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一种基于多模型高斯逆WishartPHD滤波器的空间邻近目标跟踪方法

Keywords: 红外传感器,像平面,空间邻近目标,扩展目标概率假设密度滤波器,多模型,高斯逆Wishart分布

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Abstract:

将空间邻近目标(CloselySpacedObjects,CSOs)整体建模为扩展目标(ExtendedTarget,ET),用随机矢量和随机矩阵分别描述CSOs质心运动和扩散状态,并采用高斯逆Wishart(GaussianinverseWishart,GIW)概率假设密度(ProbabilityHypothesisDensity,PHD)滤波器实现杂波和漏检条件下CSOs的稳定跟踪.修正了原GIW-PHD滤波器量测模型和形状估计的缺陷,给出新的递推表达式,并在此基础上提出一种多(形变)模型GIW-PHD滤波器,以适应CSOs分裂和融合引起的形状变化.仿真结果表明,所提算法能够有效跟踪CSOs,状态估计比原GIW-PHD更加准确,对CSOs的变化更加敏感.

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