In order to solve the problem of magnetic interference caused by airborne equipment and motion characteristics in UAV magnetic anti-submarine missions, a study based on the improved magnetic compensation model was carried out. An improved T-L magnetic compensation model based on GAN and LSTM is proposed, which combines the advantages of the traditional T-L model in attitude-dependent noise modeling, the ability of LSTM to capture the long-term interval dependence, and the learning ability of GAN to the data distribution characteristics, so as to significantly improve the accuracy of noise recognition and the measurement accuracy of magnetic data. The simulation results show that the compensation accuracy is increased by 67% and the improvement ratio is 43.67 compared with the T-L model, and the compensation accuracy is increased by 64% and the improvement ratio is 26.93 in the UAV airborne test. The results show that this method significantly improves the quality of magnetic survey data and provides accurate magnetic field for underwater anti-submarine missions based on magnetic field changes.