Resolution Enhancement for Inversed Synthetic Aperture Radar Imaging Under Low SNR via Improved Compressive Sensing

Zhang, Lei; Xing, Mengdao; Qiu, Cheng‐Wei; Li, Jun; Sheng, Jialian; Li, Yachao; Bao, Zheng

doi:10.1109/tgrs.2010.2048575

Cited by 282 publications

(188 citation statements)

References 33 publications

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“…Inspired by an ordered-statistics constant-false-alarm-rate (CFAR) detector [28] as well as noise level estimation in [22], we can first order all image cells by their energy and determine the cells with largest energy as signal cells and the rest as noise samples. The lower threshold for the mean energy of image cells to select signal cells is given as…”

Section: Sdd-cs Processing Scheme For Wideband Rpri Radarmentioning

confidence: 99%

“…In addition, considering that the direct application of CS theory will result in large-scale dictionaries and high computational complexity, we intended to scale down the dictionaries by using some prior information. It is well known that the existing CS-based schemes mainly focus on the undersampling of the measurement data [16,[19][20][21][22], which will reduce the row number of the dictionary. For our problem, we also thin the dictionary in the parameter domain, which determines its column number.…”

Section: Introductionmentioning

confidence: 99%

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High Resolution Wideband Imaging of Fast Rotating Targets Based on Random Pri Radar

Liu¹,

Chen²,

Sui³

2018

PIER M

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Abstract-By exploiting the micro-motion features of fast rotating targets, wideband radar has been successfully applied to high resolution imaging. However, due to the traditional fixed pulse repetition interval (PRI), the target image may suffer from aliasing in some practical situations. In this paper, under the compressed sensing (CS) radar framework, an efficient wideband imaging scheme with random PRI signal is introduced for aliasing reduction. Considering that direct application of the CS theory will result in large-scale dictionaries and high computational complexity, we firstly generate a low resolution image by applying modified generalized Radon transform on range-slow time domain and then scale down the dictionary column by reserving the atoms corresponding to those strong scattering areas. Simulation results show that this scheme can achieve aliasing-free images with acceptable computational cost.

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Section: Sdd-cs Processing Scheme For Wideband Rpri Radarmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

High Resolution Wideband Imaging of Fast Rotating Targets Based on Random Pri Radar

Liu¹,

Chen²,

Sui³

2018

PIER M

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show abstract

“…However, for a special dictionary, in general, it is not easy to test whether G Σ satisfies RIP. Herein, a method based on eigenvalue statistics which has been described in [46] is adopted. After scaling, columns of G Σ have unit norm, and it is explicit that G Σ obeys-the RIP of order k when G T Σk G Σk has eigenvalues sufficiently within (1 − δ k , 1 + δ k ).…”

Section: And In Order Tomentioning

confidence: 99%

Forward-Looking Imaging of Scanning Phased Array Radar Based on the Compressed Sensing

Wen¹,

Kuang²,

Hu³

et al. 2013

PIER

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Abstract-In this paper, a novel forward-looking imaging method based on the compressed sensing is proposed for scanning phased array radar (PAR) in order to improve the azimuth resolution. Firstly, the echo of targets is modeled according to the principle of PAR. Then, it is analyzed why some of the former methods as multi-channel deconvolution are ineffective based on the signal model. Using a widely accepted assumption that dominant scatterers in an interesting area are sparse or compressible, an imaging algorithm based on the compressed sensing is proposed and investigated. This method obtains its high range resolution by transmitting and compressing chirp pulse signal, and improves its azimuth resolution by utilizing the compressed sensing technique. The effectiveness of the proposed method is illustrated and analyzed with simulations data.

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“…Using these range noise bins estimate noise level ε . The threshold can be expressed as follow [4] :…”

Section: Advanced Engineering Forum Vols 6-7 683mentioning

confidence: 99%

“…The research shows that imaging methods based on sparse representation utilize the sparsity of target scene and nonlinear optimization algorithms to realize sparse representation and reconstruction of the signal, which break through the limitation of Nyquist sampling theorem and achieve the purpose of super resolution [2][3][4][5][6] . Therefore, the paper combines sparse representation and time-frequency transform, and constructs appropriately dictionary based on time-frequency basis, thus achieve the well focused ISAR image with super resolution.…”

Section: Introductionmentioning

confidence: 99%

A New Rang-Instantaneous Doppler ISAR Imaging Algorithm

Wang

Sun

Guo

2012

AEF

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ISAR imaging algorithm based on sparse representation has the advantages of high resolution, noise suppression and dealing with gapped data effectively. The method is based on the hypothesis that the imaging targets move smoothly. But the movement of ISAR imaging targets is usually of high maneuverability, which results in big phase error after motion compensation. Using the traditional RD imaging algorithm and the imaging algorithm based on sparse representation will make the resultant image fuzzy, and can't even be identified. This paper introduces a new rangeinstantaneous Doppler imaging algorithm based on sparse representation and time-frequency transform, which can effectively image the maneuvering target. The experimental results validate the feasibility of this approach.

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Resolution Enhancement for Inversed Synthetic Aperture Radar Imaging Under Low SNR via Improved Compressive Sensing

Cited by 282 publications

References 33 publications

High Resolution Wideband Imaging of Fast Rotating Targets Based on Random Pri Radar

High Resolution Wideband Imaging of Fast Rotating Targets Based on Random Pri Radar

Forward-Looking Imaging of Scanning Phased Array Radar Based on the Compressed Sensing

A New Rang-Instantaneous Doppler ISAR Imaging Algorithm

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