双机协同纯方位目标跟踪研究

根据双机被动传感器接收到的空中目标俯仰角和方位角，利用非线性滤波算法即可估计出目标的位置和速度等运动参数。建立了双机协同对目标作纯方位跟踪的数学模型，在对EKF，UKF，PF几种代表性的非线性滤波算法进行理论分析、仿真比较的基础上，得出EKF更适合应用于双机协同纯方位目标跟踪的结论。采用EKF对四个场景进行Monte—Carlo仿真，结果表明：经过大约50S，距离误差曲线收敛于2．5km，速度误差曲线则逐渐收敛于零，该算法具有较好的稳定性和估计精度。对不同场景的仿真结果分析表明：双机分别作直线运动和蛇行机动的纯方位目标跟踪效果优于同时作直线运动，也优于同时作蛇行机动。

Research on Two Cooperative Aircraft Bearings-Only Target Tracking

The nonlinear filtering algorithm is used to estimate the position and velocity of aerial target by its angular information gained from two aircraft＇ s passive sensors. The mathematical model of the two cooperative aircraft bearings-only target tracking is found. Based on theory analysis and simulation comparing, it shows that EKF is more suitably applying to the passive tracking model among some representative nonlinear filtering algorithms （ EKF ／ UKF ／PF）. Four different scenes are presented in the Monte- Carlo simulations, the result indicates that the distance error converges to 2.5 km and the velocity error converges to zero in about 50 s, the algorithm shows good stability and estimation precision. The compare of the result indicates that the tracking effect of the two aircraft executed straight movement and snake maneuver respectively is better than that of the two aircrafts executed straight movement or snake maneuver synchronously.