UAV detection via long-time coherent integration for passive bistatic radar

Zuo, Luo; Wang, Jipeng; Chen, Gang

doi:10.1016/j.dsp.2021.102997

Cited by 18 publications

(3 citation statements)

References 34 publications

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“…Hough transform was used to improve the performance of general high-resolution radar in detecting and tracking UAVs [ 16 ]. A coherent integration method based on stretch processing and chirp-z transform in the frequency domain is proposed for passive bistatic radar to improve UAV detection performance [ 17 ].…”

Section: Introductionmentioning

confidence: 99%

Robust Transmit Beamforming Algorithm for Low-Altitude Slow-Speed Small Target Detection

Jin

Wang

et al. 2022

Computational Intelligence and Neuroscience

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Strong ground clutter echoes make it difficult to detect low-altitude slow-speed small (LSS) targets. To suppress ground clutter effectively in LSS target detection, a robust transmit beamforming algorithm has been proposed in this paper. Sidelobes in the ground side can be cut down, with the excess energy concentrated on the air side, which would be cleaner and simpler. The objective function is a second-order cone programming problem and can be solved by the convex optimization algorithm. With the consideration of taking full advantage of transmit power, the weight vector is further processed under the unimodular constraint. Numerical experiments are carried out to demonstrate the validity and superiority of the proposed method.

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Section: Introductionmentioning

confidence: 99%

Robust Transmit Beamforming Algorithm for Low-Altitude Slow-Speed Small Target Detection

Jin

Wang

et al. 2022

Computational Intelligence and Neuroscience

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“…In the radar field, the surveillance radar requires high system gain to realize long-range target detection. PBRs also need a high system gain for wide zone coverage [24]. However, the entire transmitter parameters are beyond the control of the system designer, including the antenna gain, the power, and the bandwidth [25].…”

Section: Introductionmentioning

confidence: 99%

A Coherent Integration Method for Moving Target Detection in Frequency Agile Signal-Based Passive Bistatic Radar

Zuo,

Li,

Tan

et al. 2024

Remote Sensing

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In this paper, the possibility of improving target detection performance in passive bistatic radar by exploiting a frequency agile (FA) signal is investigated, namely frequency agile signal-based passive bistatic radar (FAPBR) coherent integration. Since the carrier frequency of each pulse signal is agile, FAPBR coherent integration suffers from the problems of random range and Doppler phase fluctuations. To tackle these challenges, a novel FA signal coherent integration target detection scheme for PBR is proposed. In particular, the phase quadratic difference principle is presented for eliminating Doppler phase hopping. Then, frequency rearrangement is adopted to compensate for random range phase fluctuation while obtaining the high-range-resolution profiles (HRRPs) of the detecting target. Further, we innovatively present a sliding-range ambiguity decoupling (S-RAD) method to remove the range ambiguity effect in the case of the high pulse repetition frequency (HPRF). Compared with the existing methods, the proposed method can effectively mitigate Doppler phase hopping without requiring prior target velocity information, offering improved coherent integration performance in frequency agile signals with reduced computational complexity. Moreover, it successfully corrects the range ambiguity issue caused by HPRF. Finally, a series of simulation results are presented to demonstrate the effectiveness of the proposed algorithm.

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“…However, the received signal is always noisy and multipath clutter-polluted, which results in clutter remaining in the adaptive filtering process, and therefore leads to deterioration of the target detection performance [ 20 ]. Particularly, for the low-observable target, such as unmanned aerial vehicle (UAV) detection, the impact of impure reference signal is more serious because of the low radar cross-section (RCS) [ 21 ]. Therefore, to obtain the desired target detection ability in DTMB-based PBR, the reference signal should be as pure as possible.…”

Section: Introductionmentioning

confidence: 99%

A Joint Low-Rank and Sparse Method for Reference Signal Purification in DTMB-Based Passive Bistatic Radar

Zuo

Zhao

Cheng

2021

Sensors

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In a digital terrestrial multimedia broadcasting (DTMB)-based passive bistatic radar (PBR) system, the received reference signal often suffers from serious multipath effect, which decreases the detection ability of low-observable targets in urban environments. In order to improve the target detection performance, a novel reference signal purification method based on the low-rank and sparse feature is proposed in this paper. Specifically, this method firstly performs synchronization operations to the received reference signal and thus obtains the corresponding pseudo-noise (PN) sequences. Then, by innovatively exploiting the inherent low-rank structure of DTMB signals, the noise component in PN sequences is reduced. After that, a temporal correlation (TC)-based adaptive orthogonal matching pursuit (OMP) method, i.e., TC-AOMP, is performed to acquire the reliable channel estimation, whereby the previous noise-reduced PN sequences and a new halting criterion are utilized to improve channel estimation accuracy. Finally, the purification reference signal is obtained via equalization operation. The advantage of the proposed method is that it can obtain superior channel estimation performance and is more efficient compared to existing methods. Numerical and experimental results collected from the DTMB-based PBR system are presented to demonstrate the effectiveness of the proposed method.

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UAV detection via long-time coherent integration for passive bistatic radar

Cited by 18 publications

References 34 publications

Robust Transmit Beamforming Algorithm for Low-Altitude Slow-Speed Small Target Detection

Robust Transmit Beamforming Algorithm for Low-Altitude Slow-Speed Small Target Detection

A Coherent Integration Method for Moving Target Detection in Frequency Agile Signal-Based Passive Bistatic Radar

A Joint Low-Rank and Sparse Method for Reference Signal Purification in DTMB-Based Passive Bistatic Radar

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