A Novel Image Formation Algorithm for High-Resolution Wide-Swath Spaceborne Sar Using Compressed Sensing on Azimuth Displacement Phase Center Antenna

Chen, Jie; Gao, Jingqun; Zhu, Yanqing; Yang, Wei; Wang, Pengbo

doi:10.2528/pier11121101

Cited by 32 publications

(33 citation statements)

References 23 publications

(41 reference statements)

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“…A great deal of compressed sensing based methods have been applied to radar systems [8][9][10][11][12][13][14][15][16][17][18], which recover the target scene from fewer measurements than traditional methods. In [8], it is demonstrated that the compressed sensing can eliminate the need for matched filter at the receiver and has the potential to reduce the required sampling rate.…”

Section: Introductionmentioning

confidence: 99%

“…[10] focuses on monostatic chaotic multiple-input-multiple-output (MIMO) radar systems and analyze theoretically and numerically the performance of sparsity-exploiting algorithms for the parameter estimation of targets at Low-SNR. In the context of synthetic aperture radar (SAR), [11][12][13][14][15][16] present compressed sensing based data acquisition and imaging algorithms. An additional sensing matrix H is introduced in [17,18], which compress the received signal further by making nonadaptive, linear projections of the direct data sampled at the Nyquist frequency.…”

Section: Introductionmentioning

confidence: 99%

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Compressed Sensing Based Track Before Detect Algorithm for Airborne Radars

Liu¹,

Han²,

Yao³

et al. 2013

PIER

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Abstract-This paper presents a novel compressed sensing based track before detect (CS-TBD) algorithm. The proposed algorithm reconstructs the whole radar scenario (direction of arrival (DOA)-Doppler plane) for each range gate at consecutive scans using an improved stagewise orthogonal matching pursuit (StOMP) algorithm, resulting in a three-dimensional range-DOA-Doppler space. It then performs temporal tracking in the newly built three-dimensional range-DOA-Doppler space, based on the information from multiple illuminations during each scan, as well as among consecutive scans. In the proposed CS-TBD algorithm, the improved StOMP algorithm together with the temporal tracking, can effectively distinguish true targets from false targets and clutter based on information from multiple illuminations.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Compressed Sensing Based Track Before Detect Algorithm for Airborne Radars

Liu¹,

Han²,

Yao³

et al. 2013

PIER

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“…Synthetic aperture radar (SAR) is a microwave sensor which has the ability to produce all-weather, 24-hour a day, high-resolution images [1,2]. A SAR system sends electromagnetic pulses from a radar mounted on an airborne or spaceborne platform to a particular area of interest on the ground and records the return signals.…”

Section: Introductionmentioning

confidence: 99%

Sar Target Classification Using Bayesian Compressive Sensing With Scattering Centers Features

Zhang¹,

Qin²,

Li³

2013

PIER

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Abstract-The emerging field of compressed sensing provides sparse reconstruction, which has demonstrated promising results in the areas of signal processing and pattern recognition. In this paper, a new approach for synthetic aperture radar (SAR) target classification is proposed based on Bayesian compressive sensing (BCS) with scattering centers features. Scattering centers features is extracted as a l 1 -norm sparse problem on the basis of SAR observation physical model, which can improve discrimination ability compared with original SAR image. Using an overcomplete dictionary constructed by training samples, BCS is utilized to design targets classifier. For target classification performance evaluation, the proposed method is compared with several state-of-art methods through experiments on Moving and Stationary Target Acquisition and Recognition (MSTAR) public release database. Experiment results illustrate the effectiveness and robustness of the proposed approach.

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“…The spaceborne synthetic aperture radar (SAR) systems have attracted special interest in remote sensing tasks due to its high resolution [1,2], day/night operations, weather insensitivity and global coverage. Recently, SAR systems have been employed for environmental monitoring [3], surveillance [4,5], target identification [6], public security [7], navigation [8] and target recognition [9].…”

Section: Introductionmentioning

confidence: 99%

Kalman Filter for Removal of Scalloping and Inter-Scan Banding in Scansar Images

Iqbal¹,

Chen²,

Yang³

et al. 2012

PIER

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Abstract-Spaceborne synthetic aperture radar (SAR) plays more and more important role in Earth observation science, especially with ScanSAR mode which provides wide-swath coverage with moderate resolution. However, scalloping and inter-scan banding (ISB) are two major artifacts, which significantly degrade the quality of ScanSAR images. In this paper, a novel technique for removal of scalloping and ISB in ScanSAR images is proposed. Scalloping and ISB artifacts are modeled by two-dimensional gain and offset parameters varying as function of both azimuth time and range position. The gain and offset parameters can be split into azimuth and range components. The variations of gain/offset with respect to azimuth and range positions would represent scalloping and ISB artifacts respectively. In the proposed technique, recursive and minimum mean square error (MMSE) estimates of azimuth gain/offset parameters are found out by using Kalman filter for each azimuth location in a subswath by considering corresponding range samples as observation vector. Subsequently, range gain/offset parameters causing ISB artifacts are estimated by using Kalman filter for each range positions by considering azimuth samples as observation vector. The MMSE estimates of gain/offset parameters are used to directly remove scalloping and ISB artifacts. The proposed scheme was applied on simulated as well as calibrated real ScanSAR images. The experimental results exhibited the potential of proposed technique to be used as post processing tool for enhancing ScanSAR image quality.

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A Novel Image Formation Algorithm for High-Resolution Wide-Swath Spaceborne Sar Using Compressed Sensing on Azimuth Displacement Phase Center Antenna

Cited by 32 publications

References 23 publications

Compressed Sensing Based Track Before Detect Algorithm for Airborne Radars

Compressed Sensing Based Track Before Detect Algorithm for Airborne Radars

Sar Target Classification Using Bayesian Compressive Sensing With Scattering Centers Features

Kalman Filter for Removal of Scalloping and Inter-Scan Banding in Scansar Images

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