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基于隐马尔可夫模型的OTH雷达模式识别和目标定位 被引量:1

Over horizon radar mode recognition and target localization based on hidden Markov model
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摘要 针对超视距雷达目标探测中的多模传播问题,提出了基于隐马尔可夫模型的Viterbi算法,以传播模式为状态序列,以斜距为观测序列对每一次雷达重访下的每个回波进行模式识别,并在此基础上提出了利用Bayes线性模型的方法对每次雷达重访下的目标位置进行估计。通过蒙特.卡洛模拟,结果表明该方法在不同的雷达操作频率和电离层存在扰动的情况下都具有具有很高的正确性。 Focus on the multimode propagation of the over-the-horizon radar target detection, the Viterbi algorithm based on the hidden markov model is advanced. The propagation mode is set as the state sequence, while the slant range is the observation sequence. Mode recognition is carried out at each revisit of radar. A Bayes linear model is used for estimation of target positioning at each revisit based on it. Through the Monte Carlo simulation, the method is of valid at different radar operation frequence and under the circumstance of ionospheric disturbance.
作者 周晨 赵正予
出处 《系统工程与电子技术》 EI CSCD 北大核心 2009年第2期305-309,共5页 Systems Engineering and Electronics
关键词 天波超视距雷达 隐马尔可夫过程 VITERBI算法 Bayes线性模型 over the horizon radar hidden Markov process Viterbi algorithm Bayesian linear model
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参考文献13

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同被引文献1

  • 1焦培南,朱其光.高频返回散射最小时延的地面距离变换方法[J].武汉大学学报,1985.

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