目标机动性未知时的多平台交互式多模型融合算法  

The multi-platform Imm fusion alogrithm without knowledge of target maneuver

作　　者：魏同利[1] 郝惠娟[2] 

机构地区：[1]北方民族大学基础部,宁夏银川750021 [2]宁夏大学,宁夏银川750021

出　　处：《西南民族大学学报（自然科学版）》2009年第2期244-248,共5页Journal of Southwest Minzu University(Natural Science Edition)

摘　　要：多平台的交互式多模型(IMM)Kalman滤波器是一种比较有效的机动目标跟踪估计方法.但当目标存在未知机动时,基于模型的估计器的精度就会下降.目标跟踪中的输入估计技术可对未知机动性进行估计.本文在给出过程噪声和量测噪声相关情况下最小方差无偏(MVU)输入、状态滤波估计的基础上,提出了基于上述滤波器的分布式IMM多传感器多平台融合算法.仿真表明了该算法的有效性.The Imm kalman filter is the comparative effective target maneuver is unknown, the performance of the Kalman Fusion Algorithm in multi-platform target track, but when the filter degrades. The magnitude of the target maneuver can be estimated by the input estimation method. This paper presents the Imm fusion algorithm of multi-platform based on the minimum unbiased input state estimation in case of the known correlated noise covariance. The simulation gives better results of this algorithm.

关 键 词：目标机动性 无偏输入估计 分布式交互式多模型融合 

分 类 号：TP212[自动化与计算机技术—检测技术与自动化装置]