支持无线传感器网络多目标跟踪的最邻近数据关联算法研究

摘要

Multi-source data association is one of the key technologies of multi-sensor data fusion in wireless sensor network.The joint probability data association algorithm is a data association algorithm of Multi-target tracking, it doesn't need any priori information about targets and clutters, but its computer expense is very large compared with the other related data association algorithms.The joint probability data association algorithm based on the nearest neighbor method integrates the ideology of nearest neighbor data association in the process of the construction of effective matrix, then selects three valid measurements which have the least statistical distance to construct the effective matrix.This method simplifies the effective matrix, thus reduces the computation of original algorithm.%多源数据关联问题是无线传感器网络中多传感器数据融合的关键技术之一.联合概率数据关联算法是一种跟踪多目标的数据关联算法,它不需要任何关于目标和杂波的先验信息,但与其他有关数据关联算法相比,计算机开销大.在构造有效矩阵的过程中基于最邻近方法的联合概率数据关联算法,结合最邻近数据关联算法的思想,选取统计距离最小的3个有效量测构成有效矩阵,从而简化了有效矩阵,减少了原有算法的计算量.