Target location distribution model is established to describe two common situations of the submarine in on-call search,including random motion and known approximate course.Aiming at the problem that it is difficult for the Unmanned Underwater Vehicles (UUVs) to describe accurately the target motion status in on-call submarine searching,a target motion model is established based on hidden Markov Model (HMM).It can then update the probability distribution of the target in real time when the target initial probability distribution,transition probability and the detection result are known.The other problem in submarine searching is that the traditional submarine searching methods may not get the largest detection probability in limited time.A submarine searching path planning method based on improved Genetic Algorithm (GA) is designed for the UUV,which adds delete and insert operations on the basis of the traditional GA operations to guarantee connectivity of the search path.Whats more,the elite reservation operation is designed to ensure the fast convergence of the algorithm.The effectiveness of the proposed method is verified through the comparison with such common searching methods as extended position searching,patrol line searching and random searching in simulation experiments.