Underwater Target Tracking in Three Dimensional Space Based on Sound Speed Profile

At present, due to inaccurate models of environmental noise and lack of prior knowledge. most tracking algorithms are non-iterative. Moreover, most underwater tracking algorithms do not consider the influence of sound velocity on ray trajectory. As a result, many algorithms are ineffective in a real underwater environment. In order to solve the above problems, we use measured data and consider the special underwater environment characteristics to build a sound propagation model. Through this model, time of flight (ToF), and traveling distance of sound can be calculated. Then, in order to combine the advantages of iterative and non-iterative algorithms, we propose an improved underwater tracking algorithm. A minimum residual localization algorithm based on particle swarm optimization. which is a non-iterative algorithm, is modified to adapt to the underwater environment. In the end, a data fitting strategy is adopted to convert the non-iterative algorithm into an iterative one without knowledge of environmental noise. Hence, the historical information can be used to improve the accuracy of the non-iterative algorithm significantly. Simulations show that our method possesses the merit of higher precision and broader adaptability in comparison with other techniques.