Digital Techniques for Wideband Receivers
This updated third edition of Digital Techniques for Wideband Receivers offers a current, comprehensive design guide for digital processing work with today's complex receiver systems. Brand new material brings readers up to date with the latest information on wideband electronic warfare receivers, the detection of FM and BPSK radar signals, analog-to-information, time-reversal filter, and an encoder example with multiple FFT length. The book offers insights on building digital electronic warfare receivers. From fundamental concepts and procedures to recent technology advances in digital receivers, readers get practical solutions to important wideband receiver problems.
Other keywords: sensitivity problems; angle-of-arrival measurements; wideband receiver; analog-information conversion; monobit receivers; detection problems; time reversal study; receiver testing; high-resolution spectrum estimation; electronic warfare receivers; frequency modulated signal detection; frequency downconverters; analog-digital converters; digital techniques; amplifiers; zero crossing; phase measurement; multiple fast Fourier transform receiver; frequency chanelization
- Book DOI: 10.1049/SBRA511E
- Chapter DOI: 10.1049/SBRA511E
- ISBN: 9781613532171
- e-ISBN: 9781613532188
- Format: PDF
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Front Matter
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1 Introduction
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This book discusses digital signal processing schemes that are potentially applicable to electronic warfare (EW) receivers. These receivers must have very wide instantaneous input bandwidth (about 1 GHz) to fulfill their operational requirements. This means any signal within the input bandwidth will be received all the time without tuning the receiver. In contrast, a communication receiver has a relatively narrow bandwidth. For example, television channels are allotted 6 MHz (although digital TV has become a reality in the United States, the channel bandwidth of a digital TV channel is the same as an analog TV channel), frequency modulated (FM) radio channels are allotted about 200 kHz, and amplitude modulation (AM) stations are allotted only 10 kHz [1]. If one turns on 10 television sets simultaneously and each one is receiving a different channel, the instantaneous bandwidth of such an arrangement is considered to be 60 MHz (ten 6-MHz channels).
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2 Requirements and Characteristics of Electronic Warfare Receivers
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The main purpose of this chapter is to introduce the concept of an EW receiver. In order to provide a broader view, the subject of EW will be briefly discussed. The signal environment and the requirements of the EW receiver will also be discussed. Since EW is basically a responsive action to a hostile electronic environment, the requirements will change with time. If the enemy creates a new threat, EW engineers and systems must respond in a timely manner. This chapter will first discuss the information contained in a radar pulse, analog and digital receivers and the characteristics of EW.
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3 Fourier Transform
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In this chapter the continuous Fourier transform and discrete Fourier transform (DFT) will be discussed. The concepts presented in this chapter serve as the foundation of wideband receiver processing techniques presented in this book. There are plenty of good books on this subject and a few of them are listed at the end of this chapter. Readers with a background in this area can skip this chapter.
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4 Fourier Transform-Related Operations
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In this chapter, the operations related to the Fourier transform are discussed. Some of these operations are useful to electronic warfare (EW) receiver design and some of these techniques can improve the results of the fast Fourier transform (FFT). The topics include periodograms, zero padding, better localization of FFT peaks, autocorrelation, a phase sampling scheme to increase the bandwidth of the receiver, and a decimation scheme of the discrete Fourier transform (DFT) for EW receivers.
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5 Analog-to-Digital Converters, Amplifiers, and Their Interface
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The main purpose of this chapter is to present an optimum way to match the radio frequency (RF) amplifier with the ADC. The word “optimum”means obtaining a certain sensitivity and dynamic range, desired by the designer, within the limits of the amplifier performance and the ADC. This chapter will very briefly discuss analog receiver performance and point out the difference between it and digital receiver performance. The ADC and its impact on the receiver performance will then be discussed. The important parameters of the ADC related to receiver performance are the number of bits, number of effective bits, maximum sampling frequency, and input bandwidth. The most significant effect of an ADC is on the dynamic range of the receiver, which is closely related to the sensitivity of the receiver since the sensitivity is the lower limit of the dynamic range of the receiver. There are several ways to consider the dynamic range, and each approach leads to a slightly different result. All these approaches will be discussed.
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6 Frequency Downconverters
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This chapter discusses both schemes of frequency conversion-one-channel and two-channel conversions. Both analog and digital frequency conversions are discussed. Several digital approaches to create the I and Q channels are also discussed. The impact of imbalance between the I and Q channels on receiver performance are presented. Finally, a correction scheme to rectify the I and Q channels imbalance is discussed. Plenty of imbalance compensation methods have been proposed for communication systems in which the signal frequency is known to the receiver and the working bandwidth of the communication receiver is usually narrower than that of the wideband receiver. For wideband receiver applications, signal frequency in unknown to the receiver. Both imbalance compensation techniques for narrowband and wideband systems are discussed in this chapter.
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7 Sensitivity and Detection Problems
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In this chapter, receiver sensitivity is discussed. The sensitivity of a receiver is defined as its ability to measure the weakest signal. The output of an analog-to-digital converter (ADC) is digital. This output impacts the measurement approach of input signals and thus receiver sensitivity. The conventional way to calculate sensitivity is through mathematical modeling. However, due to the nonlinear property ADCs, it is difficult to manipulate the calculations mathematically. As a result, the basic analysis is still based on an analog approach. If the ADC has a large number of bits, the result will be close to the analog approach. The threshold for detecting false alarms and signals in a digital receiver cannot be set arbitrarily in a continuous sense. The threshold can only be chosen from a finite number of levels. This chapter discusses different types of detection schemes. The difference between the detection schemes of analog and digital receivers is emphasized. The possible advantages of a digital receiver from a detection point of view are discussed. The detection based on one data sample is discussed first. The one-sample case is then extended to multiple samples. Finally, frequency domain detection, which can be applied to digital receivers, is examined. Examples with computer programs are used to illustrate some of the detection schemes. Before the general discussion, let us clarify the meaning of the word detection. This word has two distinct applications in a discussion of receivers. In the first sense, it refers to the process of converting a radio frequency (RF) signal or noise into a video signal. In the second sense, it refers to the process that determines whether a signal is present. In spite of this ambiguity, the meaning should be clear from the context.
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8 Phase Measurements and Zero Crossings
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In this chapter, a phase measurement method and a zero crossing method are discussed. These methods are relatively simple, but they can operate only under limited conditions. If the input contains only one sinusoidal wave, these methods can provide very accurate frequency measurement. Theoretically these methods can detect the existence of simultaneous signals. The phase measurement approach uses analog in-phase (I) and quadrature (Q) channels as the front end. If the I-Q channels are perfectly balanced, the phase measurement method can measure the frequencies of two input signals. The zero crossing method can measure the frequencies of multiple input signals. However, when multiple signals are present, the frequency accuracy measured by both these two methods will suffer compared with one input signal. Some of these methods need more investigation to determine their performances.
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9 Monobit Receiver
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In this chapter, the concept of the monobit receiver is introduced. This technique can be considered as a digital channelized approach. The fast Fourier transform (FFT) is very simple and can be built on one chip. A simple frequency encoder is used after the FFT outputs to determine the number of input signals and their frequencies. The design of a candidate encoder will be presented. The encoder and the FFT can be built on one chip. The chip has been fabricated and the monobit receiver concept has been validated successfully in the laboratory.
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10 Frequency Channelization and Afterwards Processing
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Channelization is one of the most important operations in building digital electronic warfare (EW) receivers. The equivalent analog operation is the filter bank. Therefore digital channelization can be considered a digital filter bank. It can also be considered as an N-port network with one input and N - 1 outputs. An input signal will appear at a certain output according to its frequency. By measuring the outputs from the filter bank, the frequency of the input signal can be determined. The only practical approach to building a wideband digital EW receiver with today's technology is through channelization. A common method of performing channelization is by employing the fast Fourier transform (FFT). To build a receiver using FFT, the length and the overlap of the FFT are very important parameters. These parameters are related to the minimum pulse width (PW) and the frequency resolution, which determines the sensitivity of the receiver. The frequency information can be obtained from the outputs of the digital filters. In order to obtain the input frequency, the filter outputs must be further processed. The main objectives of a receiver are to determine the number of input signals and their frequencies. The circuit used to accomplish these goals is referred to as the encoder. The encoding circuit is the most difficult subsystem to design in an EW receiver and most research effort is spent on the encoder design. This is true for both digital and analog receivers. The main problems are to avoid the generation of false alarms and the detection of weak signals. In an analog filter bank, the shape of the filter is difficult to control, and it is difficult to build filters with uniform performance, such as bandwidth and ripple factor, therefore the encoder must accommodate this problem. The shape of each individual filter in a digital filter bank can be better controlled. As a result, the encoder should be slightly easier to design because it does not need to compensate for the filter differences. Because of the complexity of the encoder, its design will not be discussed in detail. The design of a specific digital filter bank will also be presented. This specific example is used to illustrate the design procedure while avoiding the unnecessary mathematical complexity of a general design. In this example, the concepts of polyphase filters and multirate operation are introduced. In order to understand these concepts, decimation and interpolation are discussed first.
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11 High-Resolution Spectrum Estimation
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In this chapter, other spectrum estimation approaches are introduced that will be referred to as high-resolution spectrum estimations. Their major advantage is that they can provide higher frequency resolution than the FFT, especially on simultaneous signals. If there are two signals with frequencies very close, an FFT operation may generate one peak containing both signals. High-resolution spectrum estimation may separate the two signals by generating two sharp peaks. The major drawback of applying high-resolution spectrum estimation to digital microwave receivers is the complexity of the operation. Because of the large number of operations required to estimate the frequencies, this type of estimation will probably not be implemented for real-time application in the near future. However, it might be implemented for special applications. For example, if the peak of an FFT output appears to contain more than one signal, high-resolution spectrum estimation might be used to find the frequencies, thus the operation may not be required on all the input data.
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12 Digital Techniques for Wideband Receivers, 3rd Edition
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In this chapter the detection of biphase shift keying (BPSK) is discussed. In this type of signal, the phase shift is π. There are different phase shift keying (PSK) signals, such as π/2 and π/4, especially in communication signals. However, this study focuses on BPSK since it is more popular in radar applications. Many different codes can be used to generate a BPSK signal. For example, the Global Position System (GPS) signal is a BPSK signal modulated by a Gold code. The popular code used in radars is the Barker code, which has different lengths. Thirteen bits is the longest Barker code available, and this code will be used here.
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13 Detection of Frequency Modulated Signals
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Although there is no theoretical base, the frequency obtained from the amplitude and phase comparison methods derived for CW signals can improve the frequency accuracy on a chirp signal. These phenomena are shown through simulations.It is relatively difficult to detect a chirp signal without information on the chirp rate. It appears that the most efficient approach is to sum the maximum from every frame. The sensitivity obtained is about 3.4 dB worse than for a CW signal. The detection approaches through difference frequency produce lower sensitivity than the maximum summation method. However, once a signal is detected, the difference frequency will be within a certain range, and this can be considered as an additional requirement on the detection, decreasing the detection sensitivity.
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14 Concept of Analog-to-Information
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In this chapter the concept of analog-to-information (A-to-I) is introduced. The name A-to-I comes from the Analog-to-Information Receiver Development concept presented in a Defense Advanced Research Projects Agency (DARPA) program. The goal of A-to-I is to use a low sampling frequency to cover a wide input frequency band beyond the Nyquist sampling rate allowed [2-5]. In this chapter we present the analysis results of one of the A-to-I technology development concepts by Northrop Grumman. We would like to acknowledge its contribution and the support of the Air Force Research Laboratory (AFRL).
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15 Angle of Arrival Measurements
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The angle of arrival (AOA) is the most valuable piece of information that can be obtained from an enemy radar because the radar cannot change its position drastically in a very short time frame (i.e., a few milliseconds). Unfortunately AOA information is also the most difficult information to obtain. It requires several antennas with receivers. The two common approaches to measure AOA are based on amplitude and phase comparisons. Another approach is to use the Doppler frequency shift generated by the aircraft movement. However, this approach is closely related to the phase measurement system. If the requirement is to measure AOA on simultaneous signals, the problem becomes even more complicated because receivers with multiple signal capability are needed.
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16 Time Reversal Study
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In this chapter we will examine ways to determine the input signal of a receiver from the receiver's output signal using a time reversal filter. The input signal is usually measured by a receiver, which will distort the input signal. Assuming that receiving system is a linear system, then its output information represents the input signal modified by the receiving system's impulse response. To compensate for the impact of the receiving system on the input signal, the impulse response of the receiving system is used to design a time reversal filter. The time reversal filter can compensate for signal distortion caused by the receiving system, thus restoring the input signal. In most applications the input information is of interest, and by knowing the impulse function of the receiving system, the input signal can be obtained. The time reversal filter was first proposed for acoustics [1, 2] and is widely used in communications [3-6]. In this chapter we will demonstrate how the time reversal filter can expedite the calibration of an angle of arrival (AOA) system in which the information of the input signal is used to find the angle information on the signal. Since an impulse function is difficult to generate in a laboratory environment, chirp signals can be used as an alternative to determine the impulse response. Based on the impulse response, a time reversal filter can then be determined and used to find the input signal. The impact of the chirp signal on the performance of the resulting time reversal filter is investigated in this chapter. The concept of fractional time delay, which delays the time less than the sampling period, is also discussed. This concept is important for calibrating an AOA measurement system.
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17 Multiple Fast Fourier Transform Electronic Warfare Receiver
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The performance of a fast Fourier transform (FFT)-based electronic warfare (EW) receiver depends on the size of the FFT. An EW receiver using a long FFT size has a higher sensitivity and finer frequency resolution. However, its time domain resolution suffers, thus creating a less accurate estimate on the signal's time domain characteristics, such as time of arrival (TOA) and pulse width (PW). This is especially true for short signals. On the other hand, an EW receiver using a short FFT size can better determine the signal's PW and TOA but might miss long but weak signals and have coarse frequency resolution. One way to solve this issue is to create an EW receiver with multiple FFT sizes and determine signal characteristics based on the outcomes of the FFT with different frame sizes. However, it is not a trivial task to combine signal characteristic estimates generated with different FFT frame sizes and this chapter is dedicated to addressing this task. In this chapter an EW receiver encoder algorithm based on multiple FFT frame sizes is presented.
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18 Receiver Tests
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This paper discusses the performance of a digital receiver and the procedures for testing it. Receiver performance is one of the most important aspects in receiver research. One of the main impasses in receiver research is that there are no universally acceptable standards in the performance of electronic warfare (EW) receivers. Because of this shortcoming, researchers do not know where to improve EW receiver performance. If one claims to have made some improvements in receiver performance, but cannot report the result quantitatively, it is rather difficult to have these claims accepted. Worse yet, people can make claims about the performances of an EW receiver that cannot even be used in a system. For example, if a receiver misses many signals or produces a large number of spurious responses, in general it cannot be used in any system. Under this condition, no matter how good other performances are, the result should not be reported. There should be some minimum requirements a receiver must be measured against in order to qualify as a functioning receiver.
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Back Matter
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Supplementary material
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Supplementary Files for 'Digital Techniques for Wideband Receivers 3rd edition'.
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Supplementary Files for 'Digital Techniques for Wideband Receivers 3rd edition'.
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