一种融合USBL和INS的水下组合定位方法OA

To address the issues of low positioning accuracy and poor stability in underwater navigation,this paper proposes a combined positioning method based on an adaptive Kalman filter integrating USBL and INS.This method introduces the forgetting factor to dynamically adjust the noise covariance matrix,effectively fuses the high-frequency and high-precision short-term data from the INS and the long-term stable positioning information from the USBL,significantly improves the system's adaptability to ocean environmental changes and sensor errors.Experimental results show that,compared with USBL positioning,alone this method improves positioning accuracy by approximately 66%and demonstrates excellent robustness in complex sea conditions,provides effective technical support for highly reliable underwater navigation.