水下探测目标识别的BP网络模型的设计与实现

Design and realization of bp network model for underwater detection target recognition

船舶在海洋中航行时,需要雷达系统对航道进行实时监控,此时水下目标的自动识别就显得尤为重要,只有对水下潜在的危险目标进行实时的预测,才能保证航行的安全。因此,本文着重对水下目标的特性识别方法进行了研究,通过BP网络模型建立了能够提取水下目标特征值的算法,同时对输出层和隐含层进行优化,得到了较为理想的水下目标识别模型。仿真结果表明,通过BP网络模型对目标识别算法的优化,目标的识别率都获得了较为明显的提升。

In order to ensure the safety of navigation, it is very important to recognize the underwater targets in real time when the ship is sailing in the ocean, and the real-time monitoring of the waterway is required by the radar system.Therefore, this paper focuses on the recognition method of underwater target characteristics, through the BP network model to establish the algorithm to extract the underwater target eigenvalue, while the output layer and the hidden layer optimization, get the ideal underwater Target recognition model. The simulation results show that the target recognition algorithm is improved and the recognition rate of the target is improved obviously by the BP network model.