To solve the problems of high-value sample shortage, multiple evaluation indicators, and system complexity in the performance evaluation of the Inertial Navigation System (INS), we propose a performance evaluation method for the INS based on the hierarchical Belief Rule Base (BRB). By integrating the expert knowledge and the monitoring data, the performance evaluation accuracy of the INS is significantly improved. Firstly, a hierarchical BRB model is established for the INS structure, considering the combined errors generated by the internal components of the system. Then, to reduce the influence of expert knowledge uncertainty on the evaluation accuracy of the initial model, the Projection operator-based Covariance Matrix Adaptive optimization Strategy (P-CMA-ES) is employed to construct the optimization model, where the model parameters are fine-tuned using the monitoring data. Finally, a certain type of strapdown INS is taken as an example, verifying the effectiveness of the proposed method.
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