Low Complexity Short Baseline Localization Algorithm Based on Taylor Expansion

Traditional short baseline positioning algorithm suffers from low positioning accuracy and exhaustive search algorithm has high complexity. This paper addresses the problem by introducing a low complexity underwater acoustic short baseline positioning algorithm. First, the positioning principle of short baseline system is studied. After that ingredients that affect estimate accuracy are analyzed, and then the modified algorithm is proposed: based on the exhaustive idea, the performance evaluation function is established first; then it is simplified by Taylor expansion formula; finally, the estimated position is achieved by minimizing it. In the proposed algorithm, linear operations such as multiplication and addition are used instead of square root calculation, thus it can reduce the computational complexity. Furthermore, fixed-point calculation can be realized using the ranging information between the underwater autonomous vehicle (AUV) and the beacon. Simulation results show the effectiveness of the proposed algorithm.