Problems in synthetic-aperture radar imaging

Cheney, Margaret; Borden, Brett

doi:10.1088/0266-5611/25/12/123005

Cited by 31 publications

(24 citation statements)

References 92 publications

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“…For more detailed information on SAR imaging, including several open problems in SAR imaging, the reader is referred to [7,8] and to the chapter in this handbook by Cheney and Borden [9]. The backscattered waves are picked up at a receiver or receivers, and the goal is to reconstruct an image of the region based on such measurements.…”

Section: Synthetic-aperture Radar Imagingmentioning

confidence: 99%

Microlocal Analysis in Tomography

Krishnan¹,

Quinto

2014

Handbook of Mathematical Methods in Imaging

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Several limited data problems in tomography will be presented in this chapter, including ones for X-ray tomography, electron microscopy, and radar imaging. First, reconstructions from limited data will be evaluated to observe their strengths and weaknesses. Then, the basic analytic properties of the transforms will be presented. The concept of microlocal analysis will be introduced to make the notion of singularity precise. Finally, the microlocal properties of the tomographic transforms are given and then used to explain the observed strengths and limitations of the reconstructions. This will show that these limitations are intrinsic to these limited data problems themselves.

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Section: Synthetic-aperture Radar Imagingmentioning

confidence: 99%

Microlocal Analysis in Tomography

Krishnan¹,

Quinto

2014

Handbook of Mathematical Methods in Imaging

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“…Wei (Wei et al 2010) described the SAR signal by separating the sparse target and the acquisition matrix of SAR signal. Another approach is the establishment of the linear model of the SAR raw data based on the Born Approximation (Cheney and Borden 2009;Sun et al 2014). This paper emphasizes the partial acquisition technique of the SAR system that was not done in the previous paper.…”

Section: Introductionmentioning

confidence: 99%

“…where G a is the amplitude of the transmitter signal and a(t) = rect(( − 2 ⁄ )⁄ ) is a rectangular gate function with as the pulse duration time (Cheney and Borden 2009). Furthermore, the ω o = 2 is the carrief frequency and LFM pulse chirp rate.…”

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confidence: 99%

A Partial Acquisition Technique of Sar System Using Compressive Sampling Method

Arief

2017

IJReSES

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Abstract. In line with the development of Synthetic Aperture Radar (SAR) technology, there is a serious problem when the SAR signal is acquired using high rate analog digital converter (ADC), that require large volumes data storage. The other problem on compressive sensing method, which frequently occurs, is a large measurement matrix that may cause intensive calculation. In this paper, a new approach was proposed, particularly on the partial acquisition technique of SAR system using compressive sampling method in both the azimuth and range direction. The main objectives of the study are to reduce the radar raw data by decreasing the sampling rate of ADC and to reduce the computational load by decreasing the dimension of the measurement matrix. The simulation results found that the reconstruction of SAR image using partial acquisition model has better resolution compared to the conventional method (Range Doppler Algorithm/RDA). On a target of a ship, that represents a low-level sparsity, a good reconstruction image could be achieved from a fewer number measurement. The study concludes that the method may speed up the computation time by a factor 4.49 times faster than with a full acquisition matrix.

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“…1 The main explanation is that, like other imaging systems such as tomography, we are faced with the problem of determining the spatial distribution of an unknown object (scene) from direct measurements that are called an image (in tomography, which is from indirect measurements, called a projection). 2 An inverse problem in specific seeks to estimate an object from a forward model and observed data.…”

Section: Introductionmentioning

confidence: 99%

“…g(s) = [Hf (r)](s) + (r), r ∈ R, s ∈ S (1) where g denotes the observed data, f (r) denotes the unknown objects(scene), r and s denotes the position, R and S denote whole original and observed image space respectively, H is an operator denoting the forward model, or to say, radar system response function, and denotes the noise.…”

Section: Introductionmentioning

confidence: 99%

Inverse problems arising in different synthetic aperture radar imaging systems and a general Bayesian approach for them

Zhu

Mohammad-Djafari

et al. 2011

SPIE Proceedings

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Synthetic Aperture Radar (SAR) imaging systems are nowadays very common technics of imaging in remote sensing and environment survey. There are different acquisition modes: spotlight, stripmap, scan; different geometries: mono-, bi-and multi-static; and varieties of specific applications: interferometric SAR (InSAR), polarimetric SAR etc. In this paper, first a common inverse problem framework for all of them is given, and then basics of SAR imaging and the classical deterministic inversion methods are presented. Aiming at overcoming the inadequacies of deterministic methods, a general probabilistic Bayesian estimation method is pioneered for solving image reconstruction problems. In particular, two priors which simply allow the automated determination of the hyperparameters in a Type-II likelihood framework are considered. Finally, the performances of the proposed methods on synthetic data.

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Problems in synthetic-aperture radar imaging

Abstract: The purpose of this review is to explain the basics of synthetic-aperture radar imaging to the Inverse Problems audience, and to list a variety of associated open problems.

Cited by 31 publications

References 92 publications

Microlocal Analysis in Tomography

Microlocal Analysis in Tomography

A Partial Acquisition Technique of Sar System Using Compressive Sampling Method

Inverse problems arising in different synthetic aperture radar imaging systems and a general Bayesian approach for them

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