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TitleELINT: The Interception and Analysis of Radar Signals (The Artech House Radar Library)
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Table of Contents
                            ELINT The Interception and Analysis of Radar Signals
	1 Electronic Intelligence
		1.1 Electronic Intelligence Defined
		1.2 The Importance of Intercepting and Analyzing Radar Signals
		1.3 Limitations Due to Noise
		1.4 Probability of Intercept Problems
		1.5 Direction Finding (DF) and Emitter Location
		1.6 Inferring Radar Capabilities from Observed Signal Parameters
		1.7 Receivers for Radar Interception
		1.8 Major ELINT Signal Parameters
		1.9 The Impact of LPI Radar on ELINT
	2 ELINT Implications of Range Equations and Radar Constraints
		2.1 Range Equations
		2.2 Radar Constraints
			2.2.1 Range Resolution Related to Bandwidth
			2.2.2 Spread Spectrum: Radar Versus Communications
			2.2.3 Moving Targets and Integration Time Constraints
			2.2.4 Constraints on Time-Bandwidth Product or Pulse Compression Ratio
			2.2.5 Constraints on Doppler Resolution
			2.2.6 Frequency Agility
			2.2.7 PRI Agility
			2.2.8 Power Constraints
			2.2.9 Pulse Compression Modulation Constraints
		2.3 Some ELINT Implications of Future Radar Designs
			2.3.1 Bistatic and Multistatic Radars
			2.3.2 Radar Trends
			2.3.3 Wideband Active Adaptive Array Radars
		2.4 Summary of Radar Design Constraints and Trends
		2.5 High-Power Microwave Weapons
	3 Characteristics of ELINT Interception Systems
		3.1 Intercept System Characteristics and Functions
		3.2 Frequency Coverage
		3.3 Analysis Bandwidth
			3.3.1 Wideband Radar Signal Trends
		3.4 Dynamic Range
			3.4.1 Dynamic Range Requirements
		3.5 Sensitivity
			3.5.1 Noise Figure Measurement
			3.5.2 Y-Factor Measurement
			3.5.3 Some Sensitivity Measures
			3.5.4 Output SNR and Receiver Applications
			3.5.5 Threshold Detection
			3.5.6 Sensitivity and the Received Pulse Density
		3.6 The Ultimate Limits to ELINT Parameter Measurements
		3.7 ECM and ELINT Receivers
		3.8 Crystal Video Receivers
			3.8.1 Crystal Video Applications
			3.8.2 Postdetection Signal Recording and Sorting
			3.8.3 CV System Design Considerations
		3.9 Superheterodyne Receivers
			3.9.1 Superhet Performance
			3.9.2 Sweeping Superhet Receivers
			3.9.3 Tuning Considerations
			3.9.4 Other Heterodyne Receivers
		3.10 Instantaneous Frequency Measurement Receivers
			3.10.1 Limiters Applied to IFMs
			3.10.2 The Simultaneous Signal Problem
			3.10.3 CW Signals and IFMs
			3.10.4 Digitizing the IFM Output
		3.11 Other Receivers
			3.11.1 Channelized Receivers
			3.11.2 Acousto-Optic (Bragg Cell) Receivers
			3.11.3 Microscan Receivers
		3.12 System Considerations
	4 Probability of Intercept
		4.1 Background
		4.2 Developments in the Theory Behind POI
			4.2.1 Intercept Description
			4.2.2 Implications of Today’s Environments/Operations on Intercept Time
			4.2.3 Mathematical Models
			4.2.4 Recent Developments on POI
		4.3 Summary
	5 Antennas and Direction Finders
		5.1 Omni-Directional Antennas
			5.1.1 Omni-Directional Antenna Applications
			5.1.2 Parameters for Omni-Directional Antennas
		5.2 Directional Intercept Antennas
		5.3 Direction Finding
		5.4 Instantaneous Direction Finding
			5.4.1 Amplitude Comparison AOA Measurement
			5.4.2 Phase Interferometers
			5.4.3 Bearing Discriminators
		5.5 Arrays, Lenses, and Subspace DF Methods
		5.6 Short Baseline TDOA for AOA
	6 Emitter Location
		6.1 Introduction
		6.2 Emitter Location Estimation
		6.3 Deriving the Location Covariance Matrix
		6.4 Angle of Arrival Location Analysis
		6.5 Time Difference of Arrival Location Analysis
		6.6 Time/Frequency Difference of Arrival Location Analysis
		6.7 Geometric Dilution of Precision
		6.8 Incorporation of Measurement Error
		6.9 Summary
	7 Estimating Power at the Transmitter
		7.1 Power Estimation Through ELINT
		7.2 Distance to the Horizon
		7.3 ERP Errors Due to Antenna Pointing Errors
		7.4 Estimating the Distance to the Radar
		7.5 Multiple Signal and Multipath Problems
		7.6 Summary of Power Measurement Requirements
		7.7 Sample ERP Calculations
	8 Antenna Parameters
		8.1 Polarization Defined
		8.2 Elliptical Polarization [1]
		8.3 Stokes’ Parameters [2]
		8.4 Measuring Polarization
			8.4.1 Polarization Pattern Method
			8.4.2 Phase-Amplitude Method
			8.4.3 Multiple Antenna Method
		8.5 Cross-Polarization
		8.6 Propagation Effects
		8.7 System Aspects of Polarization
		8.8 Antenna Beam Shape
		8.9 Basic Antenna Pattern Relationships
		8.10 Beam Patterns from ELINT
		8.11 Beam Patterns of Array Antennas
		8.12 Antenna Beam Summary
	9 LPI Radar and the Future of ELINT
		9.1 What Is LPI Radar?
		9.2 Radar and ELINT Detection of Signals
		9.3 Matched Filter Theory
		9.4 One Interception Strategy: Noncoherent Integration
		9.5 ESM and Radar Range Compared
		9.6 Some Pulse Compression Modulation Constraints
		9.7 Interception Techniques Using the Envelope of the Received Signal
		9.8 Narrowband Channels and Frequency Modulated Signals
		9.9 Predetection Processing Methods to Detect Linear FM and Other LPI Signals
		9.10 ELINT Receiver Requirements for Interception of Low Peak Power Signals
	10 Antenna Scan Analysis
		10.1 Introduction
		10.2 Some Principles of Searching
		10.3 Relationships Among Scan Rate, Maximum Unambiguous Range, and Energy on Target
		10.4 Fan Beam Scanning: Circular and Sector
		10.5 Pencil Beam Scanning: Raster, Helical, and Spiral
		10.6 Tracking Scans and Monopulse
		10.7 Electronic Scanning
		10.8 Scan Measurement and Analysis Techniques
		10.9 A Three-Dimensional Search Example
	11 Intrapulse Analysis
		11.1 Introduction
		11.2 Pulse Envelope Parameters
		11.3 Envelope Parameter Measurements
			11.3.1 Rise and Fall Times
		11.4 Some Radar Performance Limits Related to Pulse Envelope
		11.5 Multipath Effects
		11.6 Intrapulse Frequency and Phase Modulation
			11.6.1 Choosing the Receiver Bandwidth
		11.7 Intentionally Modulated Pulses
		11.8 Incidental Intrapulse Shape—Uses and Causes
		11.9 Comparing Wave Shapes
	12 Pulse Repetition Interval Analysis
		12.1 Introduction
		12.2 Common PRI Categories
			12.2.1 Constant PRI
			12.2.2 Jittered PRIs
			12.2.3 Dwell and Switch PRI
			12.2.4 PRI Stagger
			12.2.5 Sliding PRIs
			12.2.6 Scheduled PRIs
			12.2.7 Periodic PRI Variations
			12.2.8 Pulse Groups
		12.3 Time Interval Measurements
			12.3.1 SNR Limitations
			12.3.2 Limitations Due to Pulse Amplitude Changes
			12.3.3 Improving Interval Measurements
			12.3.4 Digital Thresholding
		12.4 PRI Analysis Techniques
			12.4.1 Raster Displays
			12.4.2 PRI Sounds
		12.5 PRI Analysis Theory and Practice
			12.5.1 Statistical Techniques
			12.5.2 Delta-T Histogram
		12.6 Interpreting the Results
			12.6.1 Delay Line PRI Generators
			12.6.2 Crystal Oscillators and Countdown Circuits
		12.7 PRI and Range Velocity Ambiguities
		12.8 MTI Radar Blind Speeds
		12.9 Moving Target Detection
	13 Deinterleaving Pulse Trains
		13.1 Pulse Sorting
		13.2 PRI-Based Gating
		13.3 Deinterleaving Algorithms
		13.4 Delta-T Histogram Applied to Deinterleaving
		13.5 The Pulse Train Spectrum
		13.6 Combining Pulse Bursts
		13.7 Raster Displays and Deinterleaving
		13.8 Measuring Deinterleaver Performance
	14 Measurement and Analysis of Carrier Frequency
		14.1 Pulsed Signal Carrier Frequency
			14.1.1 Frequency Measurement Accuracies
			14.1.2 Doppler Shifts
			14.1.3 Drift Measurement
			14.1.4 FM Ranging in Radar
		14.2 Intrapulse Frequency or Phase Modulation
			14.2.1 Analysis of Predetection Data
		14.3 Coherence (Short-Term RF Stability)
			14.3.1 RMS Phase Fluctuation
			14.3.2 RMS Frequency Fluctuations
			14.3.3 Signal Repeatability
			14.3.4 Effects of Variations in t0
			14.3.5 Frequency-Domain Stability Measures
			14.3.6 Bandwidth Limitations on Allan Variance Measurements
			14.3.7 Noise Limitations on Allan Variance Measurements
			14.3.8 Frequency Stability Measures for Power Law Spectra
			14.3.9 Sinusoidal FM and Linear Frequency Drift
			14.3.10 Short-Look Problem
		14.4 Frequency Character of CW Signals
		14.5 Pulsed Signal Example
		14.6 Measuring Coherence
		14.7 Effects of Drift
	15 Determining ELINT Parameter Limits
		15.1 Introduction
		15.2 Histograms Used to Determine Parameter Limits
		15.3 Types of Histograms
		15.4 Two-Sigma Parameter Limits
		15.5 Histogram Analysis Techniques
			15.5.1 Parameter Limits Example
			15.5.2 Intercepts Separated into Accuracy Classes
			15.5.3 Most Probable Values
		15.6 Analysis Problems
			15.6.1 Signal Identification Errors
			15.6.2 Transforming Parameters and Their Accuracies
		15.7 Histogram Analysis Summary
	16 ELINT Data Files
		16.1 Introduction
		16.2 Signal Identification
		16.3 ELINT Data for Radar Warning Receiver Design
		16.4 ELINT Data for Simulation and Training
		16.5 Adding Non-ELINT Data
		16.6 Summary
	Appendix A: Spectrum Widths: 3-dB and First Nulls for Trapezoidal Pulses
		A.1 Introduction
		A.2 Rectangular Pulses
		A.3 Trapezoidal Pulses: Equal Rise and Fall Times
		A.4 Trapezoidal Pulses: Unequal Rise and Fall Times
	Appendix B: Some ELINT Considerations of FM Signals
		B.1 Introduction
		B.2 Effects of Sinusoidal Interference on Phase- and Frequency- Demodulated Signals
		B.3 Signals with Sinusoidal Frequency Modulation
		B.4 Carson’s Rule
		B.5 Modification of Carson’s Rule for ELINT Applications
		B.6 FM Demodulation Degradation by RF Band Limiting
		B.7 Effects of Noise on FM Demodulated Signals
	Appendix C: A Frequency Hop Radar Example
		C.1 Probability That One or More Pulses Occur at the Desired Frequency
		C.2 Probability That Exactly One Pulse Occurs at the Desired Frequency
		C.2 Probability That Exactly One Pulse Occurs at the Desired Frequency
		C.3 Probability That Exactly k Pulses Occur at the Desired Frequency
		C.4 Probability That Several Pulses Occur at the Desired Frequency Less Than G Pulses Apart
		C.5 Probability Distribution of the Interval Between Two Pulses
		C.6 Determining an Optimum Receiver Sweep Rate
	Appendix D: History and Fundamentals of the IFM
		D.1 The Broadband Microwave Frequency Discriminator
	Appendix E: Emitter Location Partial Derivatives
	About the Author
	Recent Titles in the Artech House Radar Library
Document Text Contents
Page 2

The Interception and Analysis of Radar Signals

Page 234

9.7 Interception Techniques Using the Envelope of the Received Signal 219

One Rapid Sweep Superhet Receiver covered a 2-GHz band and swept that
band in 256 steps of 8 MHz in 20 ms. Its sampling rate was 50,000 samples per
channel per second. A similar channelized receiver with 256 channels each 8 MHz
wide could provide 16 million samples per channel per second. The bandwidth of
8 MHz was selected to be wide enough to pass the pulse compression modulations
then in use. (Many current threat radar systems use bandwidths of less than
10 MHz.) A common design is to test the sample against a threshold and declare
the presence of a pulse if one sample exceeds the threshold. To provide 90%
probability of detection and a 10- 6 probability of false alarm requires a SNR of
13.2 dB. The computation of the average of the envelope over a number of samples
and then comparing the average to a threshold allows the use of a much lower
threshold to achieve the same probability of detection and false alarm. The approxi-
mate improvement in sensitivity is found from (9.4). If the waveform dwells at one
carrier frequency for 2.5 ms and the bandwidth of the channels is 8 MHz, then
BT = 20,000 and the sensitivity improvement is approximately 27 dB for the
channelized receiver. The swept receiver provides a sample every 20 ms or 125
samples in 2.5 ms. Equation (9.4) gives the improvement in sensitivity as approxi-
mately 15.5 dB for the swept receiver. There is an added benefit of the swept
receiver in eliminating interference from the pulses from ordinary radar signals.
Sampling the signal for 80 ns every 20 ms means that most pulsed signals will not
contribute much to the average over 2.5 ms. The probability of coincidence between
the sampling gate of the sweeping receiver and the pulsing of the interfering radar
is very low. Of course, this could also be seen as a drawback if one is interested
in detecting both pulsed signals and modulated CW signals.

Another way of processing the samples of the envelope is to test each sample
against a threshold and then require that a certain minimum number of samples
cross the threshold out of a given number of samples tested—often called M of N
detection or binary integration [2, 6]. Here M samples out of N must cross the
threshold (N ³ M). This process is not quite as effective as computing the average
of the samples. It has the effect of suppressing very strong signals of short duration—
which is sometimes an advantage. The computation requires use of the binary
probability distribution. The first step is to determine the probability of noise alone
crossing the threshold at least M times out of N for a given probability that a single
sample of noise crosses the threshold. The notation Pfa,1 denotes the probability that
one sample of noise alone crosses the threshold, and Pfa,N is the probability that
at least M of N samples of noise alone cross the threshold. These are related by
the binary probability distribution for N trials and for Pfa,11 the probability of
‘‘success’’ on one trial. Likewise, the probability that signal plus noise crossed the
threshold on one trial is Pd,1 and the probability that signal plus noise crosses
the threshold at least M times out of N tries is Pd,N . These are also related by the
binary probability distribution. Some examples of the results are given in Table
9.1. There is an optimum value of M for any specific case. Values of M near N/2
or 1.5N0.5 have been suggested in the literature [6, 7]. The latter is used in Table
9.1. The required SNR has a broad minimum [6], and so choosing the exact
optimum value of M is not critical.

Although there is no theoretical limit to the improvement as the value of N
increases, there are important practical considerations; namely, as the threshold

Page 235

220 LPI Radar and the Future of ELINT

Table 9.1 Examples of Integration Gain Using M of N Integration

N = 8, M = 4 N = 16, M = 6 N = 32, M = 8 N = 64, M = 12
SNR = 7.3 dB SNR = 5.4 dB SNR = 3.4 dB SNR = 1.7 dB
Gain = 5.9 dB Gain = 7.8 dB Gain = 9.8 dB Gain = 11.5 dB
M is selected as 1.5N0.5; gain compared to Pd,1 = 0.9, Pfa,1 = 10

- 6 (single pulse SNR =
13.2 dB). N determined by signal duration during its coherent processing interval for Pfa,N
= 10- 6, Pd,N = 0.9.

decreases, the value of Pfa,1 becomes larger and so does the value of Pd,1. Eventually
the threshold is so low that there is not much difference between these two values.
Then a slight change in the noise level could drastically affect the final values of
Pd,N and Pfa,N . This is illustrated in Figure 9.5, which shows the probability of
both false alarm and detection at - 1.5-dB SNR. If the threshold is selected at 2.65
normalized units, then Pd,1 = 0.12 and Pfa,1 = 0.03. With a relatively small difference
between probability of detection and false alarm, a small change in the noise level
could cause a drastic change in the performance of the system. After the M of N
process (for M = 24, N = 256), the probability of detection and false alarm at SNR
= - 1.5 dB is shown in Figure 9.6. Now the probability of detection at the threshold
of 2.65 is 90% and the probability of false alarm is 10- 6. Detection using a single
sample would require the SNR to be 13.2 dB to give this same performance;
therefore, the M = 24, N = 256 process provides 13.2 - (- 1.5) = 14.7 dB of
processing gain. Coherent processing of 256 samples provides 24.1 dB of processing
gain; hence the loss of the M of N process is 9.6 dB relative to coherent integration.
The approximate gain expected from a noncoherent process as given by (9.2) is

Figure 9.5 Probability of detection (solid) and false alarm (dotted). SNR = - 1.5 dB. Threshold set
at 2.65 yields Pfa,1 = 0.03 and Pd,1 = 0.12.

Page 468

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