基于交互式多模型的主被动站跟踪算法

在高斯白噪声下，使用交互式多模型算法融合主动站和被动站量测信息，在各类机动状态模型切换，完成对机动目标的定位跟踪。根据主动站到达目标然后到达被动站的距离和以及目标到达主被动站的方位角和俯仰角信息建立量测模型；在交互式多模型算法的基础上，在常规直线机动模型基础上引入Singer模型，模拟目标机动运动；以几何关系求解得到的目标位置作为目标初始解，相较于其他初始模型，算法具有更好的收敛性。仿真实验表明，在主被动站间距几十千米，目标与主被动站间距几百千米，到达角误差2°左右，到达时间误差20 m左右的情况下，使用交互式多模型算法跟踪目标，收敛误差在百米级别。

Active-passive station tracking algorithm based on interactive multi-model

Under Gaussian white noise, the interactive multi-model algorithm is used to fuse the measurement information of the active station and the passive stations, and switch between various maneuvering state models to complete the positioning and tracking of the maneuvering target. Firstly, the measurement model is established according to the distance of the active station reaching the target and then reaching the passive stations, as well as the azimuth and pitch angle information of the target reaching the active and passive stations. Then, on the basis of the interactive multi-model algorithm, the Singer model is introduced on the basis of the conventional linear maneuvering model to simulate the target maneuvering motion. Finally, the target position obtained by solving the geometric relationship is used as the target initial solution, and the algorithm has better convergence than other initial models. Simulation experiments show that if the distance between the active and passive stations is tens of kilometers, the distance between the target and the active and passive stations is hundreds of kilometers, the arrival angle error is about 2°, and the arrival time error is about 20 m, then by using the interactive multi-model algorithm to track the target, the convergence error is at the 100 m level.