In the aquatic plants cleaning process of crab culture, in order to reduce labor intensity of the farmers and improve the positioning accuracy of navigation, a kind of DGPS and vision integrated navigation positioning method was designed with immune particle swarm optimization (IPSO) to optimize the trace of Kalman filter, which combined the advantages of DGPS and visual navigation, and was applied to aquatic plants cleaning workboat. Firstly, the integrated navigation model was established, and then the state equation and observation equation of the system were obtained. In order to solve the divergence problem of UKF filtering for navigation model, PSO was used to obtain new particles, and immune algorithm was introduced to avoid premature phenomenon of PSO. Combining with UKF, the navigation model was filtered, and the new position coordinates were obtained. At last, the comparative experiment was conducted by simulation and navigation experiment. Simulation experiment results showed that the root mean square error (RMSE) at east and north positions of the proposed method were reduced by 46.09% and 71.51% compared with DGPS navigation, and reduced by 23.92% and 58.26% compared with integrated navigation, respectively. Navigation experiment results showed that in the same longitude position the latitude error of proposed method was reduced by 22.69% and 9.14% compared with DGPS and integrated navigation, respectively. The results showed that the navigation time of the proposed method was reduced by 4.77% and 4.32% compared with DGPS and integrated navigation, respectively.