机载红外搜索跟踪系统被动定位滤波算法研究

首先用扩展卡尔曼滤波算法构建了机载红外搜索跟踪系统被动定位滤波模型．然后针对该滤波算法要求先验的噪声统计及存在系统观测模型线性化误差影响滤波精度的特点．利用虚拟噪声技术，提出了适合于红外搜索跟踪系统被动定位的自适应扩展卡尔曼滤波算法。该算法实时地估计了虚拟噪声的统计特性，减小了线性化误差，提高了非线性滤波的精度。仿真结果表明，在完全相同的初始条件下，自适应扩展卡尔曼滤波对目标距离和速度的估计结果明显优于扩展卡尔曼滤波，此算法具有很高的工程应用价值。

Filter algorithm of passive location by IRSTS

First building the filter algorithm model of passive location by IRSTS by means of extended kalman filter, then aiming at the speciality of transcendental noise statistics and linearization error of measurement model effecting on filter precision during the study of extended kalman filter, adaptive extended kalman filter algorithm for passive location by IRSTS by means of subjuctive noise technique is advanced. It improved on extended kalman filter algorithm and approximated subjuctive noise statistics. The algorithm degraded linearization error and enhanced the nonlinear filter precision. The simulation experimental results show the advantage of adaptive extended kaiman filter algorithm under the same condition, the algorithm supplied practical value of engineering.