Feature extraction of space nutation cone-shaped targets based on radar network

S. Zhao, C. Feng, W. H. Lu
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引用次数: 0

Abstract

Micro-motion feature is one of the crucial features used for ballistic target recognition. Aiming at the problem that single-view observation can't extract the nutation parameters, a novel algorithm based on the radar network is proposed to extract the target features. Firstly, the nutation model of cone-shaped target is built, the micro-Range modulation trait caused by nutation is analyzed in detail. Then under the precondition of considering the invisible problem of scattering centers, each scattering center in different perspectives is matched based on the scattering center' microRange difference, and the periodicity of target nutation is proved by Bessel function expansion, what' more, the target nutation and configuration parameters are estimated by utilizing the change rule of nutation angle combined with curve fitting method. Finally, Simulation results are given for validating the proposed algorithms.
基于雷达网络的空间章动锥形目标特征提取
微运动特征是弹道目标识别的关键特征之一。针对单视图观测无法提取章动参数的问题,提出了一种基于雷达网络的目标特征提取算法。首先,建立了锥体目标的章动模型,详细分析了由章动引起的微距离调制特性。然后,在考虑散射中心不可见问题的前提下,基于散射中心的microorange差异对不同角度下的各个散射中心进行匹配,通过贝塞尔函数展开证明目标章动的周期性,并结合曲线拟合方法利用章动角变化规律估计目标章动和组态参数。最后给出了仿真结果,验证了所提算法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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