Abstract: The disclosure discloses a trajectory optimization method and device for accurately deploying marine sensors under water. The method includes the following steps. 1. Randomly select N sets of initial control variables within a range. 2. Input all of N sets of xi to the sensor's underwater glide kinematics and dynamics models, and calculate the smallest distance between N actual deployment positions and target deployment positions. 3. Determine whether the number of iterative operations is less than the preset value, if yes, perform global random walk and local random walk on N sets of xi, obtain N sets of xi again, and return to step 2; otherwise, go to step 4. 4. Output the control variable xi corresponding to ?s(x)nminmin and the corresponding trajectory as the optimal control variable and optimal trajectory. The disclosure can improve the accuracy of prediction on the underwater three-dimensional trajectory of the marine sensor.

Abstract: The disclosure discloses a trajectory optimization method and device for accurately deploying marine sensors under water. The method includes the following steps. 1. Randomly select N sets of initial control variables within a range. 2. Input all of N sets of xi to the sensor's underwater glide kinematics and dynamics models, and calculate the smallest distance between N actual deployment positions and target deployment positions. 3. Determine whether the number of iterative operations is less than the preset value, if yes, perform global random walk and local random walk on N sets of xi, obtain N sets of xi again, and return to step 2; otherwise, go to step 4. 4. Output the control variable xi corresponding to ?s(x)nminmin and the corresponding trajectory as the optimal control variable and optimal trajectory. The disclosure can improve the accuracy of prediction on the underwater three-dimensional trajectory of the marine sensor.