适用于复杂地理环境的lss目标智能检测方法

Hao Chen, Chanjuan Zhao, Chunlei Zhao, Guanghui Xu, Ming Fang
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引用次数: 0

摘要

在复杂的地理环境中,由于杂波与目标回波的严重混叠,在对lss目标的检测中经常出现虚警、漏检等问题,导致雷达对lss目标的检测概率较低。针对这一困难,本文提出了一种lss目标的智能检测方法。首先,采用KMeans算法对场景进行识别和判断;然后利用RELAX算法对强杂波特别是强点源杂波进行抑制,降低其对弱目标回波的影响。然后通过多普勒滤波器组进行相干积累,以提高信杂比。最后对检测区域进行自适应杂波场景判断,对某多普勒信道距离维进行智能恒虚警检测。与传统方法相比,该算法具有较强的弱目标检测能力和较强的复杂场景适应能力。仿真结果验证了该算法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
LSS-target Intelligent Detection Method Suitable for Complex Geographical Environment
In complex geographical environment, due to the serious aliasing of clutter and target echo, problems such as false alarm and missed detection appear frequently in the detection of LSS-targets, resulting in the low detection probability of radar for such targets. To cope with such difficulty, the paper proposes an intelligent detection method for LSS-targets. First, The scene is identified and judged by the KMeans algorithm; then the strong clutter, especially strong point source clutter, is suppressed by the RELAX algorithm to reduce its influence on the weak target echo. Then coherent accumulation is performed through the Doppler filter bank to improve the signal-to-clutter ratio. Finally, adaptive clutter scene judging is performed on the detection area, and intelligent constant false alarm detection is performed in the range dimension of certain Doppler channel. Compared with traditional methods, the proposed algorithm shows superior ability of weak target detection and distinguished adapt ability in complex scenarios. Simulation results verify the effectiveness of the proposed algorithm.
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