Electronic Warfare Receivers Research Articles

Quantization error for weak RF simultaneous signal estimation

In a congested signal environment, it is difficult to obtain estimates of weak RF signal parameters. Determining signal parameter estimates in real time is a challenge for electronic warfare receivers that aim to receive multiple simultaneous signals. Prior work provided estimates of weak signal parameters (weak signal frequency and weak signal amplitude) without taking into account any error introduced by analog-to-digital converters that are inherently part of digital signal processing systems. In order to obtain realistic estimates, we need to take error introduced by an ADC into account. The primary aim of this paper is to quantify error introduced by a single ideal ADC as a function of angle. This paper presents a method to estimate angle resolution and quantization levels in N-bit analog-to-digital converters (ADCs) for use in a weak radiofrequency (RF) simultaneous signal estimation process. The paper quantifies the error in the angle quantization of an N-bit ADC for an input complex signal that is the instantaneous frequency obtained for the situation in which there are two simultaneous signals (with one strong signal and one weak signal) in a weak RF simultaneous signal estimation process. The presented method describes the process to determine the angle quantization range, angle quantization uncertainty, and angle quantization error. This approach has potential applications in electronic warfare (EW) systems. The approach also has potential for assessing ADC performance for measurements that approach the quantum limit. Results are presented for 1-bit, 2-bit, 3-bit, and 10-bit ADCs.

Simulation of Cognitive Electronic Warfare System With Sine and Square Waves

Today’s Electronic Warfare (EW) receivers need advanced technology to achieve real-time surveillance operations. Dynamic and intelligent systems are required for UAVs and other airborne applications. The airborne Electronic Warfare systems must be knowledge-based systems, learning from the threat scenario with highly integrated capabilities to detect, react, and adapt to radar threats in real-time. Artificial intelligence is a machine-dependent process, by adapting certain rules and logic supported by human intelligence, AI can be used for cognitive processing. Cognitive signal processing is required for making the system autonomous and dynamic in nature. Military action on radar signatures requires a set of commands to be executed dynamically with the help of the proposed EW system. It is proposed to design and develop a cognitive EW architecture and simulation of machine learning that combines neural network architecture with the help of sine and square waves as input. This paper presents the Cognitive signal processing for EW systems with Neural Network, Recurrent Neural Network (RNN), Machine learning (ML), and Deep learning (DL) techniques with their simulation with sine and square waves.

Photonic Measurement for Doppler Frequency Shift and Angle of Arrival Based on a Dual-Polarization Dual-Drive Mach–Zehnder Modulator

A novel photonic-assisted system for realizing the simultaneous measurement of Doppler frequency shift (DFS) and angle of arrival (AOA) is proposed. It is a simplified structure that is based on a dual-polarization dual-drive Mach–Zehnder modulator (DPol-DDMZM). The DFS direction can be accurately determined by comparing the phase relationship between the upper and lower low-frequency signal waveforms. An amplitude comparison function (ACF), which constructs a one-to-one mapping between the power ratio and the phase difference of echo microwave signals, can reduce the AOA measurement errors. The simulation results show that the simulated ACFs agree well with the theoretical ACFs, and the measurement errors of AOA are less than ±2.8° in a range of 0° to 78°. Moreover, the DFS can be realized by analyzing the spectrum of the low-frequency electrical signal with a measurement error of less than ±0.05 Hz. The system structure is compact and cost-effective, which provides an alternative solution for modern radar and electronic warfare receivers.

Pulse deinterleaving based on fusing PDWs and PRI extraction process for radar-assisted edge devices considering computational costs

Deinterleaving or radar pulse separation is a very important goal in terms of radar sources for identifying and implementing electronic warfare systems. In order to separate radar pulses, parameters measured by electronic warfare receivers such as electronic warfare support measures (ESM) and electronic signals intelligence (ELINT) are used in pulse separation. This paper presents a multi-parameter improved method for separating the pulse sequence of radar signals based on time of arrival (TOA) processing with sorting the other pulse descriptor words (PDW) parameters. In the proposed method, after extracting all the pulse repetition intervals (PRIs) based on TOA, the parameters of the angle of arrival, pulse width and carrier frequency (RF) are being used in pulse sorting to separate the received interleaved pulse sequences. The sequential difference histogram (SDIF) algorithm or cumulative difference histogram (CDIF) algorithm is used to extract all pulse repetition intervals. Also, in order to separate the sequence of the received pulses from all surroundings emitters, in addition to matching the potential PRI among the TOAs of the pulses and the similarity measurement in the other parameters of the pulse sequence (pulse sorting) have been used. This proposed algorithm is implemented in the integrated and complete design for deinterleaving of the radar pulses. The proposed method by considering low-cost computing sources considers a fast and low-complexity solution that can be used for edge-enabled distributed processors in aerial radar platforms as edge devices for military/combat unmanned aerial vehicles or networked missiles. The simulation results show that our method is completely effective.

Effect of Various Delay Line Ratios and Their Non-Linearity on the Performance of DIFM

The electronic warfare (EW) receiver’s frequency measurement precision is dependent on the accuracy of the delay line ratio and phase. A mathematical equation has been derived for accounting the effect of non –linearity due to inaccuracy in delay line ratio and phase. The effect of phase non-linearity (i.e., the combined effect of inaccuracy in delay line ratio and phase) on the output frequency is simulated using MATLAB. Analysis has been carried out for equal and unequal adjacent delay line ratios. Digital instantaneous frequency measurement (DIFM) receiver module has been realized for 9 GHz (1-10 GHz) bandwidth and is verified practically. Results are in good agreement with each other even in different environmental conditions.

A Photonic Approach for Doppler-Frequency-Shift and Angle-of-Arrival Measurement Without Direction Ambiguity

A dual channel system based on a dual-parallel Mach-Zehnder modulator (DPMZM) is proposed for simultaneous measurement of angle of arrival (AOA) and Doppler frequency shift (DFS). The echo signals are received by two antennas and sent into two sub modulators (sub-MZMs) of the DPMZM respectively. The transmitted signal is fed into one of the sub-MZMs to act as a local oscillator signal. The upper and the lower sidebands of the output signal from the DPMZM are separated by a wavelength-division multiplexer (WDM) to form two channels. By measuring the power of the beating signal of the two channels, the AOA can be measured and the phase measurement error is less than 3.4° in the range of about 300° (The AOA is measured from ±10° to ±90°). Moreover, the system can measure DFS with the measurement error less than 0.07 Hz and determine the DFS direction by comparing the phase relationship between the two channels. The system structure is simple and compact, which is a simple and effective solution for modern radar and electronic warfare receiver.

A novel algorithm for frequency de-hopping in radars using agile bandpass sampling for electonic support measurement

Modern radars use frequency hopping as an effective anti-jamming technique by changing their frequencies from pulse-to-pulse and thus making their blind estimation a challenging task for Electronic Warfare (EW) receivers. In this paper, a novel frequency de-hopping algorithm is proposed using agile band pass sampling by directly sampling the intercepted RF signal using three selected sampling frequencies. Under-sampling creates image frequencies around the radar carrier at integral multiples of the sampling frequencies. The proposed algorithm exploits this effect by searching for the unique/common frequency among three frequency image vectors using iterative mathematical modeling. It is shown that the proposed algorithm achieves comparably better estimation performance to the already existing single sampling chain heterodyne receivers at advantage of direct RF sampling using low speed ADCs. The achieved estimation performance is closer to CRLB. The effectiveness of frequency resolution and noise tolerance level, selection criteria of sampling frequencies, estimation time complexity of de-hopping and operational SNR range of the proposed algorithm are discussed to elaborate its strengths and limitations in EW applications.

Photonics for Ultrawideband RF Spectral Analysis in Electronic Warfare Applications

Electronic warfare receivers must satisfy particularly demanding requirements, and current electronic solutions must find a tradeoff between the request for high performance (in particular, very wide bandwidth, very high sensitivity, and very linear response) and the need for light and small systems. Photonics has been often proposed as a potential enabler of performance improvements, thanks to its wide tunability and precision, and recently the advancements of the photonic integration technologies are also promising strong reductions of size and weight. In this paper, we present an overview of the photonics-based solutions proposed so far in the field of electronic warfare. In particular, we focus on the specific implementation of a spectrum scanner we have recently proposed. Besides the performance in terms of bandwidth, linearity, and sensitivity, which are on par with the state-of-the-art electronic commercial systems, here, we report on our last advancements in terms of tuning speed. Further improvements are also discussed, in terms of both tuning speed and integrability.

Radar Antenna Scan Pattern Intelligent Recognition Using Visibility Graph

Radar antenna scan pattern (RASP) reconnaissance is a major problem in electronic warfare (EW). The RASP exerts a considerable influence on target identification, jamming decision making, and electronic support measures and thus plays a critical role in modern electronic warfare. A visibility graph (VG) is a tool for converting a time series into complex graphs with excellent noise immunity. This paper proposes a novel method for the intelligent recognition of the RASP based on the VG, including the circular, sector, helical, raster, conical, phased array, phased array azimuth and circular elevation scans. The changes in the signal amplitude received from the EW receiver are determined. Moreover, the related features are extracted from the VG and utilized to classify the RASPs. The comparison experiments performed with different classifiers, such as machine learning, neural network, and deep learning, confirm that the proposed method can improve the robustness of the recognition rate to the noise and recognition accuracy.

A Novel Radar Signals Sorting Method-Based Trajectory Features

When several foreign fighters with the same type enter detection range, the electronic warfare (EW) receivers will intercept many the same type radar emitter signals. If the intercepted pulse is processed by the traditional sorting methods, the number of emitters cannot be identified. The main reason is that the same type of radar has similar parameters. It will cause a devastating influence on subsequent strategic decisions. A novel sorting method based on the trajectory features is proposed to solve the aforementioned problems. First, the trajectory features of the intercepted pulse signal are extracted. Then, the segmentation method is utilized to preprocess the signals, which enhances the computing efficiency and improves the sorting accuracy. Meanwhile, a prediction framework based on long short-term memory (LSTM) recurrent neural network is established to forecast pulses. Finally, the radar stagger pulses are sorted by forecast pulses. The simulation results show that the proposed method can recognize the number of emitters and achieve high sorting accuracy. It provides a new idea for the radar signals sorting of the same type.

A new method for detecting jittered PRI in histogram-based methods

Histogram-based methods are among the best methods for deinterleaving, because of their easy implementation. However, they have a basic defect when they encounter a jittered pulse repetition interval (PRI). Jittered PRI is one of the most sophisticated patterns for electronic warfare (EW) receivers. In jittered PRI, the time among successive pulses varies in a totally random manner; thus its detection is very complicated. In this paper we present a new method for extracting jittered PRI from histogram-based methods. Simulation results demonstrate excellent performance of the proposed method in normal as well as hard circumstances where a higher missing pulse rate occurs or even when several targets with PRI of type jitter exist.

Automatic antenna scan type classification for next‐generation electronic warfare receivers

Cognitive electronic warfare (EW) is the key feature for next-generation EW systems. The deinterleaving and classification of received radar pulses and selection of the proper electronic attack technique are the common issues for non-preprogrammed cognitive jamming systems. Antenna scan type (AST) is a dominant parameter to discriminate and solve the ambiguities for the classification of the radar threats. In the literature, there are solutions for the classification of conical, helical, raster, and bidirectional scan types. In this study, spiral and electronic scan types are introduced in the AST analysis algorithm. Moreover, a new method based on correlation is proposed to determine the main beam signal. The proposed method gives better performance than amplitude thresholding-based algorithms for not only newly added but also other scan types. Also, main beam flatness ratio is proposed as a new feature to separate electronic scan types from the other scan types. Intensive simulations are executed to evaluate the performance of the proposed new method and feature. The classification of the conical, spiral, helical, circular, raster, and sector scan types at ~15 dB signal-to-noise ratio (SNR) is completed with 98% success. For electronic scan types, at least 94% classification accuracy is observed for SNR values above 20 dB.

Modeling and Simulation for the Investigation of Radar Responses to Electronic Attacks in Electronic Warfare Environments

An electronic warfare (EW) simulator is presented to investigate and evaluate the tracking performance of radar system under the electronic attack situations. The EW simulator has the input section in which the characteristic parameters of radar threat, radar warning receiver, jammer, electromagnetic wave propagation, and simulation scenario can be set up. During the process of simulation, the simulator displays the situations of simulation such as the received signal and its spectrum, radar scope, and angle tracking scope and also calculates the transient and root-mean-squared tracking errors of the range and angle tracking system of radar. Using the proposed EW simulator, we analyze the effect of concealment according to the noise and signal powers under the noise jamming and also analyze the effect of deception by calculating errors between the desired value and the estimated one under the deceptive jamming. Furthermore, the proposed EW simulator can be used to figure out the feature of radar threats based on the information collected from the EW receiver and also used to carry out the electronic attacks efficiently in electronic warfare.

Blind Compressive-Sensing-Based Electronic Warfare Receiver

A new compressive-sensing (CS)-based electronic warfare (EW) receiver is designed to estimate the angle-Doppler of adversary targets whose waveforms are unknown. The proposed EW receiver uses a sparse Bayesian learning (SBL) framework, which is blind in the sense that the knowledge of the sparsity basis is not available. Furthermore, a pruning mechanism is proposed to reduce the computational cost and improve convergence speed of the blind-SBL. The convergence of the proposed method is analytically proved.

Analysis of intra-pulse frequency-modulated, low probability of interception, radar signals

In this paper, we investigate the problem of analysis of low probability of interception (LPI) radar signals with intra-pulse frequency modulation (FM) under low signal-to-noise ratio conditions from the perspective of an airborne electronic warfare (EW) digital receiver. EW receivers are designed to intercept and analyse threat radar signals of different classes, received over large dynamic range and operating independently over large geographical spread to advice host aircraft to undertake specified actions. For an EW receiver, primary challenges in interception and analysis of LPI radar signals are low received power, intra-pulse modulations, multi-octave frequency range, wide signal bandwidth, long pulse width, vast and multi-parametric search space, etc. In the present work, a method based on match filterbank localization and Taylor’s series approximation for analysing the entire family of intra-pulse FM radar signals is proposed. The method involves progressive, joint time–frequency (TF) localization of the signal of interest (SOI), under piecewise linearity and continuity assumptions on instantaneous frequency, to effectively capture local TF signatures. Detection is by information-theoretic criterion based hypotheses testing, while estimation and classification are based on polynomial approximation. Fine signal analysis is followed by synthetic reconstruction of the received signal slope. Detection, estimation and classification performances for the prominent FM radar signal classes are quantified based on simulation study statistics. Stagewise implementation of analysis and FM slope reconstruction, in realistic radar threat scenarios, is demonstrated for the potential SOIs. Subject discussion is organized from the perspective of practical EW system design and presented within the realm of signal processing architecture of concurrent EW digital receivers.

Radar Signal Recovery using Compressive Sampling Matching Pursuit Algorithm

In this study, we propose compressive sampling matching pursuit (CoSaMP) algorithm for sub-Nyquist based electronic warfare (EW) receiver system. In compressed sensing (CS) theory time-frequency plane localisation and discretisation into a N×N grid in union of subspaces is established. The train of radar signals are sparse in time and frequency can be under sampled with almost no information loss. The CS theory may be applied to EW digital receivers to reduce sampling rate of analog to digital converter; to improve radar parameter resolution and increase input bandwidth. Simulated an efficient approach for radar signal recovery by CoSaMP algorithm by using a set of various sample and different sparsity level with various radar signals. This approach allows a scalable and flexible recovery process. The method has been satisfied with data in a wide frequency range up to 40 GHz. The simulation shows the feasibility of our method.

Impact of Trapping Effects on the Recovery Time of GaN Based Low Noise Amplifiers

This study investigates recovery time of the gain of AlGaN/GaN HEMT based low noise amplifiers (LNA) after an input overdrive pulse. Three LNAs, fabricated in two commercial MMIC processes and a Chalmers in-house process, are evaluated. The Chalmers process has an unintentionally doped buffer instead of the intentional Fe doping of the buffer which is standard in commercial GaN HEMT technologies. It is shown that the LNAs from the two commercial processes experience a severe drop in gain after input overdrive pulses higher than 28 dBm, recovering over a duration of around 20 ms. In contrast the LNA fabricated in-house at Chalmers experienced no visible effects up to an input power of 33 dBm. These results have impact for radar and electronic warfare receivers, which need to be operational immediately after an overdrive pulse. The long time constants suggest that these effects are due to trapping in the transistors with the Fe doped buffer playing an important role.

Discrete Electronic Warfare Signal Processing using Compressed Sensing Based on Random Modulator Pre-Integrator

Electronic warfare receiver works in the wide electromagnetic spectrum in dense radar signal environment. Current trends in radar systems are ultra wideband and low probability of intercept radar technology. Detection of signals from various radar stations is a concern. Performance and probability of intercept are mainly dependent on high speed ADC technology. The sampling and reconstruction functions have to be optimized to capture incoming signals at the receiver to extract characteristics of the radar signal. The compressive sampling of the input signal with orthonormal base vectors, projecting the basis in the union of subspaces and recovery through convex optimisation techniques is the current traditional approach. Modern trends in signal processing suggest the random modulator pre-integrator (RMPI), which sample the input signal at information rate non-adaptively and recovery by the processing of discrete and finite vectors. Analysis of RMPI theory, application to EW receiver, simulation and recovery of EW receiver signals are discussed.

Ultraweak simultaneous signal detection with theoretical phase calculation approaches

This paper presents applications of a generalized theoretical analysis of Tsui's phase measurement approach to detection of N - 1 ultraweak signals. A closed-form analytical expression is obtained for one application. A detection approach is presented for real-time estimation of the slope and curvature of sampled data of the instantaneous frequency. This approach provides the capability for early simultaneous signal detection and extraction of signal parameters. The capability for N = 4 simultaneous signals is desired for electronic warfare (EW) receivers.

Theoretical phase calculation approach for N simultaneous signals

This paper presents a generalized theoretical analysis of Tsui's phase measurement approach for the situation in which there are N simultaneous signals, where one of the signals is strong and N - 1 signals are weak. Signal amplitudes are normalized to the amplitude of the strongest signal. This approach provides the capability to extract values of the signal parameters. The capability for up to N = 4 simultaneous signals is desired in the design goal for electronic warfare receivers.