摘要
协同导航是多自主水下航行器MAUV在执行水下任务时要解决的关键问题之一。在多AUV群体中航行器的导航精度存在差异。采用了分层式协同导航结构,分层结构中将AUV按照导航精度高低分层,同层之间导航精度相当,高精度层的AUV向低精度层的AUV传递导航信息。建立AUV的数学模型,相对距离和相对方位角的测量模型。采用扩展卡尔曼滤波融合内外部导航信息,对低精度层AUV的位置状态估计更新。对基于距离和基于方位角的协同导航定位算法分别进行仿真试验,结果表明该算法提高多AUV群中低精度层AUV的导航定位精度。
Cooperative navigation is one of the key issues to be solved when multi-autonomous underwater vehicles(MAUV) perform underwater missions. In the multiple AUV group,the navigation accuracy of the aircraft is different.This paper adopts a hierarchical cooperative navigation structure. In the hierarchical structure,the AUV is stratified according to the navigation accuracy,and the navigation accuracy is the same between the same layer. The AUV of the high-precision layer transfers the navigation information to the AUV of the low-precision layer. The mathematical model of AUV,the relative distance and the relative azimuth observation model are established. The extended Kalman filter is used to fuse the internal and external navigation information to update the position state estimation of the low-precision AUV. The simulation experiments based on distance and azimuth-based cooperative navigation algorithm are carried out respectively. The results show that the algorithm can improve the navigation accuracy of AUV in lowprecision layer of multiple AUV group.
引文
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