Method of on-call submarine searching for surface ship formation based on hidden Markov model

  Objectives  In order to improve the successful probability of searching for target submarines and to make the operation of the surface ship formation more effectively, the problem about the path planning for the on-call submarine searching for ships is studied.

  Methods  Firstly, an on-call submarine searching model of surface ships was constructed based on the Hidden Markov Model(HMM). A two-stage heuristic method was designed to maximize the probability of searching for submarine search expectation. The problem of local optimum was avoided by using evolutionary algorithm(EA)to cross and mutate the individuals in the population, and a comparison with conventional searching methods was made. Then, the effects of different segmentation methods on path optimization were studied experimentally.

  Results  The simulation results of single-ship and multi-ship searching for submarines show that the method adopted in this paper can obtain the maximum submarine search expectation and the optimal searching path. The segmentation times experiment show that a reasonable re-division of the search area is beneficial to find a better searching path.

  Conclusions  This model can find an optimal path for submarine search and improve the searching efficiency of the surface ship formation.