Abstract: Aiming at the problems that the inertial navigation system has interactive effects and navigation errors are difficult to identify in complex environment, a navigation error compensation method based on self-supervised long short term memory (LSTM) network intelligent combination model is proposed. The self-supervised temperature change rate module is proposed to overcome the limit of temperature sensor precision and provide temperature change rate in real time, which further improves the ability of the model to identify navigation error. In the experiment section, the effectiveness of the self-supervised module is verified through ablation experiments under various complex environment. Taking the northward velocity of flight test data as an example, the maximum absolute velocity error before compensation is 1.607 m/s, and 0.357 m/s after. Experimental results prove that the velocity and position error under complex physics environment could be effectively reduced, and the pure inertial navigation performance is therefore improved.

Key words: inertial navigation, long short term memory network, navigation error compensation, self-supervised learning