Array Optimization of Multistatic Sonar Buoy Sensors and Its Application in Submarine Search

With the increasing threat of submarines to maritime security, the importance of anti-submarine warfare has also increased. Research on using multistatic sonar buoy sensors to search the submarine helps to increase anti-submarine efficiency and reduce costs. To solve the array optimization problem of multistatic sonar buoy sensors for submarine search, an optimization algorithm based on an improved gray wolf optimizer (IGWO) is proposed. First, the detection ranges of the bistatic sonar system are evaluated according to its working principle. Second, the search efficiency model of the multistatic sonar buoy sensor array is established. Furthermore, an array optimization model of multistatic sonar buoy sensors based on an IGWO is established to maximize the search efficiency and minimize the delivery amount of active and passive sonar buoy sensors, respectively. The global search capability of the method is enhanced by introducing a chaotic search strategy, bubble predation strategy, and intergroup crossover strategy. Finally, the experimental results show that the IGWO has certain feasibility and effectiveness. Under the limited total delivery amount of sensors, the maximum search efficiency obtained by the proposed method is 0.8456, compared with four other methods, the maximum lift rate is 13.3%. Meanwhile, compared with the active sonar buoy sensor array, the multistatic sonar buoy sensor array can greatly reduce the cost. At the same time, the max increase rate of search efficiency is 21.07%, and the average increase rate of search efficiency is 6.84%.