基于自适应差分进化和BP网络的罗盘误差补偿

Compass Error Compensation Based on Adaptive Differential Evolution and BP Network

To improve the acuuracy of heading angle measured by electronic compass, a new error compensation method is proposed based on adaptive differential evolution algorithm and BP neural network. In the method, the 3 layer BP neural network is used to model heading angle error, and adaptive differential evolution algorithm is adopted to train the weights of network, thus obtaining a more exact error model, and compensating the heading angle error measured by electronic compass. Compared with other compensation methods such as 8 position least squares, BP neural network, differential evolution algorithm for optimizing BP neural network, and so on, its error compensation accuracy is significantly improved, the method has strong global optimization ability, great convergence rate, good stability, and so on. The experimental results show that after compensation, the error range of heading angle is decreased from -16°~30.7° to -0.22° ~0.2°, which satisfies the needs of higher accuracy navigation systems.