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

机译:基于Dechirping处理的高速移动目标的BISTATIC ISAR稀疏成像方法

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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.
机译:双面逆合成孔径雷达(ISAR)可以提高跟踪高速目标的概率并提供比单声道ISAR的更多角度信息。然而,基体徒患有严重的散焦问题,由高速运动产生。此外,固有的几何失真和校准问题使双面isar(b-isar)成像更复杂。响应于这些问题,我们提出了一种基于Dechirping处理的几何失真校正和校准的高速移动目标的双稳态ISAR成像方法。首先,基于运动分解思想,建立了高速移动目标的B-ISAR回声模型。然后,通过分析范围 - 多普勒算法(RDA)的成像机制,我们消除了影响成像质量的相项目,随着速度补偿和多普勒补偿。之后,推导出几何失真因子和校准因子的分析公式,这有助于将几何校正和校准问题转换为参数估计问题。最后,利用散射点的稀疏性,使用基于最大后验概率标准的期望最大化(EM)算法来解决所需参数。利用估计参数,获得具有几何校正和校准的高速移动目标的清晰B-ISAR图像。模拟表明,该方法具有更好的分辨率,同时达到图像的几何校正和校准。

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