基于BP神经网络的反潜巡逻机背景磁场补偿技术研究

Technical Research of Anti-submarine Patrol Aircraft Magnetic Compensation Based on BP Neural Network

摘要:

通过分析反潜巡逻机背景磁场模型,针对传统模型求解时对模型参数求解方法存在的不足,提出了一种基于BP神经网络的飞机背景磁场模型求解新方法；该方法不讨论复杂的模型参数估计的问题,通过前期神经网络训练学习,直接把飞机磁补偿飞行过程中采集到的相关信号输入到训练好的网络中,得到输出干扰磁场,进而对其进行补偿；最后通过实例仿真验证了该方法的正确性和有效性,为提高反潜巡逻机磁探搜潜效能提供了科学依据,具有一定的军事意义。

Abstract:

According to analyzing the magnetic interference field model of anti-submarine patrol aircraft, a new method of solving the model based on BP neural network was presented in this paper. Through the training and studying of early neural network, this method directly took the relevant information into the trained neural without regarding to complicated model parameter estimation. After the neural network outputting magnetic interference field the interference field was compensated. Simulation result proved the correctness and validity of the method which could improve the search submarine efficiency by anti-submarine patrol aircraft using magnetic detection equipment, and it could be used in military application.