基于GPS弹道测量的卡尔曼滤波参数估计算法

为提高基于GPS定位的弹道辨识方法的实时性和可靠性,提出了一种以弹道微分方程四阶龙格库塔数值积分预测作为状态量递推的卡尔曼滤波弹道参数估计算法,并针对卫星接收机有粗大误差或失效情况对方法进行了改进. 利用卫星信号模拟器和C/A码GPS接收机构建半实物仿真系统对算法进行验证,该方法的弹道参数估计误差是GPS接收机正常工作时测量误差的30%～40%;且能在GPS接收机出现异常时继续给出接近实际的估计值.

Parameters Estimation Algorithm by Kalman Filtering Based on GPS Measurement for Projectile Trajectory

In order to improve the real-time performance and reliability of trajectory identification based on GPS position, a trajectory parameters estimation algorithm by Kalman filtering is put forward, using GPS position data as observations and performing the optimal prediction by fourth Runge-Kutta numerical integration for solving projectile trajectory nonlinear differential equation. Improvement method is taken into account in case of failure or gross error of GPS receiver. Semi-physical simulation is used by Spirent GPS satellite signal simulator and C/A code receiver. The results show that the error of trajectory parameters estimation is approximately 30 percent to 40 percent of GPS raw measurement when the receiver works properly. Further, trajectory parameters estimation could be close to true value even if GPS receiver is abnormal.