脉冲雷达探测采用多层神经网络

International 1989 Joint Conference on Neural Networks Pub Date : 1900-01-01 DOI:10.1109/IJCNN.1989.118681

H. Kwan, C. K. Lee

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引用次数: 19

摘要

介绍了一种多层前馈神经网络在脉冲雷达探测或脉冲压缩中的应用。为了说明，这里使用了巴克代码。该网络有13个输入单元、3个隐藏单元和1个输出单元。采用反向传播学习对网络进行训练。可轻松实现40 db峰值信噪比。预计处理时间比使用相关和不匹配滤波方法获得的处理时间要快得多。

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Pulse radar detection using a multi-layer neural network

The application of a multilayer feedforward neural network to pulse radar detection or pulse compression is presented. For illustration, the Barker code was used. This network has 13 input units, 3 hidden units, and 1 output unit. Backpropagation learning was used to train the network. A 40-dB peak signal-to-noise ratio can be achieved easily. The processing time is expected to be much faster than that obtained using correlation and mismatched filtering approaches.<>

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International 1989 Joint Conference on Neural Networks

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