A NEURAL NETWORK APPROACH TO PULSE RADAR DETECTION

被引：29

作者：

KWAN, HK

LEE, CK

机构：

[1] Dept. of Electrical Engineering, University of Windsor, Windsor, Ontario, N9B3P4

[2] Technical Operations, Motorola Semiconductors Hong Kong Ltd., Silicon Harbour Center, Tai Po, N.T., 2 Dai King Street, Taipo Industrial Estate

来源：

IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS | 1993年 / 29卷 / 01期

基金：

加拿大自然科学与工程研究理事会;

关键词：

D O I：

10.1109/7.249109

中图分类号：

V [航空、航天];

学科分类号：

08 ; 0825 ;

摘要：

A new approach using a multilayer feedforward neural network to pulse compression is presented. The 13-element Barker code and the maximum-length sequences (m-sequences) with lengths 15, 31, and 63 bits were used as the signal codes, and four networks were implemented, respectively. In each of these networks, the number of input units was the same as the signal length while the number of hidden units was three and the number of output unit was one. In training each of these networks, the backpropagation learning was used and the number of training epochs was 500. Using this approach, a more than 40 dB output peak signal-to-sidelobe ratio can be achieved. Moreover, these fault-tolerant neural networks can provide a robust means for pulse radar detection.

引用

页码：9 / 21

页数：13