satellite include telephony, television, and radio. These systems all work in the same way by relaying data from one location to another. Some advantages of using communication satellite for television includes high-quality data reception and access to hundreds of channels. Another way to utilize satellites is to understand and analyze the Earth s environmental conditions. Earth observation satellites are used to detect natural disasters in a sensible manner, and to monitor Earth s natural resources for future management. Earth observation satellites are also used in agriculture, geology, and forestry to gather useful data such as crop inventory, forest road maps, and 3

15 aerial photography. One application that most people are probably familiar with is navigation. Navigational satellites, as illustrated in Fig. 2.2, are the key factors in a global positioning system. The technology of navigation system is further advancing, and with the help of more powerful satellites and better coding schemes, it provides the users with more accurate and reliable services. GPS is able to provide the user with the current location and guides the user by sending directions to the intended destination, all in real time. There are around 24 GPS satellites orbiting 20,000 km above Earth, but only 3 GPS satellites are needed and 4 would provide a more accurate estimate. With 4 satellite signals, the users can calculate his or her position in 3 dimensions: latitude, longitude, and altitude. Figure 2.2: Navigational Satellite [1] The signals sent from the satellite, which travels at the speed of light, are received by the user on Earth, and they can be used to calculate how far away the satellite is based on the time it acquired to receive the signal. After the GPS calculates the distance from at least 3 satellites, it computes its position by using a process called trilateration. While GPS 4

16 satellites are very useful in everyday life, weather forecasting satellites are just as important. Weather satellites are primarily used to monitor the weather conditions and the climate of the Earth. By taking an image of the Earth and transmitting it through a signal, the weather satellite can be used to monitor the climate of the Earth. The user can decode the received signal to produce an image containing weather information such as current cloud conditions. Weather satellites can be classified into two different categories: geostationary satellite and polar orbiting satellite. Geostationary weather satellites are about 36,000 km above Earth and it takes 24 hours to orbit the Earth one time, meaning that they are in fixed position relative to Earth. Polar orbiting environmental satellites will be the topic of interest for this project. Figure 2.3: Polar Orbiting Environmental Satellite (POES) [1] Polar orbiting environmental satellites orbit the Earth at a much lower distance, and this allows the satellite to orbit the Earth more frequently. While polar orbiting satellites cannot provide a continuous viewing of one location, it can provide global coverage which can be useful to monitor the climate of the Earth. As shown in Fig. 2.3, polar 5

17 orbiting environmental satellite scans the Earth s surface to provide a global coverage. Another advantage of polar orbiting satellite is that they provide higher resolution image since they are much closer to Earth. Some of the polar orbiting weather satellites include NOAA-15, NOAA-18, NOAA-19, and METEOR M NOAA 15 Satellite NOAA 15 is a weather forecasting satellite run by National Oceanic Atmospheric Administration (NOAA). NOAA 15 was launched on May 13, 1998, and it is still operational. NOAA 15 transmits automatic picture transmissions (APT) signals at MHz and orbits the Earth every 101 minutes NOAA 18 Satellite NOAA 18 is also a weather forecasting satellite run by NOAA. NOAA 18 was launched on May 20, 2005, making this newer than NOAA 15. NOAA 18 is very similar to NOAA 15 in many forms, and it also orbits the Earth at a similar rate of NOAA 15. NOAA 18 transmits APT signals at MHz NOAA 19 Satellite NOAA 19 was launched on February 6, 2009, and it transmits APT signals at MHz. NOAA 19 is also run by NOAA and is the most recent satellite compared to NOAA satellites. NOAA 15, 18, and 19 all are very similar satellites as they transmit similar signals and have the same purposes. It is very interesting to see that these satellites are still functioning despite the fact they were launched many years ago. 6

18 2.1.4 METEOR M2 Satellite Unlike the NOAA weather satellites mentioned above, METEOR M2 is a Russian satellite that is a part of the METEOR-M series of polar orbiting weather satellites. This satellite was launched on July 8, 2014, and the transmission signal is very different compared to the NOAA satellites, as it uses low rate picture transmission signals instead of APT signals Satellite Signals Transmission and reception of radio frequency signals are everywhere, and signal polarization is an important area of discussion. The transmitting source can send the signals with different polarizations: vertical, horizontal, and circular. Vertically polarized signals provide omnidirectional communication, and it is good for moving vehicle communication. Horizontally polarized signals are bidirectional, but it is more tolerant to interference. Vertical and horizontal polarized signals are typically used by television stations and radio broadcast stations, but many of the satellites use circularly polarized signals. There are two types of circularly polarized signals: right-hand circular (RHC), when rotation is clockwise, and left-hand circular (LHC) when rotation is counterclockwise. As shown in Fig. 2.4, circularly polarized wave will emit energy in both horizontal and vertical plane and all planes in between. Circular polarization is preferred for satellite communication because it is more tolerant of atmospheric conditions. As RF signals propagate through different mediums, they tend to reflect and be absorbed by the surroundings. Linearly polarized signals are more susceptible to signal power loss because the antennas can only receive it through a single plane, but 7

19 circularly polarized signals can be received in all planes which lead to minimized power loss. Figure 2.4: Circularly Polarized Wave [3] Another advantage of a circularly polarized signal is that it solves multipath interference problem. Multipath interference occurs when the signal travels through multiple paths, and it causes interference to itself since the receiver receives multiple of the same copies at different times. Circularly polarized signals are not affected by multipath interference because when the signal is reflected, the polarization changes from RHC to LHC and vice versa. Although circular polarization may be more complicated and expensive, it is used to achieve better quality and reliability Automatic Picture Transmission NOAA-15, NOAA-18, and NOAA-19 weather satellites transmit a signal called automatic picture transmission around 137 megahertz. For automatic picture transmission (APT), The transmitted carrier is FM modulated on MHz and approaches MHz depending on the satellite index. An AM subcarrier on 2400 Hz 8

20 modulates image data, as amplitude variation along a grayscale. Each word is sampled using 8 bits/pixel along one row, which lasts exactly 0.5 seconds (2 lines/second). [14] APT protocol was specifically developed for weather satellites, and it contains a live weather image of the area with 256 levels of amplitude. The bandwidth of this signal is 34 KHz, and since this is an analog signal, the quality of the decoded image will be worse compared to a digitally modulated signal Low Rate Picture Transmission Low rate picture transmission, short for LRPT, is used by Meteor M2. Meteor M2 satellite was launched on July 8, 2014, which is much more recent than the previously mentioned NOAA satellites. The satellite, being much newer, uses a different type of transmission to transmit signals. LRPT is a digitally modulated signal using quadrature phase shift keying (QPSK) with a data rate of 72Kbps. QPSK modulation scheme is used widely in the modern digital communication system for several reasons. One of the reason is QPSK, when compared to binary phase shift keying (BPSK), encodes two bits per symbol and it minimizes the bit error rate while doubling the data rate. QPSK signal can be mathematically defined as: Si(t) = A cos(2πf c t + θ i ) (2.1) From equation 2.1, QPSK carries information on the phase of the signal. The θ i represents the phase difference, which is 90 degrees, A represents the amplitude, and f c represents the carrier frequency of the signal. Different parameters can be altered to achieve different types of modulation. 9

21 Figure 2.5: QPSK Signal Seen in Fig. 2.5, there is no change in the phase of the signal when the information is repeated. As the information is changed, for instance, from 10 to 11, there is a 90- degree difference in the phase. The constellation diagram is widely used to represent a signal that is modulated by a digital modulation scheme. Figure 2.6: QPSK Constellation Diagram Fig. 2.6 is the constellation diagram which allows for easier visualization of the different phases. Compared to the APT, LRPT uses QPSK modulation with a bandwidth of 120 KHz, resulting in way more data. With more complicated modulation and more data, it takes more effort to decode LRPT signals. Although it takes more steps to decode the 10

22 LRPT signal, the result is more rewarding since the quality of the picture will be much better Satellite Tracking To receive signals from polar orbiting satellites, satellite tracking is a very important step because one needs to know when the next satellite pass will occur. Satellites follow an elliptical orbit around the Earth, and Kepler s law helps people understand and visualize the satellite s motion by its geometry of the orbit. Mainly, two types of formats are used for orbital elements to track satellites. Two-line Element Set (TLE) is one type of format that is often used, and it will be used for this project as well. The software and programs that are commonly used for satellite tracking adopt an Earth-centered orbital Keplerian Two Line Elements. Quoted from [6], Keplerian elements, also called Two Line Elements or TLEs, are the inputs to the SGP4 standard mathematical model of spacecraft orbits used by most amateur tracking programs. Software products that use TLEs to track satellites perform computations and give a very close approximation of where the satellite currently is located, and when the satellite will be in view. The satellite tracking software allows the user to experiment with the satellite knowing that it is in the vicinity. One of the assets of the software that uses TLEs to track satellite is that it predicts future satellite passes according to the user s location. Figure 2.7: Two Line Element Set (TLE) 11

23 Fig. 2.7 is a TLE of NOAA 19 satellite. Each set of elements for TLE are written to 70 column ASCII line and they contain the necessary information to track the satellite. Table 2.1: Two Line Element Set Format Definition for Line 1 Table 2.2: Two Line Element Set Format Definition for Line 2 As shown in table 2.1 and 2.2, TLE contains all the critical information about the satellite, and an algorithm is implemented using the data from TLE to compute the satellite locations and predictions. Weekly updates to the TLE are necessary since low 12

24 orbiting satellites experience aerodynamic drag which can cause variations in the orbit, and this can lead to tracking errors Satellite Tracking Software There is a vast number of software that allows users to track satellites. Many of them need installations and initial setup to achieve an accurate satellite tracking system GPREDICT One piece of the satellite tracking software used in this project is called GPREDICT. This software can track a large number of satellites in real-time and display their positions and other information on the screen. Figure 2.8: GPREDICT Satellite Tracking Software 13

25 Fig. 2.8 is a screenshot of the software as it is tracking four different satellites. The four satellites that are being tracked are NOAA15, NOAA 18, NOAA 19, and Meteor M2. In the above figure, the blue point labeled Home is the location of the user. Each of the four satellites is identified by a yellow dot, and it has the name of the satellite below it. The circle around the satellite indicates the footprint. The footprint of a satellite is the offered coverage from the transponder of the satellite, which means that when the user s location is within the footprint of the satellite, then the signal can be received. In Fig 2.8, the location defined by the blue dot is barely in the vicinity of NOAA 19 satellite, but the elevation is only 9.54 degrees, so although the signal can be received it will not be as strong due to the low elevation levels. Another neat thing that the GPREDICT offers is the satellite predictions. Figure 2.9: GPREDICT Satellite Prediction 14

26 Satellite prediction is very important because it allows the user to see future satellite passes and plan accordingly. In Fig. 2.9, the satellite prediction for NOAA 19 displays the time of each pass along with the date. It also shows how long the satellite will be in the vicinity of the user s location with the elevation level. One benefit of using GPREDICT is that it works on Windows operating system as well as Mac operating system Orbitron Orbitron is another satellite tracking software that was used in this project, as illustrated in Fig Figure 2.10: Orbitron Satellite Tracking Software Orbitron is a satellite tracking software very similar to GPREDICT. It essentially does the same thing by tracking a large number of satellites and providing detailed information 15

27 about each satellite. Similar to GPREDICT, it shows the position of each satellite with its footprint, and it can also predict future passes with great accuracy. Orbitron is only available for Windows operating system and is not compatible with Mac OS. Although Orbitron is not compatible with Mac OS, many people still use it because Orbitron can be used with other software such as SDR#. Both of the satellite tracking systems use TLE to track and predict future satellite passes, and frequent updates to the TLEs are necessary to maintain the accuracy of the tracking system. While many of the software needs to be downloaded and set up correctly to achieve satellite tracking, there is a website that allows for satellite tracking without any installations which is discussed as follows N2YO N2YO is a website that allows for satellite tracking. This is very simple to use since installation is not necessary. Figure 2.11: N2YO Satellite Tracking Website 16

28 Similar to the other two pieces of satellite tracking software mentioned above, the N2YO website displays the location of the satellite with its footprint, as shown in Fig It also shows information of the satellite that is currently being tracked. Multiple satellites can be tracked by using this website but logging in with an account is required. This also uses the TLE to track each satellite as shown in the figure below. Figure 2.12: N2YO Displaying METEOR M2 Fig displays the METEOR M2 s information, and this is very useful for tuning into the satellite s frequency since the downlink frequency of the satellite is displayed. It also has information about the signal that the satellite is sending. The METEOR M2 is using 17

29 QPSK modulation to send out signals at a rate of 72Kbps. A very useful property that N2YO offers is that it predicts future satellite passes up to ten days in advance. Figure 2.13: N2YO s Future Pass Prediction of METEOR M2 Fig displays METEOR M2 s passing prediction. As the predictions are further away in days, the accuracy of the prediction might change a little such as elevation angles. 18

30 Chapter 3 Antenna Antennas are used everywhere as they play a critical role in wireless communication. An antenna is a transducer, which is a device that converts one form of energy to another. Antenna converts electrical current into electromagnetic waves for transmitting signals and vice versa for receiving signals. The first antenna was built and tested in 1888 by Heinrich Hertz, who was a German physicist, and antennas have become an essential component of wireless communication ever since. Without antennas, wireless communication cannot exist. Antennas are used for many applications including AM/FM radio broadcast, cell phones, broadcast television, radar, and satellite communications Half Wave Dipole Antenna There are many different types of antenna, and one of the simplest and most commonly used antenna is the dipole antenna. To be more specific, the dipole antenna is called a half wave dipole antenna, and the term half wave comes from half of the wavelength of a signal. The wavelength of a signal can be calculated if the frequency of the signal is known with the formula given below: λ = c f (3.1) In the above equation, the λ represents the wavelength, c represents the speed of light, and f represents the frequency. With the equation above, one can deduce that the frequency is inversely proportional to the wavelength thus higher frequency leads to smaller wavelength. This is important to understand because the size of the antenna is 19

31 directly related to the wavelength of the signal, so if the frequency of the signal is high, then the wavelength will be small, and the size of the antenna will also be small. The figure below displays the dimension of a half wave dipole antenna respect to the wavelength of the signal. Figure 3.1: Half wave Dipole Antenna As shown in Fig. 3.1, each section of the antenna is a quarter of the wavelength long, and both combined give the length of half of the wavelength of a signal. There are many reasons for using a half wavelength over a full wavelength antenna. One of the main reason that the half wave dipole antenna is used is that it takes very little effort to achieve a good match to the commonly used 50 ohm or 75 ohm coaxial transmission line. For a full wave dipole antenna, the voltage rises to a maximum while the current falls to a minimum at the center feed (input connection) of the antenna. When the voltage is very large, and the current is very small, the impedance of the antenna becomes very large which appears to be an open circuit. The opposite happens at the center feed of the 20

32 antenna when the length of the dipole antenna becomes half of the wavelength of a signal. Figure 3.2: Current and Voltage distribution of Half-Wave Dipole Fig. 3.2 is the visualization of the current and voltage distribution of the half wave dipole at the center feed point. At the center feed point of the antenna, the current is at a maximum point while the voltage is at a minimum point. Having the maximum current, I 0, at the input of the antenna, the radiation resistance equation can be written as shown below: R r = 2P rad I o 2 (3.2) The total radiated power from the dipole antenna is represented by P rad, and it is defined by the given equation: P rad = 2π 0 π U(θ) sin θ dθdφ 0 (3.3) The radiation intensity produced by the dipole is represented by U(θ), and further simplifying the equation yields to: 21

33 P rad = 1 2 (2π) ηi o 2 cos2 π π ( cos θ) 2 (2π) 2 0 sin θ 2 dθ = I 0 (3.4) After simplifying the equation for the total radiated power, we can plug it back into the radiation resistance equation to find the input resistance as follows: R r = I 0 2 I o 2 = Ω (3.5) The input resistance can be easily found by the equations provided above; however, it is much more complex to solve for the reactive part of the input impedance, so details have been omitted. The reactive part of the input impedance of a dipole is a function of its length, and at the resonant frequency, the final value of the dipole antenna s input impedance is provided as: Z in = j42.5 Ω (3.6) The input impedance of the half wave dipole antenna is slightly inductive. To combat for the inductiveness of the impedance, the length of the antenna can be reduced slightly to 0.48λ instead of 0.5λ which makes the antenna resonant. At a resonant frequency, the inductive reactance cancels out with the capacitive reactance, making the load purely resistive. This is a useful operating point for the antenna and the input impedance changes to: Z in = 70 + j0 Ω (3.7) With the value of this input impedance, the impedance matching of the antenna to the transmission line becomes much easier and realizable. Although half wave dipole antennas might look simple and easy to construct, it plays a huge roll in the design of 22

34 antennas because many different antennas such as Yagi-Uda antenna and turnstile antennas are derived from half wave dipole antenna Turnstile Antenna A turnstile antenna consists of a two half wave dipole antennas that are crossed at a right angle. For this reason, a turnstile antenna is often referred as a crossed dipole antenna. Turnstile antenna is an omnidirectional antenna that can be used for linear or circular polarization. A turnstile antenna is a superb antenna for low Earth orbiting satellite and polar orbiting satellite. It also is used for FM radio, TV broadcasting, and in military communications. It is quite easy to build given that the crossed dipoles antennas are the main element in turnstile antenna. The two dipoles are fed 90 degrees out of phase, and therefore a phasing cable is needed with a proper length to counteract the phase shift. Phasing cable will delay the phase of one signal by 90 degrees which will align the two signals in a constructive manner. Fig. 3.3 is a diagram of turnstile antenna with the phasing cable. Figure 3.3: Diagram of a Turnstile Antenna [9] 23

35 The length of the phasing cable is dependent on the frequency of the signal, and it is usually quarter wavelength of a signal. A turnstile antenna can operate in two different modes. Depending on the mode of operation, it can either receive linearly polarized waves or circularly polarized waves Normal Mode When the turnstile antenna operates in normal mode, it can transmit and receive either horizontally polarized or vertically polarized waves. In normal mode, the radiation is very close to omnidirectional. By stacking the turnstile antennas vertically which are fed in phase, it can achieve better antenna radiation and leads to increase in the gain Axial Mode In the axial mode, the turnstile antenna radiates circularly polarized waves. In the axial mode, conducting elements called reflectors such as a rod or a screen is added below the crossed dipole antenna. The distance from the dipole antenna to the reflector is about a quarter wavelength long. For the turnstile antenna that is used in this project, it is designed to be right hand circular polarized. As the dipole elements receive the signal, the reflector reflects the signal with right hand circularly polarized waves. By locating the reflector quarter wavelength behind the crossed dipole elements, the reflected signals become in phase and adds to the original received signal Turnstile Antenna Polarization It is important to note that the polarization of the antenna is very critical, especially for circular polarization. A linearly polarized antenna, either vertically or horizontally, can 24

36 receive circularly polarized signals, but it will lose 3dB in power which is half the power. This can be tolerable depending on the application, but when the antenna is left hand circularly polarized, and the receiving signal is right hand circularly polarized, the loss will be severe, and signals will not travel through the antenna. The turnstile antenna used for the project is circularly polarized to match the polarization of the incoming signal from the satellite Turnstile Antenna Specification A turnstile antenna was purchased online for this project. Below image is the turnstile antenna used for this project. Figure 3.4: Actual Figure of Turnstile Antenna Used for This Project In Fig 3.4, the antenna was designed for the reception of low Earth orbit satellites and works in the frequency range of 137 MHz to 152 MHz. When the satellite is highly elevated, the antenna has a gain of 0 db, but at lower elevation angles, it has a gain up to 4 db. It is important to note the gain of the antenna at low elevation angles. At low elevation angle, the satellites signals are weaker compared to high elevation, thus having a gain up to 4dB at low elevation is outstanding. 25

37 Table 3.1: Antenna Specifications Technical Specifications Frequency Range MHz Polarization Circular Right Impedance 50 Ω VSWR < 2:1 Cable 1 meter RG-58 coaxial cable Total Height 1300 mm Diameter 1065 mm Weight 2 Kg Max Pole Diameter 50 mm This turnstile antenna is simple to assemble, and the specification in table 3.1 allows it to receive proper signals from the weather satellites, so this antenna was chosen to be used for this project Double-Crossed Dipole Antenna A double-crossed dipole antenna consisting of two pairs of crossed dipole antenna was constructed for this project. Figure 3.5: Actual Figure of Double-Crossed Dipole Antenna 26

38 Fig. 3.5 is the double-crossed dipole antenna that was constructed for this project. For the conducting element of the dipole, galvanized steel was used. The diameter of the dipole antenna is small compared to the turnstile antenna. As the dimensions of the radiators increase, the bandwidth of the antenna increases as well, but this was not important because the double-crossed dipole antenna was strictly designed for 137 MHz reception. The double-crossed dipole antenna was built using the diagram shown in Fig 3.6. Figure 3.6: Diagram of a Double-Crossed Dipole Antenna [10] A turnstile antenna and a double-crossed dipole antenna are very alike and contain similar elements, but they are structured differently. In Fig 3.6, the first pair of the dipole, dipoles 1 and 2, are fed in phase while the second pair of the dipole, dipoles 3 and 4, are fed out of phase. To accommodate for this, the second pair of the dipole is fed 90 degrees 27

39 later than the first pair. To introduce a 90 degrees phase delay, the coaxial used to connect dipole 3, and 4 were quarter wavelength longer than the first pair of the dipole. By introducing a phase delay, it aligns the received signals from both pairs of the dipole, and the antenna produces a nice radiation pattern as shown below. Figure 3.7: 3D Radiation Pattern of Double Crossed Dipole Antenna [10] In Fig 3.7, the omnidirectional radiation pattern of the antenna is excellent for receiving the desired weather satellite signals. Pieced of wood was used for the structure of the antenna to hold each the dipoles. After building this antenna, it was tested but not used as much as the turnstile antenna because of the portability. The antenna was tall, and the height was fixed so it is difficult to transport the antenna, however, the turnstile antenna can be disassembled and reassembled which makes it convenient. For the 137 MHz polar orbiting satellite reception, the quadrifilar helix antenna (QFH) might perform the best Quadrifilar Helix Antenna Quadrifilar helix antennas are used for ultra-high frequency and microwave communications. Ever since the growth of satellites application, the QFH antennas have 28

40 become a popular choice for antenna design. The QFH antenna is used often because With the explosive growth of satellite-based services, the ability to receive or transmit a tight beam of circularly polarized radiation while minimizing unwanted radiation is imperative to maintaining good communication. The axial-mode helical antenna provides a high performance and robust antenna platform both in space as well as on the ground. [10] The QFH antenna is perfect for polar orbiting weather satellite signal reception, and it indeed performs better than both the turnstile antenna and double-crossed dipole antenna mentioned above. Figure 3.8: Quadrifilar Helix Antenna Although the QFH performs better compared the turnstile antenna, it was not used for this project because it was difficult to build, not portable, and hard to purchase because not many places sell it. If the QFH antenna were available, it would have been the first choice because it is an ideal antenna for weather satellite reception. 29

41 Chapter 4 Software Defined Radio Software defined radio is a radio frequency communication device that uses software to performs processing of the signal instead of using hardware, and it has been around 30 years since software defined radio was first introduced History of Software Defined Radio In 1991, the necessity of software defined radio was first introduced in a military application. Its primary objective, originating from the U.S. Air Force, was to have a single radio that could support ten different military radio protocols and operate anywhere between 2 MHz and 2 GHz. A secondary goal was the ability to incorporate new protocols and modulations, thereby future-proofing the radio hardware. [12] In 1992, Joseph Mitola published the first ever IEEE paper on software radio and now is referred to many people as the godfather of software radio. As time went on, development in software defined radios was advancing and in 2001 GNU Radio was introduced. GNU Radio is an open source software that provides blocks to represent a function component which is used for signal processing. This is useful because it allows the users to manipulate the system to achieve specific goals, making GNU Radio the most popular SDR development toolset. The Federal Communications Commission (FCC) approved the use of commercial software defined radio in the USA in 2004 with the idea that the software defined radios will bring benefits to consumers because it will be used more creatively and efficiently for different applications. The FCC believed that this was the first step for a radio technology revolution. Ever since, software defined 30

42 radios have become more popular amongst engineers, professionals, hobbyist, and students. One advantage of using an SDR is flexibility which allows the user to incorporate and change additional functionality. SDR can be identified as a class of radios which can be reprogrammed and reconfigured through software for the specific needs. For this reason, SDR will be the main instrument used to accomplish the goals of this project Ideal Software Defined Radio Software defined radio is more flexible compared to the traditional receiver because it digitizes the signal at earlier stages. An ideal SDR receiver would be able to convert the analog signal to digital while it is still in the RF range, thus it would only contain an antenna and an ADC. A DSP will read the converted signal from ADC, and the software transforms the stream of digital bits to any other form of the required application. An ideal SDR transmitter is very similar, but instead of ADC, digital to analog converter (DAC) is connected directly to the antenna. Although an ideal SDR transceiver may seem simple to achieve, it is not completely realizable because of the limitations of the technology. The challenge of an ideal SDR is to convert the signal from analog to digital or vice versa at a very fast rate with good accuracy. When the analog signal is converted to digital signal, it must be sampled at a very high rate because the signal is still in the RF range. To sample a signal without losing information and to avoid aliasing, the signal must be sampled at the Nyquist sampling rate. The Nyquist sampling theorem states that to avoid the incorrect representation of the analog signal in digital form, the signal must be sampled no less than 2 times the highest frequency component of the analog signal. For example, to convert an RF signal of 5 GHz, the ADC will have to sample at least 10 31

43 giga-samples per second which are very high sampling rate. These limitations make the idea of ideal SDR more difficult to achieve. To combat the limitations, the ADC takes place in the intermediate frequency Software Defined Radio Receiver Architecture Since it is difficult to realize an ideal SDR with the current technology, the analog to digital conversion takes place in the intermediate frequency. Intermediate frequency (IF) is a frequency where the carrier signal has been shifted higher or lower as an intermediate step of the transmission or reception. For a wireless reception, IF has a lower frequency compared to the RF since it has been shifted down and this is necessary because the ADC in the SDR does not have to sample as fast when the signal is shifted down to the lower frequency. Below is a receiver architecture for SDR. Figure 4.1: Software Defined Radio Receiver Architecture [12] In Fig. 4.1, the signal will be received through the antenna which will pass through a bandpass filter (BPF) to reject any unwanted signals. The signal then must be amplified through a low noise amplifier (LNA) so that the power of the signal becomes high enough to be useful. LNA is a special type of amplifier that introduces minimal 32

44 degradation to the signal to noise ratio (SNR) which helps to keep the overall noise figure of the system low. After the amplification, the signal gets multiplied with the local oscillator through the mixer. The local oscillator is a tunable device which changes its frequency depending on the incoming signal to produce an intermediate frequency. When the signal is mixed with the local oscillator, it produces two different signals. The first signal is lower in frequency by the difference of the frequency in the signal and the local oscillator, and the second signal is higher in frequency by the sum of the frequency of the signal and the frequency of the local oscillator. The sum of the frequency is not wanted so another filter is used to reject the summed frequency. The signal is now at the IF and gets amplified once more which is then converted to digital signal by the ADC. In this simple example, there is only one IF stage, but for more complex design, there are usually several stages of IF. Once the analog signal is converted to a digital signal, it becomes easier to manipulate using different software, and this is the main purpose of the SDR. The earlier conversion of the analog signal to the digital signal allows the SDR to have fewer physical components while allowing it to be used for more applications compared to the traditional super heterodyne receiver Traditional Super-Heterodyne Receiver Alternate to software defined radio is a super heterodyne or a homodyne receiver, and it can also be used for receiving signals. Super heterodyne receiver is more of a traditional way of receiving signals which use frequency mixing technique to shift the frequency of the wanted signal. 33

45 Figure 4.2: Traditional Super-Heterodyne Receiver Architecture [12] Fig. 4.2 is the super heterodyne receiver architecture, and it has more physical components compared to the SDR receiver architecture. Starting from the left in the above figure, the signal is received through the antenna which then passes through the band pass filter. The signal is amplified through the LNA and is mixed with the local oscillator to produce a signal with wanted intermediate frequency. The signal is followed by another filter and is amplified again through the Automatic Gain Control (AGC) amplifier, and up to this point, the super heterodyne receiver and the SDR are identical. In the case of SDR, the analog signal is converted to a digital signal at this stage, but in the super heterodyne receiver, the signal is mixed by another set of 2 mixers with a 90 degrees phase shift (used for I and Q channel) to convert from intermediate frequency to baseband. Finally, the signal is digitized using analog to digital converter for digital signal processing (DSP). It is important to realize that the analog to digital conversion is done at the baseband for the super heterodyne receiver which results in having more physical components compared to the SDR. 34

46 4.5. SDR Application Instead of using actual hardware components, the SDR uses software to implement components such as amplifiers, filters, mixers, detectors, modulators, demodulators, etc. By doing so, it allows the user to incorporate and change additional functionality which makes the SDR a more flexible device. Due to its ability to be adjusted for different situations, SDRs are used for many applications. Some of the SDR applications include: Receive Broadcast Radio Receive VHF Amateur Radio Radio Astronomy Receiving GPS Signals and Decoding it Watch Analog Broadcast TV Use it as a Spectrum Analyzer Listening to Satellites and the ISS Building a GSM Network Sniffing WIFI Packets Experimenting with LTE Experiment with Wireless Technology The list above is few of many things that can be accomplished with the SDR. To perform different applications with the SDR, all one needs is a different software capable of performing for the needs. Many software already exists for different applications due to its popularity, but it is not limited to the ones that already exist because anyone with the 35

47 skills can create a software compatible with the SDR for any application. This is the attraction and the strength of SDR Commercial SDRs There are many commercial SDRs available for everyone. Depending on the specifications of the SDR, the price may vary drastically. Most of the SDRs, not if all, have the function to receive and few of them have the ability to transmit as well. Figure 4.3: Comparison of Common Commercial SDRs Fig. 4.3 is a comparison of commercial SDRs. Most of the SDRs have the same functionalities, but some SDRs cost much more because their specifications are rated higher. Depending on the application, different SDRs can be purchased and used. There are many software out there that are compatible with many of the common SDRs since there are a lot of demands. 36

48 4.6.1 HackRF One HackRF One is one of the SDRs that was used for this project. With a proper antenna, HackRF One can pick up signals ranging from 30MHz all the way up to 6GHz. Although transmission of a signal is not necessary for this project, HackRF One was purchased because it is able to transmit signals. Many experiments were conducted prior to this project with HackRF One, some consisting transmission of few signals. Figure 4.4: Images of HackRF One Fig. 4.4 is an actual image of the HackRF One. This device is capable of transmitting, but it operates in half duplex mode, meaning that it cannot transmit and receive at the same time. HackRF is powered by a USB micro B connector and when the device is powered on, three LEDs light on (3V3, 1V8, RF) which indicates the three different power supplies. All three LEDs should remain on while using this device. When there is a communication between the SDR and the host computer, the USB LED lights on. The 37

49 RX LED is on whenever the SDR is in the receiving mode, and the TX LED is on whenever the SDR is in the transmitting mode. Since this is a half-duplex system, either the RX or TX can stay on at a single given time. The blue button labeled RESET is used to reset the microcontroller of the device. This operation is equivalent to removing the power to the power supply and supplying the power back to the power supply. Although "DFU" button is not often used, it can be used to update the firmware. Synchronization to use multiple HackRF One is done through the CLKIN and the CLKOUT port. One of the main port used on this device is the antenna port. The antenna port uses SMA connector which has 50 Ohm impedance. To get familiar with HackRF One, a simple telescopic antenna (ANT500) was used which has 50 Ohm impedance that can operate in the frequency range of 75MHz to 1GHz. It is very important that the impedance of each system is matched, otherwise, there will be power loss due to the reflection of the signal. Another SDR that was used for this project is the RTL-SDR RTL-SDR A cheaper SDR compared to the HackRF One is the RTL-SDR which was also was used for this project. RTL-SDR was purchase for this project as a backup. The price of this device is fairly low and it is a good starting device for people who are getting into SDR. This is used as a cheap computer based radio scanner which would have cost a fortune couple of years ago. Since the RTL-SDR is cheaper compared to HackRF one, the specifications are lower. For example, the frequency range for RTL-SDR is only 24MHZ to 1766 MHz. One downside of the RTL-SDR is that it cannot analyze WIFI signals due to its low frequency range, as the frequency of the WIFI signal is 2.4GHz and 5GHz. 38

50 Figure 4.5: Images of RTL-SDR Fig. 4.5 is an actual image of RTL-SDR. Comparing RTL-SDR to HackRF One, there are no fancy LEDs to indicate whether the device is functioning correctly. Although this device has lower specification ratings, it performed just as well as the more expensive SDR and got the job done. 39

51 Chapter 5 Decoding Process of APT and LRPT Signals By using a proper turnstile antenna that is tuned for weather satellites signals at 137MHZ, satellite signals with a high signal to noise ratio (S/N) were received for proper decoding Recording APT Signal Different methods using different software are available for decoding APT signals. To decode the APT signal, it first has to be recorded which can be done by constructing a flow graph through GNU Radio. Figure 5.1: Recording of APT Signal Using GNU Radio Fig. 5.1 is the flow graph that records the APT signal. GNU Radio receiver records the signal at 44.1 KHz and saves it into a waveform audio file format (WAV). An easier way to record the APT signal is by using SDR#. SDR# is an open source software that can be 40

52 used as a spectrum analyzer. SDR# will be discussed in detail in the later section of the chapter Resampling APT Signal The recorded sample rate of 44.1 KHz is too fast and needs to be converted to KHz using a software called Audacity. Figure 5.2: Using Audacity to Resample Recorded Signal Shown in Fig. 5.2, audacity is a free open source software that allows for the editing and recording of digital audio signals. Audacity is available for most of the operating systems out there. Once the signal is resampled, it has to be exported out with a different name. Sometimes the recording of the WAV file is saved in multiple files depending on the software and audacity can be used to combine the segregated WAV files. 41

53 5.3. Decoding APT Signal After the satellite signal is received, recorded, and resampled to KHz, a program called WXtoImg is used to decode signal in WAV file format. Once the signal is decoded, it results in a grayscale image. Figure 5.3: WXtoImg Software Fig. 5.3 illustrates a procedure of WXtoImg software for decoding the APT signal. WXtoImg can be downloaded for free, but it does not contain all the functionality of the program. Although the free version was used for this project, it was enough to obtain many different versions of the images. When recording the signal from the satellite, it is 42

54 important to set the bandwidth of the filter higher than the bandwidth of the signal, otherwise, there will be a loss of data, and it won t allow for proper decoding. 5.4 Decoding LRPT Signal Decoding an LRPT signal is more involved compared to the APT signal. An LRPT signal is a digitally modulated signal so after the signal is recorded, it must be demodulated. The recorded file size will be much bigger since the signal is a digitally modulated signal. Figure 5.4: Flow Graph for Decoding LRPT Signal 43

55 Fig. 5.4 is the steps that lead to the decoded image of METEOR M2. Beginning steps are similar to the steps for deciding the APT signal. SDR# is used as a spectrum analyzer to visualize and record the signal. For LRPT signal, the baseband data must be recorded, and this results in the recording of a large file. Figure 5.5: SDR# Software Fig. 5.5 is a screenshot of SDR# which was used mainly for this project to view and record the satellite signals. To record signals from METEOR M2, the baseband box must be selected instead of the audio box as shown above. This allows the raw IQ data to be recorded into a WAV file format which results in huge file size. When the file size goes over 2GB while recording, it will stop the recording automatically, so the recording button must be pressed again. By doing so, multiple WAV files will be saved on the computer. This is one way to record the signal from METEOR M2, but this method is not 44

56 very efficient. A more efficient way to record the signal will be discussed in chapter 6. After the raw IQ data has been recorded, it has to be demodulated. Figure 5.6: LRPTrx Software Fig. 5.6 is LRPTrx software, and this software is solely used for demodulating the QPSK signal. On the right side of Fig. 5.6, it displays the constellation diagram as the signal is being demodulated. After the signal is demodulated, it exports the file to a different location and the file is now ready for the decoding process. LRPTofflinedecoder is used to decode the demodulated signal. LRPTofflinedecoder allows the user to pick and upload the demodulated file which will be then decoded to produce an image. 45

57 Figure 5.7: LRPTofflinedecoder Fig. 5.7 displays the LRPTofflinedecoder as it is decoding the file. While it is decoding, it displays the constellation diagram to the left. The software decodes and produces 3 separate channels of the image, and the rightmost one is the infra-red (IR) image. Combining the 3 channels will result in a colored image. The color settings for red, green, and blue can be set accordingly. The image is now ready to be rectified. Figure 5.8: Rectified Image using SmoothMeteor 46

58 Fig. 5.8 is the result of the rectified image. After the rectification, the image looks more realistic. After the rectified image is saved, it can be imported into LRPT image processor to produce varieties of the image. Figure 5.9: LRPT Image Processor Fig. 5.9 is the LRPT image processing software. Once the rectified image is imported into this software, it allows the user to export multiple versions of the decoded image. The most difficult part of this project was choosing the right antenna and actually receiving the satellite signal. Countless attempts were made to receive and record the signal for both APT and LRPT. 47

59 Chapter 6 Results 6.1. NOAA 15 The reception of the satellite signals was the most difficult part of this project. Even with the proper antenna design and a good satellite pass, it was difficult to receive good satellite signals. Although a low noise amplifier and a filter can be used between the antenna and the SDR to improve the strength of the signal, it was not used because the transmitted signals were strong. The location of the satellite reception was crucial because in some areas there would be a lot of RF interferences. To combat for this, places with low RF interference such as hiking trails were used for the location of satellite reception. Figure 6.1: Signal from NOAA 15 (Date: 03/30, Time: 8:01 AM, Max Elevation: 69 ) 48

60 Fig. 6.1 is the signal from NOAA 15 displayed on the spectrum analyzer on the top half, and the waterfall display on the bottom half. The SDR can be used as a spectrum analyzer which measures the input signal s magnitude versus the frequency, and this is very useful for signal detection. Water display graphically represents the signal across a range of frequencies for a certain time duration. The magnitude of the signal is color coded. Fig. 6.1 was taken when the signal was very strong and not much interference was present. The frequency of the NOAA 15 satellite is MHz but the frequency of the actual signal received was MHz at that time. The frequency of the signal will change because the satellite is moving at a fast rate and this phenomenon is called the Doppler Effect. Doppler Effect occurs when the source of the signal moves towards or away from the receiver and it causes changes in the frequency. Figure 6.2: Signal from NOAA 15 as it Approaches No Line of Sight (Date: 03/30, Time: 8:01 AM, Max Elevation: 69 ) 49

61 Fig. 6.2 displays the signal of NOAA 15 as the pass from the satellite is almost over. From the figure above, the strength of the signal is very weak compared to the strength of the signal in Fig This happens because the elevation of the satellite approaches 0 as the receiver is not in the range of the satellite. The reception of the weak signal happens at the beginning and the end of each satellite pass. Another important thing to note is the center frequency of the signal which is MHz. This is lower by 5 KHz compared to the signal of the satellite as it is approaching towards the antenna. As the satellite is approaching towards the antenna, the frequency is higher and as the satellite moves away from the antenna, the frequency becomes lower. Since the Doppler Effect is present, the frequency of the spectrum analyzer must be changed to keep the signal frequency centered. Figure 6.3: Image from NOAA 15 (Date: 03/30, Time: 8:01AM, Max Elevation: 69 ) 50

62 Fig. 6.3 is the image decoded from NOAA 15 weather satellite on March 30 th at 8:01 AM with a max elevation of 69. This satellite reception was the best reception made for this project. Clouds and water from the sea can be seen from the grayscale image to the left channel. The right channel displays the infrared image, and the combination of these two channels can be used to create different versions of the image. Figure 6.4: Multispectral Effect on the Image from NOAA 15 51

63 Fig. 6.4 is the image from NOAA 15 weather satellite with multispectral effect. For this option, clouds and seawater is more visible and the color makes it more realistic. Figure 6.5: Thermal Effect on the Image from NOAA 15 Fig. 6.5 is the image from NOAA 15 weather satellite with thermal effect. This version of the image is really useful since it displays the temperature, and can be used to forecast the weather along with the image of the clouds. 52

64 6.2. NOAA 18 The reception of NOAA 18 signal was done in the same way as NOAA 15 reception. NOAA 18 transmits APT signals at MHz, and Doppler shift has to be accounted for as previously mentioned. Figure 6.6: Signal from NOAA 18 (Date: 03/18, Time: 9:04 AM, Max Elevation: 83 ) Fig. 6.6 is the signal of NOAA 18 displayed in the spectrum analyzer and the waterfall graph. Again, the actual received frequency is higher than the actual transmitted frequency since the satellite is moving closer. A strong signal with not too much interference was received for NOAA 18 signal which led to a clean decoded image. 53

65 Figure 6.7: Image from NOAA 18 (Date: 03/18, Time: 9:04AM, Max Elevation: 83 ) Fig. 6.7 is the decoded image from NOAA 18 on March 18 at 9:04 AM with a max elevation of 83. The result of this image was good. It did have some interferences in the middle of the signal which caused lines going across the middle. The left channel is the grayscale image and the right channel is the infrared channel, and the combination of the two images and different sensors can be used to create different versions of the image. 54

66 Figure 6.8: Multispectral Effect on the Image from NOAA 18 Fig. 6.8 is the decoded image from NOAA 18 with multispectral effect option. This allows for a better interpretation of the image and provides more realistic features. 55

67 Figure 6.9: Thermal Effect on the Image from NOAA 18 Fig. 6.9 is the image from NOAA 18 with thermal effect. This shows the temperature of Earth which helps with weather forecasting. 56

68 6.3. NOAA 19 For all the NOAA satellite reception, it is very similar as they are sending the same signals, just at slightly different frequencies. When the signal from NOAA 19 satellite was received, there was a quite a bit of interference. Figure 6.10: Signal from NOAA 19 (Date: 03/25, Time: 4:21 PM, Max Elevation: 85 ) Fig is the NOAA 19 signal displayed on the spectrum analyzer and the waterfall graph. For NOAA 19 satellite reception, there were more inferences and burst of noises compared to NOAA 15 and NOAA 18. This is heavily due to the location of the reception. This reception was made on a top of a building, and the interferences can be seen from the waterfall graph in Fig There were RF interferences within the frequency band of the satellite, and the interference is indicated with a horizontal line in the waterfall graph. 57

69 Figure 6.11: Image from NOAA 19 (Date: 03/25, Time: 4:21 PM, Max Elevation: 85 ) Fig is the decoded image from NOAA 19 satellite on March 25 th at 4:21 PM with a max elevation angle of 85. In the image above, there are many lines that go across both channels which are caused by the interferences that were present. The left channel is the grayscale image, and the right channel is the infrared image. 58

70 Figure 6.12: Multispectral Effect on the Image from NOAA 19 Fig is the image from NOAA 19 with the multispectral effect which allows for a more realistic representation of the image. This effect also displays the black and static lines caused by interferences. 59

71 Figure 6.13: Thermal Effect on the Image from NOAA 19 Fig is the image from NOAA 19 with the thermal effect which allows for the prediction of temperature used for weather forecasting. 60

72 6.4. METEOR M2 Meteor M2 satellite is very interesting because it uses digital modulation to transmit LRPT signals at MHz. Using QPSK as the modulation, it will send more data but the decoded image will be better quality. For simplicity and to reduce the data recorded from METEOR M2 satellite, the QPSK signals were demodulated live, and the demodulated information was stored. Figure 6.14: Signal from METEOR M2 (Date: 03/19, Time: 10:14AM, Max Elevation: 75 ) Fig is the display of the signal in spectrum analyzer and the waterfall graph. The signal to noise ratio for the signal received without any amplifier is close to 20 db. For METEOR M2 satellite reception, the bandwidth had to be around 120 KHz which is way larger compared to the NOAA satellites. The constellation diagram is displayed on the bottom left of Fig. 6.9 as the signal is demodulated live. 61

73 Figure 6.15: Constellation Diagram for Demodulated METEOR M2 Signal Fig is the zoomed in image of the constellation diagram from Fig The signal is strong enough for demodulation without too much introduction of errors. Figure 6.16: Signal from METEOR M2 as it Approaches No Line of Sight (Date: 03/19, Time: 10:14 AM, Max Elevation: 75 ) 62

74 Fig displays the signal from METEOR M2 as the satellite pass is almost over. The signal is still visible, but the strength of the signal is very weak. Demodulating a weak signal will introduce more errors, and this can be shown in the constellation diagram. Figure 6.17: Constellation Diagram for Weak METEOR M2 Signal Fig is the constellation diagram for the METEOR M2 signal as the satellite pass is almost over. When the satellite pass is almost over, the elevation angle is very low, resulting in a very weak signal power. More errors will be introduced when the weaker signal is demodulated, and this can be seen from the constellation diagram from Fig

75 Figure 6.18: Image from METEOR M2 Fig.6.18 is the decoded image from METEOR M2 on March 19 th at 10:14 AM with a max elevation degree of 75. When the signal is decoded, it produces two image channels and one infrared channel. Also, red, blue, and green color adjustment can be made which is the result of Fig

76 Figure 6.19: Image from METEOR M2 with Color Effect Fig is the decoded image from METEOR M2 with color correction. This allows for a very realistic image. From the image, west coast of the USA and some parts of Mexico can be seen. The Pacific Ocean and clouds are also visible. The horizontal lines across the images are caused by noises and interferences. 65

77 Figure 6.20: Infrared Image from METEOR M2 Fig is the image from the METEOR M2 on the infrared channel. This channel, with the combination of other channels, will be used to produce other effects. 66

78 Figure 6.21: Image from METEOR M2 with Thermal Effect Fig is the decoded image from METEOR M2 with thermal effect. The thermal image can be used to forecast the weather. 67

79 Figure 6.22: Image from METEOR M2 with Vegetation Fig is the decoded image from METEOR M2 showing vegetation life. This image is used for agricultural purpose because it can be used to monitor Earth s natural resources. 68