基于协方差拟合的离格气体泄漏源定位方法  

DOA Method of Off-Grid Gas Leakage Source Based on Covariance Fitting

作　　者：李鹏[1,2,3] 单钰强 LI Peng;SHAN Yuqiang(Jiangsu Key Laboratory of Meteorological Observation and Information Processing,Nanjing University of Information Science and Technology,Nanjing Jiangsu 210044,China;School of Automation,Binjiang College,Nanjing University of Information Science and Technology,Wuxi Jiangsu 214105,China;Jiangsu Meteorological Sensor Network Technology Engineering Center,Nanjing University of Information Science and Technology,Nanjing Jiangsu 210044,China)

机构地区：[1]南京信息工程大学,江苏省气象探测与信息处理重点实验室,江苏南京210044 [2]南京信息工程大学滨江学院自动化学院,江苏无锡214105 [3]南京信息工程大学,江苏省气象传感网技术工程中心,江苏南京210044

出　　处：《电子器件》2023年第2期478-484,共7页Chinese Journal of Electron Devices

基　　金：国家自然科学基金项目(41075115);江苏省重点研发计划社会发展项目(BE2015692);无锡市社会发展科技示范工程项目(N20191008)。

摘　　要：针对网格划分类算法导致的量化误差影响估计性能以及相干信源下难以准确定位的问题,提出了一种基于协方差拟合的离格气体泄漏源定位方法。利用协方差拟合准则重构出泄漏源在相干信号下的协方差矩阵,使其恢复Toeplitz特性,引入以L_(2)范数作为约束条件的离格模型,将恢复出的协方差矩阵与离格模型进行联合估计。最后利用泄压阀模拟气体管道泄漏的发生,对比低信噪比及相干信源下的仿真结果。实验分析表明:该方法虽然对快拍数依赖稍显敏感但是弥补了相干信源下传统稀疏恢复类算法的失效问题,同时在低信噪比情况下依然能够准确进行角度估计,为复杂环境下的气体泄漏监测提供了新的思路。Aiming at the problems of the quantization errors caused by grid partitioning class algorithms affecting estimation performance and the difficulty of accurate localization under coherent sources,an off-grid gas leak source localization method based on covariance fit-ting is proposed.Firstly,the full rank covariance matrix of the leakage source under the coherent signal is reconstructed using the covar-iance fitting criterion to recover the Toeplitz characteristic.Then the off-grid model with L_(2) norm as constraint is introduced,and the re-covered covariance matrix is estimated jointly with the off-grid model.Finally,the occurrence of gas pipeline leakage is simulated using a pressure relief valve to compare the simulation results under low SNR and coherent sources.The experimental analysis shows that the method is slightly sensitive to the dependence on the number of snapshots but compensates for the failure of traditional sparse recovery class algorithms under coherent sources,and it can still make accurate angle estimation under low SNR,which provides a new idea for gas leakage monitoring under complex environment.

关 键 词：离格 稀疏重构 协方差拟合 相干信源 波达方向(DOA)估计 

分 类 号：TM933[电气工程—电力电子与电力传动]