基于UD迭代扩展卡尔曼滤波的纯方位机动目标定位与跟踪

摘要

Study on the traditional bearings⁃only target localization and tracking focuses on the constant velocity targets, while targets often do maneuver in real situation. So according to the bearings⁃only maneuvering target localization and track⁃ing problem, a new adaptive algorithm based on UD iterative extended Kalman filter is proposed. The algorithm which com⁃bines the UD filter with iterative extend Kalman filter improves the precision of the filter. The divergence of the filter is inhib⁃ited, and the stability of the filter is also increased. On the other hand, the detection of the normalized innovations square of the filter is used to fix the results adaptively by adjusting the system noise covariance matrix. Finally the approach is simula⁃ted and the results show the effectiveness and accuracy of the algorithm.%传统的纯方位目标定位与跟踪问题的研究，主要是基于匀速直线运动的目标，但是就实际情况而言，目标常常是机动的。因此，针对纯方位机动目标定位与跟踪问题，提出了一种基于UD迭代扩展卡尔曼滤波的自适应定位跟踪算法。该算法将UD滤波与迭代扩展卡尔曼滤波相结合，形成UD迭代扩展卡尔曼滤波，不但降低了线性化误差，提高了滤波精度，而且能够有效抑制滤波发散和增加稳定性。同时利用检测滤波器中归一化新息的平方，调整系统噪声协方差矩阵，从而实时地自适应修正滤波结果，实现对机动目标的定位与跟踪。最后对该算法进行了仿真，结果验证了提出算法的有效性和精确性。