基于转换坐标卡尔曼滤波算法的目标跟踪

Target Tracking Based on Converted Coordinates Kalman Filtering Algorithm

在三维空间中推导转换坐标卡尔曼滤波算法。先设一传感器位于坐标原点,导出目标测量方程及三维传感器测量误差方差。再假设目标相对于传感器的斜距、俯仰角及方位角在一定位置,根据公式求得三者关系,然后将传感器对目标的测量值转换到直角坐标系,得到传感器的斜距误差、俯仰角误差和方位角误差均相互独立,均值为零。最后经转换,得到测量和真实值间的误差。仿真表明,该算法收敛迅速,精度较高,具有良好的跟踪性能。

The converted coordinate kalman filtering algorithm is inferred in 3-dimensional space. First, make an assumption that a sensor locates at the coordinate origin, then educe the target measure equation and 3-dimension sensor＇s measure error variance. Second, it supposes the range, height and azimuth that the target relative to the sensor, and gets the correlation of the three parameters, then transforms the measurements to Descartes coordinate parameter, then the three parameters＇ error variance mutual independence, and the mean is zero. Finally, it gets the error variance between the measurements and the true values. The result shows that the algorithm astringes rapidly, and has a high accuracy, the tracking performance is well.