水下舰艇通信网络中的故障数据挖掘方法仿真

发布时间：2018-01-19 04:05

本文关键词： 海洋混响舰艇通信网络故障数据挖掘　出处：《微电子学与计算机》2016年02期 　论文类型：期刊论文

【摘要】：在水下通信中,海洋混响将对舰艇通信网络产生破坏性干扰,导致通信网络故障和通信信道失衡,传统方法采用相邻数据段匹配滤波方法进行故障数据挖掘,识别性能不好.对提出基于分段预白化匹配检测的水下舰艇通信网络中的故障数据挖掘算法.构建了水下通信信道模型,通过分段预白化处理,把故障数据信号解析模型分解为多个窄带信号,对故障数据进行匹配检测,求得通信网络中的干扰特征幅度和相位信息,用AR模型估计不同时刻的混响频谱,对当前数据段进行平滑处理,对每段故障数据型进行分段匹配滤波检测,对当前数据段的处理结果与前一数据段的处理结果进行分段预白化匹配相关检测,实现故障数据有效识别.仿真结果表明,采用该算法能有效提高故障数据准确识别率,通过合理配置分段预白化匹配参数,提高水下舰艇通信网络中的故障数据的准确检测概率,改善了舰艇对潜水下通信的质量.
[Abstract]:In underwater communication, ocean reverberation will cause destructive interference to warship communication network, resulting in communication network fault and communication channel imbalance. Traditional methods use adjacent data segment matching filtering method for fault data mining. The recognition performance is not good. The fault data mining algorithm in underwater ship communication network based on segmented prewhitening matching detection is proposed. The underwater communication channel model is constructed and processed by subsection prewhitening. The analytical model of fault data signal is decomposed into several narrowband signals, and the fault data is matched and detected, and the characteristic amplitude and phase information of interference are obtained, and the reverberation spectrum at different times is estimated by AR model. The current data segment is smoothed, each segment fault data type is detected by segmented matched filtering, and the processing result of the current data segment and the processing result of the previous data segment are detected by segment prewhitening matching correlation detection. The simulation results show that the algorithm can effectively improve the accurate recognition rate of fault data, and the matching parameters can be reasonably configured by segment whitening. The accuracy detection probability of fault data in underwater ship communication network is improved, and the quality of ship communication under diving is improved.
【作者单位】：浙江警官职业学院;
【分类号】：U674.70
【正文快照】： 1引言在水下舰艇通信网络中,海洋的声传播损失会导致海洋混响产生强烈的干扰,且海洋混响具有时变性和非平稳性,所以海洋混响将对舰艇的水下通信网络产生破坏作用,导致故障发生.研究水下舰艇通信网络中的故障数据挖掘方法,可以提高水面舰艇对潜通信的稳定性和可靠性,相关的算法

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