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Passive Localization Based on Double-Correlation Function Using Sources of Opportunity

机译:基于双相关函数的机会源被动定位

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A method based on Double-Correlation Function (DCF) using sources of opportunity is introduced for passive source localization to effectively avoid precise modelling in classical Matched Field Processing (MFP). Two times correlation has been done between sound field of a known source and that of an unknown one, which is actually a generalized data-based MFP. This method in our work is extended into the distributed network application, with a spatial gain greatly improved. Two experiments in air have been done to prove its feasibility of using data-based sound field as replica data, its robustness against complex environment and matching stability in case of various transmitted signals.
机译:引入了一种使用机会源的基于双相关函数(DCF)的方法进行被动源定位,以有效避免经典匹配场处理(MFP)中的精确建模。在已知声源的声场和未知声源的声场之间进行了两次关联,这实际上是广义的基于数据的MFP。该方法在我们的工作中被扩展到分布式网络应用中,空间增益大大提高。在空中进行了两次实验,以证明其使用基于数据的声场作为副本数据的可行性,在复杂环境下的鲁棒性以及在各种传输信号情况下的匹配稳定性。

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