基于隐马尔可夫模型的地磁匹配算法

为了在地磁特征微弱区域内实现地磁辅助导航以及提高惯性导航系统在地磁特征明显区域内的定位精度,提出了基于隐马尔可夫模型的地磁匹配算法.首先以惯性导航系统定位误差为隐状态,以实时测量的地磁强度为观测量,建立了地磁匹配的隐马尔可夫模型;其次,针对该模型,使用Viterbi算法来确定最优状态序列,给出了惯性导航系统的当前定位误差.仿真结果表明,该算法可以实现地磁辅助导航,导航误差优于EKF算法,组合导航系统的定位误差在50 m左右.

Geomagnetic matching algorithm based on Hidden Markov Model

In order to improve the locating precision of the inertial navigation system in regions with significant geomagnetic characteristic, and realize the geomagnetic aided navigation in regions with insignificant geomagnetic characteristic, a geomagnetic matching algorithm based on HMM (Hidden Markov Model) is proposed. Firstly, the approach took INS position error as its hidden state variable and geomagnetic value as the measurement, and an HMM model for GM(geomagnetic matching) is established. Then, with the given model, an HMMGM algorithm using Viterbi algorithm is designed and implemented to estimate the position error in INS. The simulation results show that geomagnetic aided navigation can be implemented using HMMGM. It is showed that the HMMGM algorithm can significantly improve the positioning error compared with EKF algorithm, and the positioning error of the integrated navigation system is approximately 50 m.