SIGNAL AND SYSTEM LEVEL SIMULATIONS ON WIDEBAND INTERCEPT RECEIVERS

Transcription

1 SIGNAL AND SYSTEM LEVEL SIMULATIONS ON WIDEBAND INTERCEPT RECEIVERS A MASTER S THESIS in Electrical and Electronics Engineering Atilim University by İLTER KARADEDE JANUARY 2014

2 SIGNAL AND SYSTEM LEVEL SIMULATIONS ON WIDEBAND INTERCEPT RECEIVERS A THESIS SUBMITTED TO THE GRADUATE SCHOOL OF NATURAL AND APPLIED SCIENCES OF ATILIM UNIVERSITY BY İLTER KARADEDE IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE IN THE DEPARTMENT OF ELECTRICAL ELECTRONICS ENGINEERING JANUARY 2014

3 Approval of the Graduate School of Natural and Applied Sciences, Atılım University. Prof. Dr. İbrahim AKMAN Director I certify that this thesis satisfies all the requirements as a thesis for the degree of Master of Science. Assoc. Prof. Dr. Elif AYDIN Head of Department This is to certify that we have read the thesis Signal and System Level Simulations on Wideband Intercept Receivers submitted by İlter KARADEDE and that in our opinion it is fully adequate, in scope and quality, as a thesis for the degree of Master of Science. Assoc. Prof. Dr. Ali KARA Supervisor Examining Committee Members Assoc. Prof. Dr. Elif AYDIN Assoc. Prof. Dr. Ali KARA Asst. Prof. Dr. Fatma ÇALIŞKAN Asst. Prof. Dr. H. Taha HAYVACI Asst. Prof. Dr. Serdar ÖZYURT Date:

4 I declare and guarantee that all data, knowledge and information in this document has been obtained, processed and presented in accordance with academic rules and ethical conduct. Based on these rules and conduct, I have fully cited and referenced all material and results that are not original to this work. Signature: İlter KARADEDE

5 ABSTRACT SIGNAL AND SYSTEM LEVEL SIMULATIONS ON WIDEBAND INTERCEPT RECEIVERS Karadede, İlter M.S.,Electrical Electronics Engineering Department Supervisor: Assoc.Prof.Dr. Ali Kara January 2014, 51 pages Electronic Warfare (EW) simulations are mostly designed for only receiver frontend or emitter parameter measurements. This thesis presents signal and system level simulations and emitter parameter measurements on proposed structures. To that end, a proposed wideband intercept receiver is employed and emitter environment is designed using commercial simulation tool. Then, parameter measurement part is employed to measure emitter parameters in a different simulation tool. Finally, simulation results are discussed for system level simulations for wideband intercept receivers and emitter parameter measurements. Keywords: Intercept receiver, Channelized receiver, Electronic Warfare receivers, System level simulations, Emitter parameter measurement iii

6 ÖZ GENİŞBANT RADYO KESTİRİM ALICILARINA YÖNELİK SİNYAL VE SİSTEM DÜZEYİNDE BENZETİMLER Karadede, İlter Yüksek Lisans, Elektrik Elektronik Mühendisliği Bölümü Tez Yöneticisi: Doç. Dr. Ali Kara Ocak 2014, 51 sayfa Elektronik Harp (EH) simulasyonları çoğunlukla alıcı ön-ucu veya yayıcı parametre ölçümleri için tasarlanır. Bu çalışmada, önerilen yapılarla sinyal ve sistem düzeyinde ve yayıcı parametre ölçümleri ve sonuçları sunulmaktadır. Bu amaçla, ticari bir simulasyon aracı kullanılarak yayıcı çevresi ve önerilen genişbant kestirme alıcısı gerçekleştirilir. Ardından, başka bir simulasyon aracı kullanılarak yayıcı parametrelerinin ölçümü için parametre ölçüm bölümü gerçekleştirilir. Son olarak, sistem düzeyindeki simulasyonlar için genişbant kestirme alıcısı ve yayıcı parametre ölçümlerinin sonuçları ele alınır. Anahtar Kelimeler: Kestirme alıcısı, Çok kanallı alıcı, Elektronik Harp alıcıları, Sistem düzeyi simulasyonları, Yayıcı parametre ölçümleri iv

7 To My Parents v

8 ACKNOWLEDGEMENTS I express sincere appreciation to my supervisor Assoc. Prof. Dr. Ali Kara for his advice, criticism, guidance and insight throughout the research. I would like to thank my whole family; for their care on me from the beginning of my life, their prayers, and their trust on me that I could accomplish this task. vi

9 TABLE OF CONTENTS ABSTRACT... iii OZ... iv DEDICATION... v ACKNOWLEDGEMENTS... vi TABLE OF CONTENTS... vii LIST OF TABLES... ix LIST OF FIGURES... x LIST OF ABBREVIATION... xii CHAPTER 1. INTRODUCTION EMITTER ENVIRONMENT GENERATION Emitter Generation Noise Effect SIMULATION ON RECEIVER CONFIGURATION AND RECEIVER FRONT-END DESIGN Frequency Channelization ADC and Switch State EMITTER PARAMETER MEASUREMENT PART Pulse Envelope vii

10 4.2 Double Threshold Emitter Parameters Time of Arrival (TOA) and Time of Departure (TOD) Pulse Width (PW) Radio Frequency (RF) SIMULATION RESULTS Signal Separation Parameter Measurement Results CONCLUSION REFERENCES viii

11 LIST OF TABLES TABLE 1. The gain, loss, NF and cascaded NF of a receiver channel emitters radio frequency parameters due to the changes of NF emitters PW parameters due to the changes of NF ix

12 LIST OF FIGURES FIGURES 1. LFM emitter signal generator in VSS Two LFM pulses generated in VSS Spectrum of LFM pulse in Fig An emitter signal generator in VSS Generated emitter signal in VSS Spectrum of pulse in Fig Cascaded noise figure analyze of a receiver channel Complete system block diagram Some generated emitter signals at 1-5GHz band GHz problematic channel belongs to first structure The first and second channels of the second approach VSS output of the second proposed structure for 1-2GHz channel Two channels of second conversion stage Dynamic time shared switch Captured pulse by the Receiver A radar pulse with various features Flow chart for TOA and TOD indices measurement algorithm Pulse indices graph Flow chart of simple pulse and LFM pulse frequency measurement algorithm x

13 20. Three pulses received with a channel One of the separated pulses in three different pulses FFT of pulse in Fig Matlab GUI for parameter measurements Average error versus NF xi

14 LIST OF ABBREVIATIONS ADC - Analog to Digital Converter ADS - Advanced Design System CFAR - Constant False Alarm Rate CW - Continuous Wave DR - Dynamic Range EW - Electronic Warfare FT - Fourier Transform FFT - Fast Fourier Transform GUI - Graphical User Interface IIP 3 - Third Order Intercept Point LFM - Linear Frequency Modulated LO - Local Oscillator MTD - Moving Target Detection NF - Noise Figure PRF - Pulse Repetition Frequency PRI - Pulse Repetition Interval PW - Pulsewidth RF - Radio Frequency SNR - Signal to Noise Ratio TOA - Time of Arrival TOD - Time of Departure xii

15 CHAPTER 1 INTRODUCTION Electronic Warfare (EW) receiver design has important trade-offs between some parameters such as sensitivity, instantaneous bandwidth, dynamic range, number of simultaneous signals, probability of intercept and dynamic range [1]. If high probability of intercept is desired, then minimum spurious signals, large instantaneous bandwidth and high sensitivity can be arranged and this causes challenging receiver design [1,2]. One of the most important problems for intercept receivers are no detection of threats and false alarms. The platforms are directly effected by these two problems. To provide efficient measurements of intercepted signals and to minimise these two problems are the main design considerations of EW receivers. Therefore, the receiver design procedure must be based on to provide elimination of unwanted spurious signals, which are internally generated by the receiver, high sensitivity, large instantaneous bandwidth and high probability of intercept [1]. Today, mostly wide open, scanning superheterodyne and parallel channelized receivers are used commonly [3]. Mostly, radars classifications are based on the type of waveforms, and they can be pulsed or continuous waveforms. Radar operations can be rated on its pulse repetition frequency (PRF) as high, medium and low PRF, and they change due to the operation limits [4]. Radars are used in many operations such as ground radars, air radars and sea radars. In EW, detection of the enemy threats firstly depends on intercept receivers and emitter parameter measurements. For this purpose, measurements of the pulse parameters take the first place of threats detection [5]. Having a high dynamic range and reasonable wide instantaneous bandwidth are the advances of digital receiver techniques which make them charming in EW receiver 1

16 design. Furthermore, generating a suitable counter measure is easy when the intercepted signals are digitally processed [1]. In EW, extraction of pulse parameters is very important part of an intercept system [5]. The aim of emitter parameter measurements depends on some important steps. The most important four steps are signal sorting, signal identification, jamming information assignment and extraction of radar parameters. Firstly, the deinterleaving of various emitter signals and collecting emitter pulses of individual radars are included in signal sorting. Secondly, classifications of emitter types are included in signal identification. Then, assignment of jamming information and emitter parameter extractions are included in measurement of unknown emitter parameters. At first, emitter parameters measurement is happened in discrete components in circuit form. But now, digital signal processing techniques can help the real time processing [5]. On the other hand, the designers use various simulation tools efficiently. In order to make a cost efficient, easy and complete intercept receivers, these tools are user friendly [3]. There are various simulation tools for commercial and educational purposes on the market. These tools are used in many areas, such as telecommunication and EW. Advanced Design System (ADS), Simulink and AWR Visual System Simulator (VSS) are the most commonly used simulation tools. VSS for high frequency design is more convenient than other simulation tools, because VSS is made for high frequency designs. In order to measure emitter parameters VSS can be used again, but these measurements are made in system level and there could be no understandable and visual data observed. To overcome this situation, Matlab is used in this thesis. There are again various software tools in the market, but Matlab is more user friendly than the other tools in the market. However, the most important reason for using Matlab, VSS is allowed to use only with Matlab instead of other simulation tools. Matlab is very helpful with its built in functions, figures and Graphical User Interface etc. In the reference given in [6], a system, which is used Doppler radar to detect targets, is designed in VSS to receive Doppler radar signals. In that study, Moving Target Detection (MTD) is done with the co-operation of VSS and Matlab. Received signals 2

17 are sent to Matlab for MTD. At last, the results gathered from MTD are shown with several graphs. Moreover, Constant False Alarm Rate (CFAR) is observed with Matlab in [6]. In that study, the signals received by the VSS are processed simultaneously with Matlab. However, in this thesis, the signals received by the VSS is firstly saved with VSS as a data file and this data file is processed in Matlab. The wideband channelized intercept receiver design and emitter parameter measurements efforts contribute to signal level simulations by using AWR design environment and Matlab co-operations. The aim is to reach a high sensitivity and a high probability of intercept. For this purpose, parallel channelized receiver structure was selected and applied according to proposed structure in [2]. According to [2], it can be necessary to intercept simultaneous signals with a channelized receiver. The bank of filters with adjacent frequencies can separate signals. Due to this proposal, the minimum bandwidth of the filter is directly related to the desired minimum pulsewidth. For instance, 100ns pulsewidth can be detected with a receiver that has 10MHz filter bandwidth. However, this kind of filter bandwidth is not practical in real [2]. On the other hand, there is another approach, which is given in [2], provides a proper parallel channelization for wideband intercept receivers. According to the design, it is decided that the intercept receiver has a bandwidth of GHz and this bandwidth is divided in to 2GHz channels due to the reference [2]. This approach not only provides 2GHz channels but also it has some down and up conversion stages. According to this design, all the bands are directly up or down converted to 2-4GHz subbands except the 2-4GHz band. In the lights of this approach, some bands adjacent to 2-4GHz band are not converted directly. These bands are converted up and down to the 2-4GHz subbands to avoid spur problem which is generated by the mixer. However, there is another way to convert these channels. Adjacent to 2-4GHz channels are divided again into two channels and up or down converted to 2-4GHz band based on this approach which is used in this thesis by using VSS [2,3]. In order to measure emitter parameters, a signal processing part is performed in this thesis. There is an effective and attractive proposal given in the reference [5]. A 3

18 hardware noise gate to capture pulse envelope proposed in [5] is implemented in Matlab. Emitter pulse parameters such as radio frequency (RF), pulsewidth (PW) and time of arrival (TOA) are measured with a given algorithm proposed in [5]. In this study, the multipath fading effect is neglected at the beginning of the system so system is assumed to work if true emitter signals are detected. If compared with other system level simulations, the channelized receiver part and emitter parameter measurement part in signal processing are performed at the same study with proposed approaches and done in different simulation tools. Emitter signals are generated in VSS firstly and these emitter signals are received with a wideband channelized intercept receiver in VSS again, at last these received emitter signals are processed to measure emitter parameters in Matlab. In the scope of this thesis, various radar signals such as pulse radar and Linear Frequency modulated (LFM) pulse radar signals are generated to measure emitter parameters by using VSS and Matlab. A wideband channelized intercept receiver has a frequency band of GHz is performed to intercept more than one emitter signals at the same time. After, signal processing part is employed to measure emitter parameters. In order to achieve these goals, two different software platforms are used efficiently. To generate and receive emitter signals, VSS is used in this thesis. Finally, to measure emitter parameters, Matlab is used. This thesis presents the simulations and results of the signal and system level simulations and emitter parameter measurements for intercept receiver. Emitter environment is designed to provide synthetic emitter signals which are used as the input signals. Simulations on receiver configurations are described and designed as proposed in [2]. This proposed approach is performed to receive more than one emitter signal. After that, emitter parameter measurement part is performed as proposed in [5], and implementation of this part is done in Matlab to measure emitter parameters which are radio frequency, pulsewidth and time of arrival. Hereafter, the results are compared and examined by changing several Noise Figures of the receiver. The study done in this thesis is concentrated on software implementations of channelized receiver and signal processing with proposed approaches that are given in the literatures as [2] and [5], respectively. 4

19 The rest of the thesis is organised as follows. In the second Chapter, emitter environment for emitter signal generations is performed and noise effect of the receiver is discussed. In the third Chapter, receiver configurations are described in details. In Chapter four, implementations of signal processing part are described in detail. In the fifth Chapter, the results of the simulations are discussed. Finally, conclusion is presented in Chapter six. 5

20 CHAPTER 2 EMITTER ENVIRONMENT GENERATION In order to create a proper simulation for the channelized intercept receiver, there must be more than one emitter signal exist and fall in different channels. For this purpose, synthetic emitter signals are generated as emitter environment using VSS [3]. As mentioned previously, both synthetically generated pulses and real radar pulses taken from the literature are used as inputs to the system. It is important to study with real emitter pulses to test and examine the receiver part and signal processing part. By this way, reliability of the system is more convenient. Nonetheless, synthetic radar pulses are added to emitter environment generation part to increase the number of emitter signals. Two different type of emitter pulse types are generated in this study. One of them is pulse radar signal and the other is LFM pulse radar signal. PW, PRI and so TOA s are selected by the user. Furthermore, to get a realistic emitter environment a certain amount of noise is added to the signal generation part. In addition, multipath effect is not added to the emitter environment part of the system. A sequence of rectangular pulses is used for a typical emitter signal generations. According to the operation of civilian and military applications, there are some parameters of emitters vary, and by this way various types of emitters can be obtained [7, 8, 9, 10]. Generally, emitter parameters are classified, and there are no too many number of emitters could be obtained in open sources. There is a very popular source which gives some emitter parameters in [11], and they are used in this study effectively [3]. Two kinds of modulated emitter types are used in this study and they are pulsed radar and LFM pulse radar waveforms as discussed. When modelling the noise effects, White Gaussian Noise is added to the system. The use of several groups of blocks in VSS can easily help to generate both pulse radar signals and LFM pulse radar signals. 6

21 In the emitter generation part of this thesis, it is desired that generated radar pulses, which are pulse radar and LFM pulse radar, are received and measured in VSS and Matlab precisely. Sample emitter generation blocks can be seen in Fig. 1 and Fig. 4 for both pulse radar and LFM pulse radar. 2.1 Emitter generation As discussed at the beginning of this chapter, it is decided to add both pulse radar and LFM pulse radar signals to emitter generation part. The main part of an emitter signal, duration of τ centered at t=0 rectangular pulse function ( ) with the amplitude of the signal is as follow, ( ) ( ) (1) In order to generate a periodic function, ( ) is as follows, ( ) ( ) (2) where the periodic function ( ) has PRI (T) and duration of pulse is. Then, periodic rectangular pulse function and coherent modulated CW ( ) that is given as ( ) ( ) [ ( )] (3) Then, ( )is represented as, ( ) [ ( ) ] (4) where ( ) is complex envelope of ( ) and ( ) can be written as, 7

22 ( ) ( ) ( ) (5) Therefore, inphase and quadrature parts of ( ) is as follows, ( ) [ ( ) ( )] (6) where ( ) ( ) ( ) ( ) ( ) ( ) (7) For Linear Frequency Modulated pulse complex radar signal ( ) is as follows, ( ) ( ) (8) where is bandwidth which is subtraction of starting frequency from ending frequency, and is sweep duration of LFM signal. To generate emitter signals, VSS blocks were used effectively. As shown in Fig. 1, LFM pulse radar signals were produced VSS blocks in this thesis. Figure 1. LFM emitter signal generator in VSS. 8

23 Fig. 2 shows two pulses of LFM radar and its important parameters which are generated in VSS. PRI, PW and bandwidth of LFM pulse radar signal can be seen in Fig. 2. Figure 2. Two LFM pulses generated in VSS. As shown in Fig. 2, an LFM emitter signal is generated with a 32μs PRI and 8μs PW can be seen in Fig. 2. In Fig. 2, is starting frequency, is ending frequency, T is PRI and is duration of the pulse. An example of LFM pulse generator is shown in Fig. 1 in VSS. There were several emitters built to simulate the receiver. Fig. 3 shows the spectrum of generated LFM pulse in Fig. 2. 9

24 Figure 3. Spectrum of LFM pulse in Fig. 2. According to Fig. 3, frequency spectrum of LFM pulse is obtained and this can be supported by the theory with taking Fourier Transform (FT) of time domain signal. Further information about FT can be found in [12]. Another example of an emitter is shown in Fig. 4. Some blocks are used for generation of radar pulses in VSS, and this simulator is very useful to generate emitter with its various parameters. Fig. 4 shows an example of emitter generation blocks which has a simple pulse radar. Figure 4. An emitter signal generator in VSS. 10

25 In Fig. 5, there is an emitter which has a 750MHz, 0.02μs pulsewidth(pw) and 0.2μs PRI. Furthermore, to generate a simple radar pulse, ( ) is represented as 0 in Equation 3. By this way simple pulse radar signal generated in VSS is shown in Fig. 5 Figure 5. Generated emitter signal in VSS. Fig. 6 shows that the spectrum of the generated emitter signal in Fig. 5 and the parameters which are carrier frequency, PW and PRI can be measured using this spectrum. The envelope of this signal is a sinc function and this theory can be supported by taking FT of time domain signal [3]. Figure 6. Spectrum of pulse in Fig

26 To support the receiver that is described in the next sections, many emitters were used with both simple pulse radar and LFM pulse radar. The receiver operational bandwidth was decided to cover GHz like very common commercial receivers. In order to generate emitter environment, there were several emitters generated with high sampling rate and it had to satisfy the Nyquist rate which causes a reduction in simulation speed. 2.2 Noise effect In order to simulate receiver, noise effect was assumed to the system. In the emitter generation part, noise was modeled with White Gaussian Noise. 30dB Signal to Noise Ratio (SNR) was assumed for emitter environment part. Receiver sensitivity is affected by either internal generated noise of the receiver or video detector characteristics. By keeping the RF gain high enough in front of the detector, only the receiver noise level changes the sensitivity. Noise of the resistors can be called as a noise generator that is in series. At the input of a receiver, thermal noise power can be as follows (9) Where is the power, is bandwidth of the receiver, is the temperature and is Boltzmann s constant ( ). Then the noise figure is as follows (10) where the receiver output noise is, the receiver RF gain is and is thermal input noise. For standardization of the equations, the room temperature is specified by the authorities [2]. The receiver gain is described as (11) where is the input and is the output power then combining Equation 10 and 11 12

27 are as follows (12) Thereafter the output signal to noise ratio always smaller than the input signal to noise ratio and the noise figure is greater than unity. Several devices can be connected cascaded to the system [2]. In order to calculate the NF of a channel in this thesis, which can be seen in Fig. 7, Equation 13 is as follows, (13) where, and, which are inverse of the filter losses, are first and second filters NFs. and are gains, which are inverse of losses, of the first and second filters. and are the first and second amplifiers NFs and is the gain of first amplifier. Finally, is the NF of mixer and its gain is. These NFs, gains and losses are expressed in power ratios. With the help of these equations, noise effect of the proposed receiver was applied in VSS. Budget analyze tool of the VSS was used to determine noise figure of the receiver. Fig. 7 shows the noise figure analyze of a channel of the receiver. Figure 7. Cascaded noise figure analyze of a receiver channel. 13

28 Cascaded NF analyze can be seen in Fig. 7. The gain, loss and NF of the blocks, which are filters, amplifiers and mixer, are stated in the Table 1 below. At the bottom of the Table 1, cascaded NF is listed as in order. Table 1. The gain, loss, NF and cascaded NF of a receiver channel. Filter 1 Amplifier 1 Fılter 2 Mixer Amplifier 2 Gain(dB) NF(dB) Cascaded NF(dB) When the Equation 13 is performed to a receiver channel shown in Fig. 7 and the parameters, which are given in Table 1, are applied to the equation, NF of the receiver is calculated as follows, (14) As shown in Fig. 7, Noise Figure at the output of the channel is nearly 4.5dB. Noise Figure is changed and tested in the next section. 14

29 CHAPTER 3 SIMULATION ON RECEIVER CONFIGURATIONS AND RECEIVER FRONT- END DESIGN Due to their selectivity and high sensitivity, superheterodyne receivers are the most commonly used receivers for communication. Most of the radar receivers are this type of receivers. To measure signal information properly, this type of receivers are mostly used in EW. On the other hand, parallel combinations of narrowband superheterodyne receivers generate a channelized wideband receiver. The most proper way to cower wide frequency band is to make a channelized receiver. In order to cover a 2-18GHz band with a receiver, dividing the whole band into 1GHz parallel bands with filters is an approach. This can be called a channelized approach; however, the receiver cannot be called as a channelized receiver. It can only be called a channelized front end. To make a channelized receiver, channels must have filters and conversions stages [2]. To collect emitter signals, which are produced in emitter environment part, a wideband channelized receiver is applied as proposed in [2]. This wideband channelized receiver design covers GHz. The most important part of the receiver is frequency channelization operations. In order to analyze and collect more than one signal, frequency channelization is used [2, 9]. Channelized wideband receiver mainly contains large number of filters for every channel. Emitter signals are separated from each other by receiver channels [2]. To analyze different emitter signals simultaneously, frequency channelization is necessary. The wideband channelized receiver block diagram is shown in Fig. 8. In Fig. 8, the system starts with an emitter environment part to generate emitter signals for simulation. In the first conversion stage, GHz frequency band is down or up converted to 2GHz subbands. First conversion stage has 11 channels and every channel has filters, a mixer, a local oscillator and amplifiers. However, in the third channel, which is 2-4GHz channel, there is no mixer and local oscillator, because it has already desired band. Therefore, N is the number of channel corresponds to 11 channels which can be seen in Fig. 8. After that, a switch is employed. The 15

30 operational band of the switch is 2-4GHz, and the duration of the every switched channel is given maximum PRI of the emitter environment part. The second conversion stage is employed after the switch. In this conversion part, 2-4GHz channels are down converted to 200MHz subbands. In the second conversion, there are 10 channels and M corresponds to channel number of the second conversion stage which can be seen in Fig. 8. Then a 16 bit ADC is employed to convert analog data to digital. At last, signal processing is employed to measure emitter parameters. According to implemented receiver as shown in Fig. 8, a sample emitter signal which has a 750MHz pulse is expected to receive with the first channel, which corresponds to 0.5-1GHz channel, and it is up converted to 2750MHz. After first conversion, this emitter signal is switched and second conversion begins. After that, the emitter signal, which is received and converted by the first conversion, is received by the fourth channel, which corresponds to GHz channel, and this signal is down converted to 0-200MHz channel. At the end of the second conversion, the emitter signal frequency is now 50MHz. Next, this signal is digitized and sent to signal processing part. Emitter Signals Emitter Environment LO. N 1 st Conversion N Switch LO M 2 nd Conversion A D C Parameter Measurement Figure 8. Complete system block diagram. 16

31 3.1 Frequency channelization The desired receiver band is set to GHz and it is decided that the whole band is firstly separated to 2GHz sub-bands [2]. According to proposal of [2], two receiver structures can be implemented to cover GHz. For the first proposed structure, the whole band is directly up or down converted to 2-4GHz channels. Then, the first channel is set to 0.5-2GHz, the second is set to 2-4GHz and the last channel is set to 16-18GHz. All input bands are converted to 2-4GHz bands for matching the input frequency. This structure has a very critical disadvantage. The channels adjacent to 2-4GHz channel are affected by spurious signals [2]. As shown in Fig. 9, some generated emitter signals can be seen between 1-5GHz bands. These emitter signals are some of the generated signals which are marked on the Fig. 9. Figure 9. Some generated emitter signals at 1-5GHz band. For instance, it was mentioned before, 0.5-2GHz channel is a problematic channel and when the first structure was implemented, it was expected that 1200MHz and 1500MHz emitter signals were up converted to 3200MHz and 3500MHz respectively. However, it was seen that many spurious signals were been formed, furthermore it can be seen that these spur signals powers are very close to expected 17

32 signals in Fig. 10. The 0.5-2GHz problematic channel output can be seen with its unwanted spur signals in Fig. 10. Figure GHz problematic channel belongs to first structure. Up converted actual emitter signals 3200MHz and 3500MHz are marked in Fig. 10, but it is seen that there are 3175MHz, 3225MHz, 3425MHz and 3525MHz unwanted signals in Fig. 10, which are generated by mixers, can be seen at the same time. Moreover, some of these signals are stronger than the actual signals. On the other hand, due to this structures spurious problem, another approach is implemented. For the second approach, instead of dividing the whole band to 2-4GHz channels, channelization process starts with 0.5-1GHz and goes with 1-2GHz and follows with 2-4GHz channel. After 2-4GHz channel, the receiver channels continue with 4-5GHz and follows with 5-6GHz. After the 5-6GHz channel, the channelization continues with 6-8GHz channel and the last one is 16-18GHz. To summarize this case, unlike the first structure the channels adjacent to 2-4GHz channel, which are 0.5-2GHz and 4-6GHz channels, are divided in to 0.5-1GHz, 1-2GHz, 4-5GHz and 5-6GHz channels with respectively [2]. According to [2], 0.5-1GHz and 4-5GHz bands should be converted to 2-3GHz subband GHz subband should be converted 2.5-3GHz channel and 4-5GHz subband should be 18

33 converted to 2-3GHz. For 1-2GHz and 5-6GHz subbands, they should be converted to 3-4GHz channels. Hereafter, channelization continues with 2GHz subbands to the end of 16-18GHz subband [2]. This means that the first conversion contains 11 channels. Fig. 11 shows the first and second channels in the second approach. The other channels have same types like in 1-2GHz channel but related blocks and its values can be different. Each channel of this approach operates as a narrowband superheterodyne receiver and their parallel combinations construct a wideband channelized receiver [3]. Figure 11. The first and second channels of the second approach. According to this approach, which is performed in this thesis, it is expected that 1200MHz and 1500MHz emitter signals are received by 1-2GHz channel. Moreover, as stated in [2], unlike the first structure there should be no unwanted spurious signals at this band which can be seen in Fig

34 Figure 12. VSS output of the second proposed structure for 1-2GHz channel. It can be easily seen that 1200MHz and 1500MHz emitter signals are converted to 3200MHz and 3500 MHz respectively in Fig. 12. Furthermore, there are not any spurious signals close to actual emitter signals or stronger than the actual ones. Before the second channelization operation, a dynamic switch was employed and this is discussed in next sections. After the first channelization, these subbands are again separated to 200MHz subbands. In order to reduce presence of more than one emitter signals at the same channel, second channelization is performed. Emitter parameter measurements could be easier by this way; because, less emitter falls in a same channel. Fig. 13 shows two channels of the second channelization stage. The other channels have same types but their filters and local oscillators (LO) values can be different. 20

35 Figure 13. Two channels of second conversion stage. In this stage, it operates like the first conversion stage, but its operational bands and channels bands are different. In Fig. 13, two channels from the second conversion can be seen, and the switched channels from the first conversion are separated by 200MHz channels. The channelization starts with GHz channels, continues with GHz channel and lasts with 3.8-4GHz channel. This means that the second conversion contains 10 channels. Therefore, to keep signal quality, design considerations were implemented to this stage such as, NF and SNR etc. Finally, tests showed that second stage was implemented successfully. After the second stage, it was seen that if emitter numbers are increased, there could be more than one emitter signal fall at the same channel. To avoid this problem, another solution was employed in the signal processing part. In the signal processing part, which is described in next sections, presented algorithm can separate signals. 21

36 3.2 ADC and Switch state In order to convert analog signal to digital one, 16 bit ADC is used in this study. One of the most important parameters of the receiver is dynamic range (DR). In this case, ADC selection is an important part too. For a digitized signal the resolution of a converter is limited by SNR. For this case, it is expected that DR of the ADC must be bigger than the DR of the receiver; however, if the DR of the ADC is too bigger than the receiver, DR will effect badly, and it is not desired. Receiver dynamic range can be calculated with Equation 15 which is given in [2], [ ( ) ( )] (15) Where IIP 3 is the third order intercept point of the receiver, NF is the Noise Figure of the receiver and BW is the receiver bandwidth. When the equation 15 is applied to the receiver configurations, which are 40dB, 4dB NF and 2GHz BW, DR is calculated as follows, (16) Under the light of these situations, 16 bit ADC is used in this system [13]. To calculate DR of an ADC is given in [2] as follows ( ) (17) where is the number of quantization level. Number of quantization level and number of bits is related to each other, such as 16 bit ADC has 16 quantization levels. According to 1 bit change in ADC causes 6dB change in DR. Therefore, it is important to adjust ADC not to affect DR of the system badly. SNR and DR of the ADC are directly proportional to each other. 16 bit ADC has a maximum SNR of 96.32dB. Therefore, it is suitable to use 16 bit ADC if the receiver has a dynamic range under 90dB. The ADC input signal sampling rate should satisfy the Nyquist criterion. The bandwidth of the ADC is 200MHz at the second conversion stage, so sampling rate must be greater than twice or more of the bandwidth. At the same time, 22

37 when the sampling rate of the ADC increases, the digitally processing speed decreases. Therefore, processing time can be effected badly [13]. For further information about ADC can be found in [13]. Figure 14. Dynamic time shared switch. To avoid loss of frequency information, a different time shared switch state had been used in this study. Generally, the switches are used with activity detection stages. For instance, activity detectors are positioned between at the end of the channels and inputs of the switch. Activity detectors detect all the channels if a signal is present, that channel is switched and all the other channels are delayed. In this activity detection, the switch input is activated by the leading edge of pulses detected with a threshold detector, by this way only active channel signal, which has pulse or pulses, passes to the second conversion stage and the other channels outputs are delayed till the trailing edge of the pulse is ended. This process continues with the same procedure for other channels [14]. For further information about activity detection and switch can be found in [14]. However, VSS starts to produce signals from the lowest frequency to highest frequency. In this case, this activity detection cannot be applicable. Because, the switch keeps open the channels with respectively. For example, if there are 500MHz, 1500MHz, 2500MHz and 5000MHz emitter signals, activity detector is firstly activated by 500MHz signal, then this signal passes through to first input of the switch. After that, the same procedure like for the first 23

38 500MHz signal, continues with 1500MHz for the second input, 2500MHz for the third input and 5000MHz for the fourth input of the switch, respectively. Therefore, this type of activity detector and switch are useless in this case. Instead of this type, dynamic switch was used to switch all channels in this thesis. For this situation, another way was followed. Firstly, to keep open switched channel, maximum PRI (T) of the emitter environment is used to determine switched channel duration. According to this situation, all channels are kept open with the same duration respectively, but channels are delayed with multiplication of channel number and maximum T. To keep channels in respectively, delay is used as can be seen in Fig. 14. The switching state stars with the first channel and goes second and then ends with N th channel respectively, and multiplication of PRI and the channel number gives delay time of each channel. N is the input number of the switch and this number must be same as with the channel number of the first conversion stage. Switched input channel numbers are stored with a look up table not to loose channel information. This channel information will be helped to find frequency information in next sections. 24

39 CHAPTER 4 EMITTER PARAMETER MEASUREMENTS PART In this part of the study, it is decided that emitter parameters such as PW, TOA, TOD and RF are measured which are parameters of pulsed radar and LFM pulsed radar emitters. In order to measure emitter parameters, a direct and efficient approach is performed as described in literature [5]. In early years, emitter parameter measurements were employed with circuits in the receiver. However, nowadays emitter parameter measurements are performed with software platforms. Fast speed computer based processor can help to measure emitter parameters efficiently. In this thesis, a simple and efficient algorithm is performed as given in [5]. Before implementing this approach, averaging filter is used to obtain envelope of the signal. After that, double threshold levels are performed to get the envelope of the signal. When the previous signal is lower than the upper threshold and present signal is higher than the upper threshold leading edge is detected by this way. If previous signal is upper then the lower threshold and present signal is lower than the lower threshold trailing edge is detected by this way. The leading edge and trailing edge locations give TOA and TOD, respectively [5]. According to [5], TOA and TOD locations are used to separate pulses in the same channel. In addition to this, increasing the range between two threshold levels can give better measurements, but the receiver sensitivity is affected badly by this way. To avoid this, 3dB difference is generally used [5]. In order to measure radio frequency of the emitter signals, FFT is performed as mentioned in [5]. Firstly, FFT is employed to the signal, after that maximum peak of the sampled FFT is found and another threshold level is used to determine the radio frequency of the emitter signals. If just one peak exists on the upper side of the threshold, maximum peak is measured as simple pulse radio frequency and if more than one peak exists on the upper side of the threshold level, the first and second 25

40 maximum peaks are used to determine LFM pulse radio frequency, which is described in this Chapter. 4.1 Pulse envelope In order to have constant amplitude (flat), pulse must be perfect. Because of temperature effect and non-linear characteristics of devices, the amplitude of the pulses is not flat. Frequency changes do not affect the pulse envelope and from pulse to pulse it has a specific issue. Further information about pulse envelope can be found in [15], [16], [17], [18] and [19]. In this study, pulse envelope y(n) is calculated by using averaging filter of the amplitude of A(n) of input pulse [15] ( ) ( ) (18) where the filter length is N. This filter is implemented in the signal processing part of this study. The reason of using this filter is to reduce the noise of the signal. In Fig. 12 an average filtered pulse can be seen. For the calculation of the pulsewidth, window based power calculation is done to designate %50 of the pulse [15]. On the pulse, ( ) in average power ( ) is as follows [15] ( ) ( ) (19) where the window initial sample is n and the window size is N. When the average power calculation of the pulse is done, start and stop points of the pulse can be calculated by double thresholding. 26

41 Figure 15. Captured pulse by the Receiver. When average power is obtained to pulse seen on Fig. 15, then the pulse envelope is formed like in Fig. 16. After this stage, parameters measurement of the emitter signals begins. 4.2 Double threshold In order to measure emitter parameters, double threshold noise gate is used in this study. In this study, as mentioned in section 2.2, signals can be affected by noise. In Matlab environment to detect the pulse, double threshold noise gate was applied in the signal processing part as introduced in [5]. The receiver may be triggered multiple times if the input signal is very close to the threshold level. In this case, receiver detects incorrect information. On the other hand, to avoid this problem double threshold is applied. According to this case, the signal must exceed the upper threshold level for triggering to obtain 27

42 data, and drop under the second threshold to state end of the pulse and stop achieving data [5]. Fig. 15 shows the double threshold on averaged power on pulse. The range is arbitrary chosen between two thresholds. If the range between thresholds is too large, receiver sensitivity can be affected and if the range is too short, data acquisition can be affected in emitter parameter measurements part. In general, the range between two thresholds is selected 3dB not to effect receiver sensitivity in a bad way [5]. Rise time and fall time locations can give important clues about the type of the radar. These rise and fall regimes can be generated intentionally or unintentionally on pulse shaping, but bandwidth of the pulse is limited by pulse shaping. To increase main lobe of the amplitude and to decrease side lobes pulse shaping can be applied [15]. On the rising edge, the rise time can be represented by the time difference between %10 and %90 points of average amplitude [16]. Furthermore, fall time has the same response but in trailing edge. The rise, fall time and threshold values can be seen on Fig

43 Figure 16. A radar pulse with various features. 29

44 4.3 Emitter parameters In this stage, pulse radar and LFM pulse radar parameters are measured which are captured and received by the receiver and measured in parameter measurement part. Describing the pulsed radars can be performed with carrier frequency, which depends on radar operation, PW, modulation and pulse repetition frequency (PRF) [2]. In this study, simple pulsed and LFM pulse waveform are used to generate emitter environment. Hence, radio frequency, PW and TOA parameters are measured in emitter parameter measurement part Time of arrival (TOA) and time of departure (TOD) In the proposed approach of [5], time reference of all pulses can be obtained by TOA. Some emitters generate pulses with staggered PRI, in other words PRI varies within specific periods. However, with stable PRI kind of emitters, practical parameter is TOA. In this thesis, in order to provide time reference for measuring received pulse parameters, TOA is used. Also, TOA is used to separate pulses if more than one pulse exists at the same channel. By measuring each sample s amplitude levels of the TOA and TOD with thresholds, TOA and TOD information indices can be found in Matlab. Positive edge detection occurs when the previous sample is lower than the upper threshold and the present signal is higher than the upper threshold level. TOA index is found by this way. Algorithm states this index as a TOA index. On the other hand, negative edge detection occurs when previous signal amplitude is higher than the lower threshold and the present is lower than the lower threshold level. This time the algorithm states that indices as a TOD indices [5]. These TOA and TOD indices are used to find number of pulses. Moreover, if there is more than one pulse, these pulses are found by using TOA and TOD indices. In addition to this, every TOA and TOD indices indicate one pulse and by this way signal separation for PW measurements of the emitters can be done which is described in section A flow chart starts from the IF signal, which is obtained at the end of the receiver, and lasts with TOA and TOD measurements for driven algorithm is presented in Fig. 30

45 17. According to this algorithm flow chart, IF signal is digitized with an ADC, after that envelope of the whole channel is obtained with averaging filter and double threshold approach is applied. After applying threshold levels, TOA and TOD indices are found which is described in this section. 31

46 Amplitude Time(s) IF Signal ADC Time(s) x Envelope Amplitude Time(s) x 10-5 Treshold 1 Treshold2 Amplitude x 10-5 Pulse Presence (Pulse Indices location and Number of Pulse Determination) TOA and TOD measurement for all pulses Figure 17. Flow chart for TOA and TOD indices measurement algorithm. 32

47 4.3.2 Pulse Width (PW) In order to measure PW of the emitter signals, a simple method is used in this thesis. A high pass filter was used to find PW in early years. Because when the pulse passes through a high pass filter, leading edge is turned into positive spike and trailing edge is turned into negative spike. A great accuracy was achieved for PW measurements by using a counter, because positive spike location is used to start count and the negative spike location is used to stop count. Today, complete shapes of the pulses can be achieved with fast ADCs, because PW can be sampled with a high rate [5]. Therefore, according to proposed approach in [5], calculated TOA and TOD indices are very helpful to indicate PW with simple Equation 20 given in [5] [ ] (20) where pulse width indices length is 18.. TOA and TOD indices can be seen in Fig. Figure 18. Pulse indices graph. 33

48 4.3.3 Radio frequency (RF) Radio frequency is one of the most important parameter for emitter signals. Sampled data frame is converted from time domain to frequency domain in order to measure emitter frequency. For this measurement Fast Fourier Transform (FFT) is performed in this thesis, which can be found in [12], to measure radio frequency of the emitters. In this study, RF is calculated by a simple equation which is given in literature [5]. According to [5], the location of the maximum FFT output sample ( ) is an approach to find frequency of the emitter signal. In order to use this approach for determining the emitter frequency, given data frame length ( ), local oscillator frequency ( ) and sampling frequency ( ) are used. Therefore the equation is as follows, (21) In this study, there are two kinds of emitter signals generated. These are simple pulse and LFM pulse signals. In order to measure simple pulse radar signal frequency, it is sufficient to use Equation 21. However, Equation 21 is not sufficient for LFM pulses. To avoid this, a simple threshold algorithm is used as an approach of this thesis like in Section 4.3. After FFT is applied to the pulse sample, a threshold is applied under the maximum peak of the FFT output sample. This threshold can help to determine if the signal is simple pulse or LFM pulse. According to this threshold, maximum peak of the FFT sample is found firstly and this threshold is located under 3dB of the maximum peak. After that, if one peak exists between maximum peak and threshold level, this peak is described as maximum peak location of the FFT sample, then this location ( ) is used in Equation 21 to measure emitter signal frequency. Furthermore, if there is more than one peak between the maximum peak of the FFT sample and threshold, the second maximum peak location is found. By this way, the range between these two maximum peak locations gives LFM signal frequency bandwidth. The algorithm flow chart can be seen in Fig

49 IF Signal ADC Pulse Separation FFT Pulse Presence (Pulse Indices location and Number of Pulse Determination from Section 4.4.1) Max. Peak Power Treshold Peak Detections and Decision Simple Pulse Frequency LFM Pulse Frequency Figure 19. Flow chart of simple pulse and LFM pulse frequency measurement algorithm. 35

50 CHAPTER 5 SIMULATION RESULTS RF front-end design and digital signal processing procedures were employed successfully on AWR-VSS environment and Matlab with stated proposals. Simulation was performed with several emitters. These emitters were used both pulse signal and LFM pulse signal. In the literature, most of the proposed approaches are concentrated on theoretical aspects of simulations for emitter parameter measurements. Furthermore, less importance is given on performing receiver and parameter measurement stages at the same study. They are mostly concentrated on receiver stage or parameter stages. Some of these studies can be found in literatures [1], [5], [20] and [21]. In the scope of this thesis, emitter generation is employed in emitter environment part to simulate the channelized receiver and parameter measurement parts. Emitter environment part is implemented in VSS with both simple pulse and LFM pulse radar signals. Secondly, to receive generated emitter signals from the emitter environment part, a wideband channelized intercept receiver is performed with first and second conversion stages. This receiver has a GHz operational bandwidth as can be found commercial ones in open market. After receiving stage, these received emitters signal parameters are measured in Matlab. For the wideband channelized receiver, a proposed structure is implemented as described in [2]. For the parameter measurement part, a proposed method is implemented as described in [5]. Finally, a Graphical User Interface (GUI) is designed to demonstrate measured emitter parameters. 36

51 5.1 Signal separation To measure desired emitter parameters, some algorithms, which are defined in the parameter measurement part of the study, were used in this study. For time domain analysis, same method, which was described in sections and 4.4.2, was employed because both pulsed radar and LFM pulse radar signals can be analyzed similarly in time domain. In order to measure the frequency of the pulses, FFT is used which is described in section At the beginning of this study, it is assumed that only one signal will fall on one channel in receiver, however; when number of emitters was increased to get test data, it was seen that there could be more than one signal falls on a channel. To avoid this problem, signal processing algorithm was improved to separate all emitter signals at one channel. In the processing part, different emitter signals separated firstly with an approach described in section 4.4.1, than the parameter measurement is employed as mentioned in section and By this way, emitter separation can be done efficiently. 37

52 Figure 20. Three pulses received with a channel. 38

53 In Fig. 20, there are three pulses received at the same channel. It is desired to separate these three different pulses. As seen on Fig 20, an LFM and basic pulsed emitter signals are received on the same channel of a receiver, and the written algorithm checks the envelope of the whole channels and then determines the number of the pulses, thereafter the algorithm starts to analyse pulse parameters which are described in section with flow chart in Fig. 17. Fig. 21 shows an emitter signal which was received and separated from the other signals which can be seen in Fig. 20. Figure 21. One of the separated pulses in three different pulses. In Fig. 20 there are 3 different pulses can be seen and these three different pulses are separated to measure their parameters. After separation is done by the approach which is described in section 4.4.1, parameter measurement part is performed as described in section Furthermore, for frequency measurement, the location of pulses indices, which are obtained from section 4.4.1, are used to determine FFT sample location as mentioned in section