Isar Imaging Based on L1 L0 Norms Homotopy 2d Block Sparse Signal Recovery Algorithm

Ma, Changzheng; Ng, Boon Poh; Feng, Jundong

doi:10.2528/pierc16060701

Cited by 2 publications

(2 citation statements)

References 11 publications

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“…There are many algorithm to solve equation (33), such as greedy algorithm [23], convex optimization algorithm [24], and Bayesian statistical method [25]. However, for robust reconstruction performance and better noise immunity, the Bayesian inference theory is adopted with the maximum a posterior (MAP) criterion.…”

Section: B-isar Imaging Methods Of High-speed Target Based On Sparse Imentioning

confidence: 99%

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Bistatic ISAR Sparse Imaging Method for High-Speed Moving Target Based on Dechirping Processing

Zeng

Zhu

Xin

2019

International Journal of Antennas and Propagation

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Bistatic inverse synthetic aperture radar (ISAR) can increase the probability of tracking the high-speed target and provide more angle information than monostatic ISAR. However, bistatic ISAR suffers from a serious defocusing problem, resulting from the high-speed motion. Furthermore, the inherent geometry distortion and calibration problems make bistatic ISAR (B-ISAR) imaging more complex. In response to these problems, we propose a bistatic ISAR imaging method for high-speed moving target with geometric distortion correction and calibration based on dechirping processing. At first, based on the motion decomposition idea, the B-ISAR echo model of the high-speed moving target is established. Then, by analyzing the imaging mechanism of the Range-Doppler algorithm (RDA), we eliminate the phase items influencing the imaging quality with speed compensation and Doppler compensation. After that, the analytic formula of the geometric distortion factor and calibration factor are deduced, which helps transform the geometric correction and calibration problem into a parameter estimation problem. Finally, with the sparsity of the scattering points, the required parameters are solved using the expectation maximization (EM) algorithm based on the maximum a posteriori probability criterion. With the estimated parameters, a clear B-ISAR image of a high-speed moving target with geometric correction and calibration is obtained. The simulations show that the proposed method has a better resolution and simultaneously attains geometric correction and calibration of the image.

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Section: B-isar Imaging Methods Of High-speed Target Based On Sparse Imentioning

confidence: 99%

“…by Using the CPF. From equation (24), after the speed and translational compensation, the echo can be regarded as a cubic phase function with respect to t m in the cross-range direction. The high-order phase term will lead to a defocused image, as shown in Figures 5(a) and 5(c).…”

Section: Doppler Compensation Based On Parameter Estimationmentioning

confidence: 99%