引用本文: | 芦永强,韩壮志,张宏伟. 一种非平稳复杂环境下的自适应恒虚警算法[J]. 雷达科学与技术, 2018, 16(3): 333-337.[点击复制] |
LU Yongqiang, HAN Zhuangzhi, ZHANG Hongwei. An Adaptive CFAR Algorithm in Nonstationary and Complex Environment[J]. Radar Science and Technology, 2018, 16(3): 333-337.[点击复制] |
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摘要: |
针对当前恒虚警算法在非平稳强干扰环境下检测适应性能较差的问题,提出了一种自适应恒虚警检测方法。该算法利用二阶统计假设与Shapiro-Wilk检验得到具有均匀分布的杂波背景估计,并且结合频域加窗处理方法,对超高射速脱壳弹弹丸多目标回波进行处理,消除了卡瓣频谱干扰的影响。实测数据表明,该算法不需要任何关于背景环境的先验信息,可以适应多种回波数据,实现了在复杂强干扰环境中对目标的精确检测。 |
关键词: 超高射速弹丸多目标 剔除平均恒虚警 自适应恒虚警 二阶统计假设 Shapiro-Wilk检验 频域加窗 |
DOI:10.3969/j.issn.1672-2337.2018.03.017 |
分类号:TN957 |
基金项目: |
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An Adaptive CFAR Algorithm in Nonstationary and Complex Environment |
LU Yongqiang, HAN Zhuangzhi, ZHANG Hongwei
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The Army Engineering University, Shijiazhuang 050003, China
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Abstract: |
An adaptive CFAR detection method is proposed to solve the problem that the current CFAR algorithms show poor performance in nonstationary and strong interference environments. The algorithm uses second order statistical hypothesis and Shapiro-Wilk test to obtain uniformly distributed clutter background estimation. Combining with frequency domain windowing algorithm, it performs processing of the multi-target echoes of high firing rate projectile to eliminate the spectrum obstruct of the claw. The measured data show that the algorithm can adapt to a variety of echo data without any prior information about the background environment and achieve accurate CFAR detection in complex and strong interference environment. |
Key words: ultra-high firing rate projectile multi-target TM-CFAR adaptive CFAR second order statistical hypothesis Shapiro-Wilk test frequency domain windowing |