无线声传感器网络中多目标检测与定位算法

Jaechan Lim, Jinseok Lee, Sangjin Hong
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引用次数: 0

摘要

在大多数基于联合概率数据关联(JPDA)的多目标跟踪方法中,目标数量变化很大的问题(由于高度复杂性的维数限制)难以应用该方法。本文介绍了一种无线声传感器网络(ADMAN)中多目标检测算法;我们在ADMAN之后通过粒子滤波对检测目标进行定位。ADMAN的目的是在感兴趣的领域检测任意数量的目标(在检测算法中我们知道目标的大致位置)。ADMAN的优点是能够及时地处理不同数量的目标。ADMAN对目标号码的变化模式没有任何限制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Algorithm for Detection and Localization of Multi-targets in Wireless Acoustic Sensor Networks
In most multitarget tracking approaches based on joint probabilistic data association (JPDA), it is difficult to apply the solutions to problems (due to the dimensionality curse of heavy complexity) where the number of targets varies dramatically. In this paper, we introduce an algorithm for detection of multitargets in wireless acoustic sensor networks (ADMAN); we localize detected targets by the particle filtering after the ADMAN. The purpose of ADMAN is detecting any number of targets (We know the approximate locations of targets during the detection algorithm.) in the field of interest. The advantage of ADMAN is its ability to cope with varying number of targets in time. ADMAN does not have any restrictions on the varying pattern of the target number.
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