Zhang Tao, Chen Liping, Li Yao
Key Laboratory of Micro-Inertial Instrument and Advanced Navigation Technology, Ministry of Education, Southeast University, Nanjing 210096, China.
School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China.
Sensors (Basel). 2015 Dec 30;16(1):42. doi: 10.3390/s16010042.
This paper studies an underwater positioning algorithm based on the interactive assistance of a strapdown inertial navigation system (SINS) and LBL, and this algorithm mainly includes an optimal correlation algorithm with aided tracking of an SINS/Doppler velocity log (DVL)/magnetic compass pilot (MCP), a three-dimensional TDOA positioning algorithm of Taylor series expansion and a multi-sensor information fusion algorithm. The final simulation results show that compared to traditional underwater positioning algorithms, this scheme can not only directly correct accumulative errors caused by a dead reckoning algorithm, but also solves the problem of ambiguous correlation peaks caused by multipath transmission of underwater acoustic signals. The proposed method can calibrate the accumulative error of the AUV position more directly and effectively, which prolongs the underwater operating duration of the AUV.
本文研究了一种基于捷联惯性导航系统(SINS)与长基线定位系统(LBL)交互辅助的水下定位算法,该算法主要包括带SINS/多普勒速度计(DVL)/磁罗盘导航(MCP)辅助跟踪的最优相关算法、泰勒级数展开的三维到达时间差(TDOA)定位算法以及多传感器信息融合算法。最终仿真结果表明,与传统水下定位算法相比,该方案不仅能直接校正航位推算算法引起的累积误差,还解决了水下声信号多径传播导致的相关峰模糊问题。所提方法能更直接有效地校准自主水下航行器(AUV)位置的累积误差,从而延长AUV的水下作业时长。