Abstract: In order to solve the problems of missing optimization theory, simple distribution of sensor array and single mode of detecting object motion in existing sensor array placement optimization of underwater vehicle, a sensor array for detecting the position of two different moving objects was optimized based on the sequential heuristic sensor layout method of Bayesian probability model. Combining the relative entropy and sequence heuristic algorithm to construct the objective function, and using the correlation coefficient to design the evaluation function, the theoretical model of artificial lateral line sensor array optimization is constructed. The flow field simulation database of various moving objects is constructed by flow field simulation. The probability of the flow field simulation data of different moving objects is used to characterize the accuracy of different arrays in detecting the location of objects. The detection accuracy of the optimized array is evaluated by designing the experimental system of underwater artificial lateral line optimization array. The simulation results show that compared with the traditional uniform array and the empirical array, the optimized array has an average detection probability of 50.78% and 29.69% higher for the position of the horizontal and vertical vibrating dipole target, respectively. The experimental results show that compared with uniform array and empirical array, the optimized array has an average detection probability of 53.37% and 9.80% higher for the position of the horizontal and vertical vibrating dipole target, respectively, which effectively improves the detection accuracy of multi-moving objects.

Key words: underwater vehicle, artificial lateral line, horizontal/vertical vibration target detection array optimization, bayesian probability model