| 减少防撞雷达虚假目标的信号处理研究 |
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| 引用本文： | 孙艳敏,周长林,常青美,高辉.减少防撞雷达虚假目标的信号处理研究[J].微型机与应用,2011,30(18):46-48,51. |
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| 作者姓名： | 孙艳敏 周长林 常青美 高辉 |
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| 作者单位： | 解放军信息工程大学理学院,河南郑州,450001 |
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| 摘 要： | 从信号处理的角度分析了防撞雷达虚报警率、漏报警率偏高的原因,采用AR模型功率谱估计的Burg算法代替传统的FFT算法,并将粗神经网络应用于防撞雷达目标识别。仿真结果表明,此方法提高了雷达信号处理的准确度和目标识别率,能有效地降低漏报警、虚报警率。
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| 关 键 词： | 防撞雷达 虚假目标 功率谱估计 粗神经网络 |
Signal processing study on reducing false targets for anti-collision radar |
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| Sun Yanmin,Zhou Changlin,Chang Qingmei,Gao Hui.Signal processing study on reducing false targets for anti-collision radar[J].Microcomputer & its Applications,2011,30(18):46-48,51. |
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| Authors: | Sun Yanmin Zhou Changlin Chang Qingmei Gao Hui |
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| Affiliation: | Sun Yanmin,Zhou Changlin,Chang Qingmei,Gao Hui(Institute of Science,Information Engineering University,Zhengzhou 450001,China) |
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| Abstract: | This article analyzes the reasons for the high rate of leakage alarm and false alarm of the anti-collision radar from the point of the signal processing, using the Burg algorithm of AR models power spectrum estimation instead of the traditional FIT algorithm, and use the rough neural network for anti-collision radar target identification. Simulation results show that this method improves the accuracy of radar signal processing and target recognition rate, which can effectively reduce the leakage alarm and false alarm rate. |
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| Keywords: | anti-collision radar false target power spectrum estimation rough neural network |
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