Optimization study of underwater long baseline positioning trajectory

Abstract

With the economic and military development of today’s era, more and more fields have higher and higher requirements for the positioning accuracy of underwater vehicles. In order to solve the optimization of long baseline trajectory smoothing, the intersection algorithm of simplified model and the optimization algorithm based on redundant measurement-Gaussian Newton method are studied, the comparison between Kalman prediction and alpha prediction and smoothing optimization algorithm in the Ca and CV states, and the Kalman filtering, alpha filtering and interactive multi-model (IMM) filtering algorithm in the maneuvering state, simulation experiments show that the IMM algorithm smoothing effect is better, and the Kalman filter algorithm of the CV model has a small error.