Sparsity Adaptive Matching Pursuit Detection Algorithm Based on Compressed Sensing for Radar Signals

Wei, Yanbo; Lu, Zhizhong; Yuan, Gannan; Zhao, Fang; Huang, Yu

doi:10.3390/s17051120

Cited by 22 publications

(9 citation statements)

References 26 publications

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“…Multichannel signal detection is a fundamental problem in the signal processing community [ 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 ]. Kelly first derived the generalized likelihood ratio test (GLRT) for multichannel radar systems in unknown noise in 1986 [ 9 ].…”

Section: Introductionmentioning

confidence: 99%

Distributed Target Detection in Unknown Interference

Deng

2022

Sensors

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Interference can degrade the detection performance of a radar system. To overcome the difficulty of target detection in unknown interference, in this paper we model the interference belonging to a subspace orthogonal to the signal subspace. We design three effective detectors for distributed target detection in unknown interference by adopting the criteria of the generalized likelihood ratio test (GLRT), the Rao test, and the Wald test. At the stage of performance evaluation, we illustrate the detection performance of the proposed detectors in the presence of completely unknown interference (not constrained to lie in the above subspace). Numerical examples indicate that the proposed GLRT and Wald test can provide better detection performance than the existing detectors.

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Section: Introductionmentioning

confidence: 99%

Distributed Target Detection in Unknown Interference

Deng

2022

Sensors

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“…X-band marine radar has high spatial and temporal resolution, as well as a low extra cost relative to other remotesensing instruments [8]. This type of radar has frequently been mounted on ships and other vessels for navigation purposes [9], providing a convenient means for studying sea surface inversion data, such as oil spill detection [10], surface current [11][12][13], wave height [14][15][16], and other factors.…”

Section: Introductionmentioning

confidence: 99%

An Energy Spectrum Algorithm for Wind Direction Retrieval From X-Band Marine Radar Image Sequences

Wang

Qiu

et al. 2021

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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In this study, an energy spectrum (ES) algorithm is proposed to retrieve wind direction from Xband marine radar image sequences. This algorithm is based on utilizing the occlusion area zero-pixel percentage (OZPP) to distinguish rain-free and rain-contaminated radar data. And then the rain-contaminated images are detected and discarded. The effect of radar radial attenuation in radar image sequences is modified by the piecewise fitting technique. Wind direction is determined from rain-free and radial correction data, based on the energy spectrum of small-scale wind streaks. The energy spectrum of small-scale wind streaks is obtained by establishing an energy spectrum scale separation filter. Based on the wind streak characteristics, a two-dimensional fast Fourier transform (FFT) is used to obtain the energy spectrum of radar images. The wind streak characteristics are derived from the distribution of the azimuth normalization radar cross-section (NRCS). The proposed algorithm is tested using data collected from X-band radar images and in-situ anemometer data from the coast of the East China Sea. Compared with the anemometer data, after using the proposed algorithm, the root-mean-square difference for wind direction is 12.13°, which is an acceptable result for engineering application.

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“…Alternatively, a lot of research studies today have attempted to employ compressed sensing (CS) to recover the real target signal directly from the jammed signal [23][24][25]. The real target signal in time domain extracted by the energy function can be utilized as a kind of compressed data [24].…”

Section: Introductionmentioning

confidence: 99%

A Truncated Matched Filter Method for Interrupted Sampling Repeater Jamming Suppression Based on Jamming Reconstruction

Wei

2021

Remote Sensing

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Interrupted sampling repeater jamming (ISRJ) is becoming more widely used in electronic countermeasures (ECM), thanks to the development of digital radio frequency memory (DRFM). Radar electronic counter-countermeasure (ECCM) is much more difficult when the jamming signal is coherent with the emitted signal. Due to the intermittent transmission feature of ISRJ, the energy accumulation of jamming on the matched filter shows a ‘ladder’ characteristic, whereas the real target signal is continuous. As a consequence, the time delay and distribution of the jamming slice can be obtained based on searching the truncated-matched-filter (TMF) matrix. That is composed of pulse compression (PC) results under matched filters with different lengths. Based on the above theory, this paper proposes a truncated matched filter method by the reconstruction of jamming slices to suppress ISRJ of linear frequency modulation (LFM) radars. The numerical simulations indicate the effectiveness of the proposed method and validate the theoretical analysis.

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Sparsity Adaptive Matching Pursuit Detection Algorithm Based on Compressed Sensing for Radar Signals

Cited by 22 publications

References 26 publications

Distributed Target Detection in Unknown Interference

Distributed Target Detection in Unknown Interference

An Energy Spectrum Algorithm for Wind Direction Retrieval From X-Band Marine Radar Image Sequences

A Truncated Matched Filter Method for Interrupted Sampling Repeater Jamming Suppression Based on Jamming Reconstruction

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