基于动态规划的海面机动小目标长时间相干积分算法

Yao Zhang, Dunge Liu, Z. Xia, Tao Zhang, Zhilong Zhao, Yuhua Guo, Xin Liu, Yuqian Yang, Kejia Zhang, Huifeng Shi
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引用次数: 0

摘要

海面机动小目标的检测一直面临着海杂波背景强、信噪比低的问题,长时间相干积分算法可以有效地改善海杂波背景下的信噪比。针对海面强机动目标的距离偏移和多普勒频率偏移,提出了一种长时间相干积分算法。该算法采用阶段优化思想,能够同时补偿距离偏移和多普勒频率偏移,有效地积累目标沿弹道的能量,有效地提高目标的信噪比。此外,该算法还能在积累过程中实现目标速度和位置的精确跟踪,适用于任何机动模式。实际数据处理和分析表明,该算法能够实现对低信噪比机动目标的有效积累,积累增益比现有方法提高6dB以上。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Long-Time Coherent Integration Algorithm for Sea Surface Maneuvering Small Target Based on Dynamic Programming
Detection of sea surface maneuvering small target has long been faced with the problems of strong sea clutter background and low signal-clutter-noise ratio (SCNR), the long-time coherent integration algorithm can effectively improve the SCNR. A long-time coherent integration algorithm is proposed in this paper to process the echo signals of sea surface strongly maneuvering targets with both range and Doppler frequency migration. By using the idea of stage optimization, this algorithm can compensate the range and Doppler frequency migration at the same time, efficiently accumulate the target energy along the trajectory of the target, and effectively improve the SCNR of the target. In addition, this algorithm can also achieve the precise tracking of the target speed and position during the accumulation process, and is suitable for any maneuvering mode. The actual data processing and analysis show that this algorithm can realize the effective accumulation of maneuvering targets with low SCNR, and the accumulation gain is improved by more than 6dB compared with existing methods.
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