基于BP神经网络的雷达网抗隐身能力评估

为了评估雷达网抗隐身能力,构建了评估的指标体系,建立了雷达网抗隐身能力评估的三层BP神经网络模型,给出了训练样本构造的方法,并用构造的样本对BP神经网络进行训练。运用训练好的神经网络对雷达网抗隐身能力进行评估,结果表明,该方法能够较好地克服人为因素和模糊随机性的影响,具有较高的可行性和可信度。

Evaluation of Anti-hiding Capacity of Radar Net Based on BP Neural Networks

In order to evaluate the anti-hiding capacity of radar net,an index system for effectiveness evaluation is set up,a 3-level BP neural network is established,introduced the construction method of training samples and used these samples to train BP neural networks.When the training precision reaches the requirement,the BP neural network is used to evaluate the anti-hiding capacity of radar net.The result indicated that this method conquers the infection of subjective factors and fuzzy-randomicity,the method is feasible and reliable.