Imaging Enhancement of Stepped Frequency Radar Using the Sparse Reconstruction Technique

Pang, Bo; Dai, Dahai; Xing, Shu; Li, Yongzhen; Wang, Xuesong

doi:10.2528/pier13030407

Cited by 6 publications

(4 citation statements)

References 47 publications

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“…In this experiment, the size of the two-dimensional radar echo is 466 × 56, and the size of the scene is 309 × 158. If the conventional CSbased imaging algorithm is used [39,40], namely CS is used to improve range and azimuth resolutions simultaneously, the corresponding size of dictionary matrix A will be 26096 × 48822. It means that 48822 variables should be solved from 26096 equations, which is obviously an extensive computation burden.…”

Section: Experiments Resultsmentioning

confidence: 99%

“…Another contribution of this paper is the development of a computationally efficient implementation. For conventional SAR imaging algorithms based on the CS theory, an inherent requirement of two dimensional sampling for both the signal and the scene is required [39,40]. Although super-resolving ability can be achieved in both range and azimuth directions in this way, extensive computational effort is also involved, which hinders its practical usefulness.…”

Section: Computational Burden Analysismentioning

confidence: 99%

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An Enhanced Forward-Looking Sar Imaging Algorithm Based on Compressive Sensing

Pang¹,

Wu²,

Xing³

et al. 2019

PIER M

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Having the imaging ability of the area in front of flight direction, forward-looking synthetic aperture radar (SAR) has become a hot topic in areas of SAR research. Nevertheless, constrained by limited azimuth aperture length, the imaging of forward-looking SAR suffers from poor azimuth resolution. Aiming at this problem, an enhanced forward-looking SAR imaging algorithm is proposed in this paper. This algorithm takes both super-resolving ability and computational burden into account. Firstly, an imaging framework is proposed to decrease the computational burden. Secondly, an iterative regularization implementation of compressive sensing (CS) is proposed to improve azimuth resolution. Finally, imaging experiments based on simulated data and Ku-band complex valued image data from the MiniSAR system demonstrate the effectiveness of the proposed algorithm.

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Section: Experiments Resultsmentioning

confidence: 99%

Section: Computational Burden Analysismentioning

confidence: 99%

An Enhanced Forward-Looking Sar Imaging Algorithm Based on Compressive Sensing

Pang¹,

Wu²,

Xing³

et al. 2019

PIER M

Self Cite

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“…Stepped-frequency (SF) signal is widely used in the highresolution radar systems [1][2][3], because it can be used to get the high-resolution range profile (HRRP) of target. However, SF signal is highly sensitive to targets motion.…”

Section: Introductionmentioning

confidence: 99%

The New Mathematical Model of Motion Compensation for Stepped-Frequency Radar Signal

Lin

Pang

et al. 2014

Mathematical Problems in Engineering

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When a stepped-frequency radar is used to obtain the high-resolution range profile (HRRP) of high-speed target, accurate speed estimation and motion compensation must be considered. Therefore, in this paper, a novel mathematical method is presented for estimating the target speed. Firstly, the pulse Doppler method is used to calculate the initial estimation value. Secondly, based on the initial estimation value, the minimum entropy method is used to calculate the coarse estimation value. Finally, based on the coarse estimation value, the minimuml1-Norms method is used to calculate the accurate estimation value. The numeric simulation results confirm that this new method is effective and predominant, which has a much higher estimation accuracy in a low SNR and a much larger estimation range of target speed. The final estimation value can be used to well compensate for the influence of target speed on HRRP.

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“…Meanwhile, the idea of CS has also been introduced in imaging radar system. [9][10][11][12][13][14][15] In Ref. 10, a CS-based radar imaging method is proposed in which the pulse compression matched filter is no longer needed.…”

Section: Introductionmentioning

confidence: 99%

Two-dimensional sparse synthetic aperture radar imaging method with stepped-frequency waveform

Zhang

et al. 2015

J. Appl. Remote Sens

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Abstract. Stepped-frequency waveforms (SFWs) can use the digital signal processing method to obtain high-range resolution with relatively narrow instantaneous bandwidth, which has been used in synthetic aperture radar (SAR). However, SFWs have the disadvantages of poor antijamming capability and a long period of transmission. Also, in the coherent integration time, some echo data are frequently lost. A two-dimensional sparse imaging method in the space and frequency domains for SAR is proposed based on compressed sensing (CS) theory. A sparse SFW for SAR imaging is formed and analyzed first, which has the advantages of better antijamming capability and a shorter time period of transmission. The range compression is completed by using CS theory. As to the sparse echo data in the space domain, the imaging operator and the CS-based imaging scheme are constructed to simultaneously implement the range cell migration correction and azimuth compression. Compared with the conventional SAR imaging method of SFWs, a much smaller number of frequencies and a smaller amount of imaging data are required for SAR imaging by using the proposed method. Finally, the effectiveness of the proposed method is proven by simulation and experimental results. © The Authors.Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

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Imaging Enhancement of Stepped Frequency Radar Using the Sparse Reconstruction Technique

Cited by 6 publications

References 47 publications

An Enhanced Forward-Looking Sar Imaging Algorithm Based on Compressive Sensing

An Enhanced Forward-Looking Sar Imaging Algorithm Based on Compressive Sensing

The New Mathematical Model of Motion Compensation for Stepped-Frequency Radar Signal

Two-dimensional sparse synthetic aperture radar imaging method with stepped-frequency waveform

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