目标对载机准确定位数据融合算法的研究

A Study on Data Fusion in the Positioning of Targets

基于Kalman滤波的数据融合理论,建立了目标对载机准确定位的物理模型和极坐标下的数学模型,研究在机载光电跟踪系统中,红外传感器和传统的雷达传感器测量信息的数据融合。进行了观测值加权融合算法、观测状态向量合并和状态估计融合反馈3 种算法的分析比较,以方位角融合为例进行仿真实验,并采用了协方差分析,结果表明,观测值融合算法的性能优于其它算法。

Based on Kalman’s filter theories of data fusion, the maneuvering and mathematical models in the polar coordinate for accurate target positioning are studied. Besides, studies are made on the algorisms and applications of data fusion in the measurements (range and position) of IR sensors and radar sensor in the airborne E-O system. Three different methods are compared, the track-to-track fusion algorithm is taken as an example for simulated experiment and the covariance is analyzed. Results show that the measurement fusion model is better than other methods.