Abstract
The existing navigation and positioning method for underwater vehicles, which is flexible using, operates independently, and without datum reference, is very unfavorable to the efficient and convenient task implementation. The establishment of deep-sea navigation and positioning is a prerequisite for humans to rely on underwater vehicles to enter, explore, and develop the deep sea. We consider the long-term deep-sea navigation and positioning network (LT-DSNPN) built in the South China Sea to introduce the deployment and datum measurement methods. The dynamic threshold method (DTM) and correction Kalman filtering (CKF) methods are proposed to improve the detection and positioning probability based on the characteristics of the LT-DSNPN. After the sea trials, measured data and analysis results are carried out under 3 different conditions, and the performance has been analyzed and compared. The results show that DTM and CKF methods can obviously improve the detection and positioning probability to make it better than 97 %.
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