Synthetic Aperture Radar autofocus via Semidefinite Relaxation

Liu, Kuang-Hung; Wiesel, Ami; Munson, D.C.

doi:10.1109/icassp.2010.5495441

Cited by 11 publications

(9 citation statements)

References 14 publications

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“…. (5) where is the total number of pulses and is phase error of pulse. In general phase errors are independent of the fast time and are assumed to be the same for the same pulse [12],…”

Section: Signal Modelmentioning

confidence: 99%

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Analysis of sparsity based joint SAR image reconstruction and autofocus techniques

Çamlıca

Güven

Gürbüz

et al. 2015

2015 3rd International Workshop on Compressed Sensing Theory and Its Applications to Radar, Sonar and Remote Sensing (CoSeRa)

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Synthetic Aperture Radar (SAR) has significance in many remote sensing applications. One of the main problems with SAR is the platform motion that causes defocusing in the reconstructed SAR image. To mitigate this problem, for particularly on imaging of fields that admit a sparse representation, various sparsity based techniques that either apply optimization procedures or greedy iterative solutions have been proposed in the literature. Although these techniques have been mainly compared with classical phase gradient autofocus (PGA) algorithm, they have not been analyzed and compared with each other. In this paper several of the recent sparsity based SAR phase correction techniques are compared using metrics such as mean square error (MSE), entropy, target to background ratio (TBR) in terms of undersampling ratio, signal to noise ratio (SNR). In addition to comparisons, a cross validation based stopping criterion is introduced with an OMP procedure to free the algorithm from user defined parameters. The techniques are tested on simulated data for detailed comparisons. Real data results of tested techniques are also provided. Our initial results show that all compared sparsity based techniques provide better performance compared to PGA with varying relative performances.

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“…. (5) where is the total number of pulses and is phase error of pulse. In general phase errors are independent of the fast time and are assumed to be the same for the same pulse [12],…”

Section: Signal Modelmentioning

confidence: 99%

“…One of the most well known techniques is the phase gradient autofocus (PGA) [3], which corrects phases based on dominant targets. Although there are many other autofocus techniques for classical SAR imaging [4], [5] sparsity based SAR imaging and autofocus techniques have been proposed in the recent years [6]- [9].…”

Section: Introductionmentioning

confidence: 99%

Analysis of sparsity based joint SAR image reconstruction and autofocus techniques

Çamlıca

Güven

Gürbüz

et al. 2015

2015 3rd International Workshop on Compressed Sensing Theory and Its Applications to Radar, Sonar and Remote Sensing (CoSeRa)

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“…This paper expands upon a preliminary version of our work reported in [18]. The organization of the paper is as follows.…”

Section: Introductionmentioning

confidence: 95%

Synthetic Aperture Radar Autofocus via Semidefinite Relaxation

Liu

Wiesel

Munson

2013

IEEE Trans. on Image Process.

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The autofocus problem in synthetic aperture radar imaging amounts to estimating unknown phase errors caused by unknown platform or target motion. At the heart of three state-of-the-art autofocus algorithms, namely, phase gradient autofocus, multichannel autofocus (MCA), and Fourier-domain multichannel autofocus (FMCA), is the solution of a constant modulus quadratic program (CMQP). Currently, these algorithms solve a CMQP by using an eigenvalue relaxation approach. We propose an alternative relaxation approach based on semidefinite programming, which has recently attracted considerable attention in other signal processing problems. Experimental results show that our proposed methods provide promising performance improvements for MCA and FMCA through an increase in computational complexity.

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“…There are several sparsity driven approaches in the literature that attack this problem [2], [3], [11], [4]. The methods usually solve a sparsity enhancing optimization problem by minimizing the functional:…”

Section: B Sparsity Driven Autofocus (Sda)mentioning

confidence: 99%

“…There are several algorithms that can estimate and correct the phase error, however these algorithms have not been proven to work well in the context of compressed sensing. While sparsity-driven autofocused SAR imaging has been proposed before [1], [2], [3], [4], [5], computationally efficient algorithms for practical use remains a challenge. Our contribution here is an improved and computationally efficient alternating direction method of multipliers (ADMM) based algorithm for autofocused compressive SAR imaging.…”

Section: Introductionmentioning

confidence: 99%

Autofocused compressive SAR imaging based on the alternating direction method of multipliers

Güngör

Çetin

Güven

2017

2017 IEEE Radar Conference (RadarConf)

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Abstract-We present an alternating direction method of multipliers (ADMM) based autofocused Synthetic Aperture Radar (SAR) imaging method in the presence of unknown 1-D phase errors in the phase history domain, with undersampled measurements. We formulate the problem as one of joint image formation and phase error estimation. We assume sparsity of strong scatterers in the image domain, and as such use sparsity priors for reconstruction. The algorithm uses p-norm minimization (p ≤ 1) [8] with an improvement by integrating the phase error updates within the alternating direction method of multipliers (ADMM) steps to correct the unknown 1-D phase error. We present experimental results comparing our proposed algorithm with a coordinate descent based algorithm in terms of convergence speed and reconstruction quality.

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Synthetic Aperture Radar autofocus via Semidefinite Relaxation

Cited by 11 publications

References 14 publications

Analysis of sparsity based joint SAR image reconstruction and autofocus techniques

Analysis of sparsity based joint SAR image reconstruction and autofocus techniques

Synthetic Aperture Radar Autofocus via Semidefinite Relaxation

Autofocused compressive SAR imaging based on the alternating direction method of multipliers

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