一种适应较大INS速度误差的地形辅助导航算法

A Novel Terrain Aided Navigation Algorithm Adaptive for Large Velocity Error of INS

地形辅助导航是飞行器实现自主导航定位的重要方式之一。传统的地形辅助导航算法在匹配过程中,一般对惯性系统的速度误差范围有较严格要求,当速度误差过大时匹配正确概率会迅速下降。提出了一种新的基于短链修正的概率数据关联地形辅助导航算法,首先,依据短时间内由速度误差积累的航位漂移较小的特性,通过附近短链的关联滤波结果修正长链上的节点;其次,设计了通过匹配链后验概率构造关联概率的方法。该方法能较好地处理INS速度误差较大的情况,仿真结果表明该算法的正确匹配率,均方根误差和圆概率误差均优于TERCOM算法和直接基于概率数据关联的地形辅助导航算法。

Terrain aided navigation （TAN） is one of the important methods for autonomous navigation system of aircraft. Conventional TAN algorithms do not generally perform well when the velocity error of INS is considerably large. Therefore, a new Probabilistic Data Association Filter （PDAF） based TAN algorithm is proposed in this paper to cope with that gruesome situation. In the sketched method, contribution mainly consists of two respects, firstly, nodes in matching chains are upgraded by the PDAF results of neighboring shorter chains ; secondly, association probabilities of matching chains are constructed from the posterior probabilities. Simulations demonstrate that our method is preferable to TERCOM and one existing PDAF based method.