计算机科学 ›› 2018, Vol. 45 ›› Issue (9): 161-165.doi: 10.11896／j.issn.1002-137X.2018.09.026
杨思星, 郭艳, 李宁, 孙保明, 钱鹏
YANG Si-xing, GUO Yan, LI Ning, SUN Bao-ming, QIAN Peng
摘要： 文中提出一种基于数据融合的压缩感知多目标定位算法,该算法能够同时处理多种不同类型的定位数据。与传统算法相比,该算法以目标个数的稀疏性为基础,通过压缩感知技术来重构目标位置向量,从而大大减少了传感器的数目。算法分为数据预处理和数据融合定位两个阶段。在数据预处理阶段,将不同类型的数据转换到同一个数量级,使得各类型数据能被充分用于提高目标定位性能;在数据融合定位阶段,提出一种基于多测量向量的压缩感知重构算法来估计目标位置向量。仿真证明,相比于现有的压缩感知定位算法,所提算法具有更高的定位精度和更强的鲁棒性。
中图分类号:
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