Compressive sensing and stretch processing

Krichene, H. A.; Sharp, Matthew D.; Lauritzen, Keir C.; Lucarelli, Dennis; Wang, I-J.

doi:10.1109/radar.2011.5960560

Cited by 9 publications

(6 citation statements)

References 9 publications

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“…The observation of radar received signal of radar before matched filter is For LFM waveform, its Pulse-Doppler compression is coupled together [37]. However, in our approach, we implement compressed sensing (in section 4) to improve the final image quality of the proposed radar.…”

Section: Data Acquisitionmentioning

confidence: 99%

3D Imaging Millimeter Wave Circular Synthetic Aperture Radar

Zhang

Cao

2017

Preprint

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Abstract:In this paper, a new millimeter wave 3D imaging radar is proposed. The user just needs to move the radar along a circular track, a high resolution 3D imaging can be generated. The proposed radar uses the movement of itself to synthesize a large aperture in both the azimuth and elevation directions. It can utilize inverse Radon transform to resolve 3D imaging. To improve the sensing result, compressed sensing approach is further investigated. The simulation and experimental result further illustrated the design. Because a single transceiver circuit is needed, a light, affordable and high resolution 3D mmWave imaging radar is illustrated in the paper.

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Section: Data Acquisitionmentioning

confidence: 99%

3D Imaging Millimeter Wave Circular Synthetic Aperture Radar

Zhang

Cao

2017

Preprint

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“…The first type is the sparsity‐based high‐range resolution imaging methods. In [6], the stretch waveform‐CS algorithm is proposed, which results in up to a 30% improvement in range resolution. In [7], a method of obtaining high‐range resolution profiles (HRRPs) with low computational complexity is proposed based on the CS.…”

Section: Introductionmentioning

confidence: 99%

Fast 2D super resolution ISAR imaging method under low signal‐to‐noise ratio

Li¹,

Chen²,

Liu³

et al. 2017

IET Radar, Sonar & Navigation

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“…It has been discussed in the literature that the off-grid targets create an important degradation in CS reconstruction performance [17][18][19][20][21][22][23] since the sparsity assumption on the defined grids is no longer valid. In [16], performance degradation for offgrid targets is discussed for CS and SP but a solution is not provided.…”

Section: Introductionmentioning

confidence: 99%

“…The CS framework is also studied with SP in [16]. In this application of CS to SP the continuous frequency space is discretised into a frequency grid and the DFT basis is used only to reconstruct the discrete frequency/range vectors.…”

Section: Introductionmentioning

confidence: 99%

Compressive sensing‐based robust off‐the‐grid stretch processing

Ilhan

Gürbüz

Arıkan

2017

IET Radar, Sonar & Navigation

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Classical stretch processing (SP) obtains high range resolution by compressing large bandwidth signals with narrowband receivers using lower rate analogue-to-digital converters. SP achieves the resolution of the large bandwidth signal by focusing into a limited range window, and by deramping in the analogue domain. SP offers moderate data rate for signal processing for high bandwidth waveforms. Furthermore, if the scene in the examined window is sparse, compressive sensing (CS)-based techniques have the potential to further decrease the required number of measurements. However, CS-based reconstructions are highly affected by model mismatches such as targets that are off-the-grid. This study proposes a sparsitybased iterative parameter perturbation technique for SP that is robust to targets off-the-grid in range or Doppler. The error between reconstructed and actual scenes is measured using Earth mover's distance metric. Performance analyses of the proposed technique are compared with classical CS and SP techniques in terms of data rate, resolution and signal-to-noise ratio. It is shown through simulations that the proposed technique offers robust and high-resolution reconstructions for the same data rate compared with both classical SP-and CS-based techniques.

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Compressive sensing and stretch processing

Cited by 9 publications

References 9 publications

3D Imaging Millimeter Wave Circular Synthetic Aperture Radar

3D Imaging Millimeter Wave Circular Synthetic Aperture Radar

Fast 2D super resolution ISAR imaging method under low signal‐to‐noise ratio

Compressive sensing‐based robust off‐the‐grid stretch processing

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