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Advanced Anti-Jamming Methods and Signal Processing Techniques for Radar System

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A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Communications".

Deadline for manuscript submissions: closed (20 February 2024) | Viewed by 22135

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Special Issue Editors

Dr. Jingwei Xu

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National Lab of Radar Signal Processing, School of Electronic Engineering, Xidian University, Xi’an 710071, China
Interests: radar system modeling; multi-sensor array signal processing; space–time adaptive processing; radar waveform diversity
Special Issues, Collections and Topics in MDPI journals

Dr. Yimin Liu

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Guest Editor

Department of Electronic Engineering, Tsinghua University, Beijing 100084, China
Interests: radar theory; statistic signal processing; compressive sensing and their applications in radar; spectrum sensing; intelligent transportation systems

Dr. Lan Lan

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Guest Editor

National Lab of Radar Signal Processing, School of Electronic Engineering, Xidian University, Xi’an 710071, China
Interests: frequency diverse array radar systems; MIMO radar signal processing; target detection and estimation; ECCM
Special Issues, Collections and Topics in MDPI journals

Dr. Yan Huang

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Guest Editor

State Key Laboratory of Millimeter Waves, School of Information Science and Engineering, Southeast University, Nanjing 210096, China
Interests: millimeter wave radar system design and signal processing; driverless communication and sensing; intelligent anti-jamming technology; multi-source data processing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

With advancements in electronic systems and signal processing theory, the field of modern radars and electronic jammers has become increasingly competitive. Jamming signals can be modulated in multiple dimensions in a space–time coupled manner for defense and civil applications. Modern radars are developed for performance enhancement within dense electromagnetic jamming environments, implementing new strategies for this purpose, including waveform diversity and/or agility, sophisticated design of signal recovery, knowledge-based adaptive processing, advanced learning-based processing frameworks, and so on. This Special Issue concerns anti-jamming challenges in the radar community. Possible strategies include, but are not limited to: waveform optimization, advanced coding design, frequency/time/coding diversity, and waveform agility, etc. Signal processing methods are of particular interest, including multi-array signal processing, multi-dimensional signal processing, multiple–input multiple–output techniques, frequency diverse array processing, agility radar coherent processing, sparse recovery and compressive sensing, knowledge-aided adaptive processing, and machine-learning-based processing. System design and signal processing methods must be considered simultaneously to solve increasingly urgent problems and meet new application demands.

Dr. Jingwei Xu
Dr. Yimin Liu
Dr. Lan Lan
Dr. Yan Huang
Guest Editors

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Published Papers (12 papers)

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Research

16 pages, 4149 KiB

Open AccessArticle

AK-MADDPG-Based Antijamming Strategy Design Method for Frequency Agile Radar

by Zhidong Zhu, Xiaoying Deng, Jian Dong, Cheng Feng and Xiongjun Fu

Sensors 2024, 24(11), 3445; https://doi.org/10.3390/s24113445 - 27 May 2024

Viewed by 698

Abstract

Frequency agility refers to the rapid variation of the carrier frequency of adjacent pulses, which is an effective radar active antijamming method against frequency spot jamming. Variation patterns of traditional pseudo-random frequency hopping methods are susceptible to analysis and decryption, rendering them ineffective against increasingly sophisticated jamming strategies. Although existing reinforcement learning-based methods can adaptively optimize frequency hopping strategies, they are limited in adapting to the diversity and dynamics of jamming strategies, resulting in poor performance in the face of complex unknown jamming strategies. This paper proposes an AK-MADDPG (Adaptive K-th order history-based Multi-Agent Deep Deterministic Policy Gradient) method for designing frequency hopping strategies in frequency agile radar. Signal pulses within a coherent processing interval are treated as agents, learning to optimize their hopping strategies in the case of unknown jamming strategies. Agents dynamically adjust their carrier frequencies to evade jamming and collaborate with others to enhance antijamming efficacy. This approach exploits cooperative relationships among the pulses, providing additional information for optimized frequency hopping strategies. In addition, an adaptive K-th order history method has been introduced into the algorithm to capture long-term dependencies in sequential data. Simulation results demonstrate the superior performance of the proposed method. Full article

(This article belongs to the Special Issue Advanced Anti-Jamming Methods and Signal Processing Techniques for Radar System)

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17 pages, 7041 KiB

Open AccessCommunication

SMSP Mainlobe Jamming Suppression with FDA-MIMO Radar Based on FastICA Algorithm

by Pengfei Wan, Guisheng Liao, Jingwei Xu and Xiaolong Fu

Sensors 2023, 23(12), 5619; https://doi.org/10.3390/s23125619 - 15 Jun 2023

Cited by 4 | Viewed by 1183

Abstract

In the electronic warfare environment, the performance of ground-based radar target search is seriously degraded due to the existence of smeared spectrum (SMSP) jamming. SMSP jamming is generated by the self-defense jammer on the platform, playing an important role in electronic warfare, making traditional radars based on linear frequency modulation (LFM) waveforms face great challenges in searching for targets. To solve this problem, an SMSP mainlobe jamming suppression method based on a frequency diverse array (FDA) multiple-input multiple-output (MIMO) radar is proposed. The proposed method first uses the maximum entropy algorithm to estimate the target angle and eliminate the interference signals from the sidelobe. Then, the range-angle dependence of the FDA-MIMO radar signal is utilized, and the blind source separation (BSS) algorithm is used to separate the mainlobe interference signal and the target signal, avoiding the impact of mainlobe interference on target search. The simulation verifies that the target echo signal can be effectively separated, the similarity coefficient can reach more than 90% and the detection probability of the radar is significantly enhanced at a low signal-to-noise ratio. Full article

(This article belongs to the Special Issue Advanced Anti-Jamming Methods and Signal Processing Techniques for Radar System)

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16 pages, 549 KiB

Open AccessArticle

Hybrid FSK–FDM Scheme for Data Rate Enhancement in Dual-Function Radar and Communication

by Muhammad Fahad Munir, Abdul Basit, Wasim Khan, Athar Waseem, Muhammad Mohsin Khan, Ahmed Saleem, Salman A. AlQahtani, Amil Daraz and Pranavkumar Pathak

Sensors 2023, 23(12), 5440; https://doi.org/10.3390/s23125440 - 8 Jun 2023

Cited by 2 | Viewed by 1666

Abstract

In this paper, we present a hybrid frequency shift keying and frequency division multiplexing (i.e., FSK–FDM) approach for information embedding in dual-function radar and communication (DFRC) design to achieve an improved communication data rate. Since most of the existing works focus on merely two-bit transmission in each pulse repetition interval (PRI) using different amplitude modulation (AM)- and phased modulation (PM)-based techniques, this paper proposes a new technique that doubles the data rate by using a hybrid FSK–FDM technique. Note that the AM-based techniques are used when the communication receiver resides in the side lobe region of the radar. In contrast, the PM-based techniques perform better if the communication receiver is in the main lobe region. However, the proposed design facilitates the delivery of information bits to the communication receivers with an improved bit rate (BR) and bit error rate (BER) regardless of their locations in the radar’s main lobe or side lobe regions. That is, the proposed scheme enables information encoding according to the transmitted waveforms and frequencies using FSK modulation. Next, the modulated symbols are added together to achieve a double data rate using the FDM technique. Finally, each transmitted composite symbol contains multiple FSK-modulated symbols, resulting in an increased data rate for the communication receiver. Numerous simulation results are presented to validate the effectiveness of the proposed technique. Full article

(This article belongs to the Special Issue Advanced Anti-Jamming Methods and Signal Processing Techniques for Radar System)

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18 pages, 20764 KiB

Open AccessArticle

Transmit–Receive Sparse Synthesis of Linear Frequency Diverse Array in Range-Angle Space Using Genetic Algorithm

by Yanhong Xu, Xiao Huang and Anyi Wang

Sensors 2023, 23(6), 3107; https://doi.org/10.3390/s23063107 - 14 Mar 2023

Cited by 2 | Viewed by 1573

Abstract

Unlike conventional phased array (PA), frequency diversity array (FDA) can perform the beampattern synthesis not only in an angle dimension but also in a range dimension by introducing an additional frequency offset (FO) across the array aperture, thus greatly enhancing the beamforming flexibility of an array antenna. Nevertheless, an FDA with uniform inter-element spacing that consists of a huge number of elements is required when a high resolution is needed, which results in a high cost. To substantially reduce the cost while almost maintaining the antenna resolution, it is important to conduct a sparse synthesis of FDA. Under these circumstances, this paper investigated the transmit–receive beamforming of a sparse-fda in range and angle dimensions. In particular, the joint transmit–receive signal formula was first derived and analyzed to resolve the inherent time-varying characteristics of FDA based on a cost-effective signal processing diagram. In the sequel, the GA-based low sidelobe level (SLL) transmit–receive beamforming of the sparse-fda was proposed to generate a focused main lobe in a range-angle space, where the array element positions were incorporated into the optimization problem. Numerical results showed that 50% of the elements can be saved for the two linear FDAs with sinusoidally and logarithmically varying frequency offsets, respectively termed as sin-FO linear-FDA and log-FO linear-FDA, with only a less than 1 dB increment in SLL. The resultant SLLs are below −9.6 dB, and −12.9 dB for these two linear FDAs, respectively. Full article

(This article belongs to the Special Issue Advanced Anti-Jamming Methods and Signal Processing Techniques for Radar System)

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20 pages, 3804 KiB

Open AccessArticle

Low-Altitude Windshear Estimation Method Based on Four-Dimensional Frequency Domain Compensation for Fuselage Frustum Conformal Array

by Hai Li, Lei Zheng and Fanwang Meng

Sensors 2023, 23(1), 371; https://doi.org/10.3390/s23010371 - 29 Dec 2022

Viewed by 1579

Abstract

In this paper, a low-altitude wind speed estimation method based on the fuselage frustum conformal array system is proposed. Firstly, based on the signal model of the fuselage conformal array radar, the four-dimensional joint phase compensation of the echo data in the Doppler domain and three-dimensional space-frequency domain is performed by using the four-dimensional frequency domain compensation method. Secondly, the clutter covariance matrix is estimated by the compensated echo data, and a space-time Adaptive Processing (STAP) processor suitable for low-altitude windshear target is constructed to suppress clutter. Finally, the maximum Doppler value of each distance cell is extracted, and the wind velocity is estimated. Simulation results show that the proposed method can effectively suppress clutter and accurately estimate wind speed. Full article

(This article belongs to the Special Issue Advanced Anti-Jamming Methods and Signal Processing Techniques for Radar System)

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17 pages, 2269 KiB

Open AccessArticle

Low-Altitude Windshear Wind Speed Estimation Method Based on KASPICE-STAP

by Hai Li, Yutong Chen, Kaihong Feng and Ming Jin

Sensors 2023, 23(1), 54; https://doi.org/10.3390/s23010054 - 21 Dec 2022

Cited by 1 | Viewed by 1906

Abstract

Aiming at the problem of low-altitude windshear wind speed estimation for airborne weather radar without independent identically distributed (IID) training samples, this paper proposes a low-altitude windshear wind speed estimation method based on knowledge-aided sparse iterative covariance-based estimation STAP (KASPICE-STAP). Firstly, a clutter dictionary composed of clutter space–time steering vectors is constructed using prior knowledge of the distribution position of ground clutter echo signals in the space–time spectrum. Secondly, the SPICE algorithm is used to obtain the clutter covariance matrix iteratively. Finally, the STAP processor is designed to eliminate the ground clutter echo signal, and the wind speed is estimated after eliminating the ground clutter echo signal. The simulation results show that the proposed method can accurately realize a low-altitude windshear wind speed estimation without IID training samples. Full article

(This article belongs to the Special Issue Advanced Anti-Jamming Methods and Signal Processing Techniques for Radar System)

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16 pages, 25263 KiB

Open AccessArticle

A Novel Method for Interferometric Phase Estimation in Dual-Channel Cancellation

by Long Huang, Aifang Liu, Zuzhen Huang, Hui Xu and Dong Han

Sensors 2022, 22(23), 9356; https://doi.org/10.3390/s22239356 - 1 Dec 2022

Viewed by 1464

Abstract

Multichannel SAR systems have grown rapidly over the past decade due to their powerful high-resolution and wide-swath (HRWS) capabilities. Because spatially separated channels also have the potential to suppress jamming, dual-channel cancellation is a general method that is effective regardless of the type of jamming signal. In this paper, the principle of dual-channel cancellation (DCC) is introduced, and several practical problems using DCC are also discussed. Moreover, this paper emphasizes interferometric phase estimation, which is the key to DCC. If the jamming-to-signal ratio (JSR) is high, the interferometric phase can be estimated accurately from the interferometry of two channel signals, but estimation becomes rather difficult when the JSR decreases. To solve the problem of interferometric phase estimation under a low JSR, a novel interferometric phase estimation method using cosine similarity is proposed in this paper. L-band airborne dual-channel SAR is performed to investigate the applicability of the method. The results not only prove that cosine similarity is an effective method for interferometric phase estimation, but also demonstrate the potential of DCC in the SAR anti-jamming processing. Full article

(This article belongs to the Special Issue Advanced Anti-Jamming Methods and Signal Processing Techniques for Radar System)

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25 pages, 5125 KiB

Open AccessArticle

Airborne Radar Anti-Jamming Waveform Design Based on Deep Reinforcement Learning

by Zexin Zheng, Wei Li and Kun Zou

Sensors 2022, 22(22), 8689; https://doi.org/10.3390/s22228689 - 10 Nov 2022

Cited by 14 | Viewed by 2387

Abstract

Airborne radars are susceptible to a large number of clutter, noise and variable jamming signals in the real environment, especially when faced with active main lobe jamming, as the waveform shortcut technology in the traditional regime can no longer meet the actual battlefield radar anti-jamming requirements. Therefore, it is necessary to study anti-main-lobe jamming techniques for airborne radars in complex environments to improve their battlefield survivability. In this paper, we propose an airborne radar waveform design method based on a deep reinforcement learning (DRL) algorithm under clutter and jamming conditions, after previous research on reinforcement-learning (RL)-based airborne radar anti-jamming waveform design methods that have improved the anti-jamming performance of airborne radars. The method uses a Markov decision process (MDP) to describe the complex operating environment of airborne radars, calculates the value of the radar anti-jamming waveform strategy under various jamming states using deep neural networks and designs the optimal anti-jamming waveform strategy for airborne radars based on the duelling double deep Q network (D3QN) algorithm. In addition, the method uses an iterative transformation method (ITM) to generate the time domain signals of the optimal waveform strategy. Simulation results show that the airborne radar waveform designed based on the deep reinforcement learning algorithm proposed in this paper improves the signal-to-jamming plus noise ratio (SJNR) by 2.08 dB and 3.03 dB, and target detection probability by 26.79% and 44.25%, respectively, compared with the waveform designed based on the reinforcement learning algorithm and the conventional linear frequency modulation (LFM) signal at a radar transmit power of 5 W. The airborne radar waveform design method proposed in this paper helps airborne radars to enhance anti-jamming performance in complex environments while further improving target detection performance. Full article

(This article belongs to the Special Issue Advanced Anti-Jamming Methods and Signal Processing Techniques for Radar System)

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12 pages, 3331 KiB

Open AccessArticle

Multiple Mainlobe Interferences Suppression Based on Eigen-Subspace and Eigen-Oblique Projection

by Yunhao Ji, Yaobing Lu, Shan Wei and Zigeng Li

Sensors 2022, 22(21), 8494; https://doi.org/10.3390/s22218494 - 4 Nov 2022

Cited by 2 | Viewed by 1653

Abstract

When the desired signal and multiple mainlobe interferences coexist in the received data, the performance of the current mainlobe interference suppression algorithms is severely challenged. This paper proposes a multiple mainlobe interference suppression method based on eigen-subspace and eigen-oblique projection to solve this problem. First, use the spatial spectrum algorithm to calculate interference power and direction. Next, reconstruct the eigen-subspace to accurately calculate the interference eigenvector, then generate the eigen-oblique projection matrix to suppress mainlobe interference and output the desired signal without distortion. Finally, the adaptive weight vector is calculated to suppress sidelobe interference. Through the above steps, the proposed method solves the problem that the mainlobe interference eigenvector is difficult to select, caused by the desired signal and the mismatch of the mainlobe interference steering vector and its eigenvector. The simulation result proves that our method could suppress interference more successfully than the former methods. Full article

(This article belongs to the Special Issue Advanced Anti-Jamming Methods and Signal Processing Techniques for Radar System)

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14 pages, 2855 KiB

Open AccessArticle

Cooperative Anti-Deception Jamming in a Distributed Multiple-Radar System under Registration Errors

by Shanshan Zhao, Minju Yi and Ziwei Liu

Sensors 2022, 22(19), 7216; https://doi.org/10.3390/s22197216 - 23 Sep 2022

Cited by 3 | Viewed by 1902

Abstract

A distributed multiple-radar system has natural advantages in anti-deception jamming. However, most of the anti-jamming methods are proposed in full spatial registration. In practice, the registration error is difficult to eliminate, which will seriously degrade the performance of cooperative anti-jamming. Therefore, it is of great significance to consider the problem of cooperative anti-deception jamming under registration error. In this paper, the cooperative anti-deception jamming method is proposed in a distributed multiple-radar system under registration errors. On the premise of the known registration error, target received signal vectors are estimated from an uncertainty region in each channel by maximum likelihood (ML) algorithm. With the estimated received signal vectors, a target discrimination algorithm is introduced based on the difference in target spatial scattering characteristics, which calculate the correlation coefficient between different target received signal vectors and discriminate a false target with a designed threshold. Furthermore, since the registration error depends on the radar site errors, theoretical derivation for the registration error is given as a function of the transmitter and receiver site errors. Finally, simulation results verify the feasibility of the proposed discrimination method, and its performance due to the influence of the jamming-to-noise ratio (JNR), the registration error, the target size, and the discrimination threshold are considered. Full article

(This article belongs to the Special Issue Advanced Anti-Jamming Methods and Signal Processing Techniques for Radar System)

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18 pages, 4310 KiB

Open AccessArticle

Research on Ultra-Wideband Radar Echo Signal Processing Method Based on P-Order Extraction and VMD

by Qingjie Qi, Youxin Zhao, Liang Zhang, Zhen Yang, Lifeng Sun and Xinlei Jia

Sensors 2022, 22(18), 6726; https://doi.org/10.3390/s22186726 - 6 Sep 2022

Cited by 9 | Viewed by 2204

Abstract

As a new method to detect vital signs, Ultra-wideband (UWB) radar could continuously monitor human respiratory signs without contact. Aimed at addressing the problem of large interference and weak acquisition signal in radar echo signals from complex scenes, this paper adopts a UWB radar echo signal processing method that combines strong physical sign information extraction at P time and Variational Mode Decomposition (VMD) to carry out theoretical derivation. Using this novel processing scheme, respiration and heartbeat signals can be quickly reconstructed according to the selection of the appropriate intrinsic mode functions (IMFs), and the real-time detection accuracy of human respiratory signs is greatly improved. Based on an experimental platform, the data collected by the UWB radar module were first verified against the measured values obtained at the actual scene. The results of a validation test proved that our UWB radar echo signal processing method effectively eliminated the respiratory clutter signal and realized the accurate measurement of respiratory and heartbeat signals, which would prove the existence of life and further improve the quality of respiration and heartbeat signal and the robustness of detection. Full article

(This article belongs to the Special Issue Advanced Anti-Jamming Methods and Signal Processing Techniques for Radar System)

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9 pages, 1597 KiB

Open AccessCommunication

Characteristics of an Eight-Quadrant Corner Reflector Involving a Reconfigurable Active Metasurface

by Lin Gan, Guang Sun, Dejun Feng and Jianbing Li

Sensors 2022, 22(13), 4715; https://doi.org/10.3390/s22134715 - 22 Jun 2022

Cited by 4 | Viewed by 1924

Abstract

The traditional corner reflector is a type of classical passive jamming equipment but with several shortcomings, such as fixed electromagnetic characteristics and a poor response to radar polarization. In this paper, an eight-quadrant corner reflector equipped with an electronically controlled miniaturized active frequency-selective surface (MAFSS) for X band is proposed to obtain better radar characteristics controllability and polarization adaptability. The scattering characteristics of the new eight-quadrant corner reflector for different switchable scattering states (penetration/reflection), frequency and polarization are simulated and analyzed. Results show that the RCS modulation depth, which is jointly affected by the electromagnetic wave frequency and incident directions, can be maintained above 10 dB in the majority of directions, and even larger than 30 dB at the resonant frequency. Moreover, the RCS adjustable bandwidth can be as wide as 1 GHz in different incident directions. Full article

(This article belongs to the Special Issue Advanced Anti-Jamming Methods and Signal Processing Techniques for Radar System)

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