Abstract: Based on the forward-looking sonar image sequences, the particle filtering (PF) optimized by the immune algorithm for underwater target tracking is studied and implemented. After the sonar image is segmented into binary image, the area shape features of the target are extracted to construct the observation model, and the adaptive updating method of the target template is designed. The clone and mutation ideas of the immune algorithm are introduced into particle filtering to solve the problem of particle degradation. The tracking experiments for two groups of underwater moving objects show that even if the target has certain deformation and interference, the immune particle filtering algorithm in this paper can still track the real trajectory with high precision and compared to the traditional particle filtering algorithm, the stability is also stronger.