惯性/地磁组合导航算法

Algorithms for inertial/geomagnetic integrated navigation

针对惯性/地磁组合导航滤波算法进行了深入研究。分析了惯性/地磁组合导航系统的基本原理,基于巡航导弹巡航段飞行过程建立了组合导航系统的滤波模型。在观测信息分别为实测地磁场三分量信息和单一幅值信息条件下,采用广义卡尔曼滤波和Unscented卡尔曼滤波算法进行了仿真分析。仿真结果表明,在观测信息为三分量地磁信息条件下,Unscented卡尔曼滤波总体滤波效果略优于广义卡尔曼滤波,两种算法在最后30s内的平均定位精度都可达到50m;在观测信息仅为地磁场幅值的情况下,广义卡尔曼滤波算法的滤波收敛速度和精度均大幅下降,而Unscented卡尔曼滤波仍然取得不错的收敛效果,滤波性能明显优于广义卡尔曼滤波。

The algorithms for inertial/geomagnetic integrated navigation were discussed. The theory of inertial/ geomagnetic navigation was analyzed. Concerning the cruise phase of cruise missile, the filter model of the integrated navigation system was established. Using scalar and vector information of geomagnetic field as observation separately, the simulations were calculated with the employment of Extended Kalman Filter（EKF） and Unscented Kalman Filter（UKF） algorithm. The results show that the effect of UKF is slightly better than that of EKF when the measurement information is the geomagnetic data of three components, and the positioning accuracy of the two algorithms could both achieve 〈50 m within the last 30 s. Taking scalar information as observation, EKF are not so much astringency and accuracy, but UKF can give a better performance.