Aiming at the problem of mission planning in the field of satellite application, a mission planning model for multi-type imaging satellites is constructed, and a hybrid immune genetic algorithm (HIGA) is proposed to solve the model. An encoding and decoding strategy is designed according to the characteristics of multi-type imaging satellite task planning, an adaptive mechanism and a tabu search idea are introduced, and a selection strategy based on antibody concentration and fitness and a new vaccination operation are defined. The simulation results show that the proposed algorithm can solve the problem of multi-type satellite mission planning, and effectively improve the problems of immune genetic algorithm, such as premature convergence and falling into local optimum. Compared with the comparative algorithm, the proposed algorithm can achieve faster convergence speed and better planning results, and can also achieve better planning results when planning large-scale missions.