基于Sigma粒子Kalman滤波的地形辅助导航方法

地形辅助导航技术依据机载设备实时测量地形高度与机载数字高程地图的对比,给出飞行器定位结果,能够有效地修正主惯性导航系统的误差。传统地形辅助导航中应用较为广泛的是扩展Kalman滤波方法,但因为地形高度测量的非线性,扩展Kalman滤波不一定能够得到系统最优估计。Sigma粒子Kalman滤波作为一种新面世的非线性滤波器,能够有效地解决非线性估计问题。基于Sigma粒子Kalman滤波,提出一种新的地形辅助导航方法。在真实数字高程地图上得到的仿真结果表明,该地形辅助导航方法性能总体优于扩展Kalman滤波方法,尤其在飞越平坦地形时表现更佳。

A Better Terrain Aided Navigation Method Based on Sigma-Point Kalman Filters

At present the relatively widely used terrain aided navigation(TAN) method is based on extended Kalman filter(EKF).We now present a new and better TAN method based on Sigma-point Kalman filters(SPKFs).In the full paper,we explain our TAN method in some detail;in this abstract,we just add some pertinent remarks to listing the three topics of explanation.The first topic is: the principles of the TAN.In this topic,we derive the input of the TAN measurement equation as shown in eq.(4) in the full paper.The second topic is: EKF.In this topic,we point out that EKF cannot guarantee the optimal estimation because terrain height measurement is nonlinear.The third topic is: SPKFs.In this topic,we calculate the Sigma points and use the points to calculate the mean and covariance of a state vector of the TAN system,as summarized in eqs.(32) and(33).Thus,SPKFs solve the nonlinearity and their solution is furnished to the TAN system.Finally we simulate our TAN method using real digital elevation map.The simulation results,given in Figs.4 and 5,show preliminarily that our TAN method reduces average circular error probability(CEP) to 22.10 m while the EKF method has the average CEP of 24.39 m,thus providing better accuracy for the TAN system,especially when the terrain is flat.