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Source localization using widely separated special microphone arrays: study of the applicability of higher order statistics

机译:利用广泛分离的特殊麦克风阵列的源本地化:研究高阶统计的适用性

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This paper presents an application implying higher order statistics in source localization. Such techniques have been first introduced in the early 1990抯. Some interesting properties of higher order statistics are exploited in zone survey applications. A large global array constituted by a set of moving sub-arrays (soldiers wearing a Head Equipment (HE) equipped with one or more microphones, a GPS receiver and a magnetometer) allows the localization of the menaces near a survey zone. Studying a large global array, with second order statistics high resolution localization techniques, the local informations are not significant enough in order to have an influence on the estimation of the position of the acoustic sources (for instance, the orientation of the HE has no influence on the estimation of the position of the sources). We expect that the use of higher order statistics and their properties concerning especially the virtual equivalent network (VEN) will improve the significance of these local information and thus, allow to have a better estimation of the source position. A first study has been based on simulations, and then, some results with real data, collected in october 2003, are presented.
机译:本文介绍了一个应用于源本地化的更高阶统计的应用程序。这些技术已在1990年代初推出。在区域调查应用中利用了更高阶统计的一些有趣的特性。由一组移动子阵列构成的大型全局阵列(戴着头部设备(HE)的士兵配备有一个或多个麦克风,GPS接收器和磁力计)允许在调查区附近定位威胁。研究一个大型全局阵列,具有二阶统计高分辨率本地化技术,本地信息不够重要,以便对声源的位置估计有影响(例如,他没有影响的方向关于估算来源的位置)。我们预计使用更高阶统计及其尤其是虚拟等效网络(Ven)的性质将提高这些本地信息的重要性,从而提高源位置更好地估计源位置。第一项研究一直基于模拟,然后,展示了2003年10月收集的实际数据的一些结果。

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