The Research Of Underwater Target Tracking Based On Multiple Model Filtering Algorithm

With the development of science and technology, it cannot be ignored that the technology of underwater target tracking is more and more important. In this paper, a novel target tracking algorithm is proposed which is improved from filtering calculation and motion modeling. Based on the Gauss-Hermita Quadrature Filtering (GHQF) that has high accuracy, the Strong Tracking Sparse Grid Quadrature Filtering (STSGQF) is proposed and the filter’s running time is reduced greatly with the little loss of accuracy. And based on the improved algorithm, the multiple model algorithm that can describe the motion more perfect is introduced to the underwater target tracking system. In this paper, the main work are listed as follows.Firstly, the approximate nonlinear Gauss filterings such as Expended Kalman Filtering(EKF), Unscented Kalman Filtering (UKF) and GHQF are theoretically analyzed from the aspects of accuracy and efficiency. The one-dimensional and multi-dimensional nonlinear numerical experiments are used to test and verify the performance of the three filtering algorithms. The results show that the accuracy order is EKF < UKF ≤ GHQF and the running time order is EKF < UKF < GHQF.To solve the problem of "the curse of dimensionality", a new numerical integration, namely rule the Sparse Grid Quadrature (SGQ) rule, is introduced, then the Sparse Grid Quadrature Filtering (SGQF) is obtained. The calculation of SGQ is far less than GHQ in the same numerical integration. In terms of the Sigma points, the SGQF with second order is equal to the UKF. According to the simulation experiments, the SGQF’s accuracy is slightly lower than the GHQF, but the running time of the SGQF is sharply reduced.In order to overcome the problem that the estimation accuracy may decrease, and even diverges when the state suddenly changes, the Strong Tracking Filtering (STF) is introduced to the SGQF so that the STSGQF is obtained. Through the simulation experiments, the STSGQF can adapt the strong maneuvering better than the SGQF.Finally, at the aspect of the target motion model, the theory and procedure of the multiple model algorithm are highlighted, and the multiple model filtering algorithm that the STSGQF is introduced is obtained. According to the simulation example, the Interactive Multiple Model(IMM) based on the STSGQF has the higher estimation accuracy than the STSGQF and UKF based on the constant acceleration model.The main aim of this paper is to propose the STSGQF that has higher efficiency and stronger robustness. And based on it, apply the IMM algorithm to the underwater target tracking.In the end, the new algorithm achieves good results.