based on above performances the applications of multi-sensor data fusion in state estimation for maneuvering target is studied systemically . the main work includes : based on the analysis that the extreme value of acceleration presupposed causes influence in the “ current ” statistical model, a modified model is given, which utilizes the functional relationship between maneuvering status and estimation of the neighboring intersample position vector to carry out the self-adaptive of the process noise variance . then combining with the recursive characteristic of kalman filter, an improved self-adaptive filtering algorithm is presented 基于此,本文针对多传感器数据融合技术在机动目标状态估计中的应用进行了系统的研究,其主要工作如下:1、基于“当前”统计模型中加速度极限值的预先设定对于滤波效果影响的分析,利用目标机动状况与相邻采样时刻间位置估计量变化之间的函数关系实现噪声方差自适应,进而提出了一种修正的模型,并结合卡尔曼滤波递推算法,提出了一种改进的自适应滤波算法。