针对固定单站无源定位必须实现快速和稳定定位跟踪的要求, 在传统定位方法基础上引入角度变化率和多普勒频率变化率信息; 在此基础上提出了一种基于空频域信息的不敏卡尔曼滤波(UKF)算法并结合应用背景对标准UKF算法作了改进, 详细分析了其定位性能并与扩展卡尔曼滤波(EKF)算法进行比较; 仿真结果表明UKF算法的定位性能要明显优于EKF算法, 具有更快的收敛速度和更高的收敛精度; 增加高精度的角度变化率和多普勒频率变化率信息能够显著改善定位性能。

To satisfy the requirement of high locating speed and stability to single non-moving observer, the information of angle changing rate and Doppler frequency changing rate was introduced into the location model based on traditional locating method. On which basis, an Unscented Kalman Filter(UKF) algorithm was put forward and an improvement was made to the standard UKF. The locating performance of the improved UKF was compared with that of the Extended Kalman Filter (EKF). Simulation result showed that the locating performance of the UKF was apparently better than that of EKF, which has faster convergence speed and higher convergence precision. The added information of high-accuracy angle changing rate and Doppler frequency changing rate can improve the locating performance significantly.