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Strip-Mode Microwave Staring Correlated Imaging with Self-Calibration of Gain–Phase Errors

机译:带增益相位误差自校准的带状模式微波凝视相关成像

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摘要

Microwave staring correlated imaging (MSCI) can realize super resolution imaging without the limit of relative motion with the target. However, gain–phase errors generally exist in the multi-transmitter array, which results in imaging model mismatch and degrades the imaging performance considerably. In order to solve the problem of MSCI with gain–phase error in a large scene, a method of MSCI with strip-mode self-calibration of gain–phase errors is proposed. The method divides the whole imaging scene into multiple imaging strips, then the strip target scattering coefficient and the gain–phase errors are combined into a multi-parameter optimization problem that can be solved by alternate iteration, and the error estimation results of the previous strip can be carried into the next strip as the initial value. All strips are processed in multiple rounds, and the gain–phase error estimation results of the last strip can be taken as the initial value and substituted into the first strip for the correlated processing of the next round. Finally, the whole imaging in a large scene can be achieved by multi-strip image splicing. Numerical simulations validate its potential advantages to shorten the imaging time dramatically and improve the imaging and gain–phase error estimation performance.
机译:微波凝视相关成像(MSCI)可以实现超分辨率成像,而没有与目标相对运动的限制。但是,多发射器阵列中通常存在增益相位误差,这会导致成像模型不匹配,并显着降低成像性能。为了解决在大场景下具有相位误差的MSCI问题,提出了一种带状相位误差自校正的MSCI方法。该方法将整个成像场景划分为多个成像带,然后将带目标散射系数和增益相位误差组合为一个多参数优化问题,可以通过交替迭代解决该问题,并且前一个带的误差估计结果可以作为初始值带入下一个试条。所有条带都经过多轮处理,最后一条带的增益相位误差估计结果可以作为初始值,并替换为第一条带,以进行下一轮的相关处理。最后,通过多条图像拼接可以实现大场景下的整体成像。数值模拟证实了其潜在的优势,可以大大缩短成像时间,并改善成像和增益相位误差估计性能。

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