Design and Analysis of Compressed Sensing Radar Detectors

Anitori, Laura; Maleki, Arian; Otten, M.P.G.; Baraniuk, Richard G.; Hoogeboom, P.

doi:10.1109/tsp.2012.2225057

Cited by 116 publications

(61 citation statements)

References 30 publications

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“…In pulse-Doppler processing, some works [16,17] are towards detection of targets while other [18~23] are about the extraction of radar target's information (Doppler, range and amplitude). These pioneering works show that the processing effectiveness is highly dependent on the measurement matrix or the sub-Nyquist sampling system.…”

Section: Discussionmentioning

confidence: 99%

A pulse-Doppler processing scheme for quadrature compressive sampling radar

Liu

Chen

et al. 2014

2014 19th International Conference on Digital Signal Processing

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Quadrature compressive sampling (QuadCS) is a subNyquist sampling system for acquiring inphase and quadrature (I/Q) components of radio-frequency signals. This paper discusses the application of the QuadCS system to pulse-Doppler radars and develops a compressive sampling pulse-Doppler (CoSaPD) processing scheme from the sub-Nyquist samples. The Doppler estimation is realized through spectrum analyzer as in classic processing. The detection is done on the Doppler bin data. The range estimation is performed through sparse recovery algorithms on the detected targets. Due to inherent detection property of the recovery algorithms, the detection threshold can be set at a low value and then the introduced false targets are removed in the range estimation stage. Simulation results show that the CoSaPD scheme with the data at one eighth the Nyquist rate and for SNR above -25dB can achieve performance of the classic processing with Nyquist samples.

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Section: Discussionmentioning

confidence: 99%

A pulse-Doppler processing scheme for quadrature compressive sampling radar

Liu

Chen

et al. 2014

2014 19th International Conference on Digital Signal Processing

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“…The targets follow a near constant velocity dynamic model as in (1). The clutter is assumed uniformly distributed with density 1×10 −5 /m 3 .…”

Section: Distributed Compressed Sensing Based Joint Detection and Tramentioning

confidence: 99%

“…In the classical compressed sensing based radar system, the sparse vector is constructed based on the range (delay), angle, Doppler measurements or combination set of them [18,5,45,25,1,3]. The state vector has to be estimated at each scan based on the reconstructed range (delay), angle, Doppler measurements.…”

Section: Introductionmentioning

confidence: 99%

Distributed compressed sensing based joint detection and tracking for multistatic radar system

Liu

Mallick

2016

Information Sciences

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“…Very little work has yet evaluated exploitation performance with compressive [28,29] or sparsityconstrained [30,31] systems. Here we comment on constant false alarm rate (CFAR) detection.…”

Section: E Nonlinear Processingmentioning

confidence: 99%

Pitfalls and possibilities of radar compressive sensing

Goodman

Potter

2015

Appl. Opt.

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In this paper, we consider the application of compressive sensing (CS) to radar remote sensing applications. We survey a suite of practical system-level issues related to the compression of radar measurements, and we advocate the consideration of these issues by researchers exploring potential gains of CS in radar applications. We also give abbreviated examples of decades-old radio-frequency (RF) practices that already embody elements of CS for relevant applications. In addition to the cautionary implications of system-level issues and historical precedents, we identify several promising results that RF practitioners may gain from the recent explosion of CS literature.

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Design and Analysis of Compressed Sensing Radar Detectors

Cited by 116 publications

References 30 publications

A pulse-Doppler processing scheme for quadrature compressive sampling radar

A pulse-Doppler processing scheme for quadrature compressive sampling radar

Distributed compressed sensing based joint detection and tracking for multistatic radar system

Pitfalls and possibilities of radar compressive sensing

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