计算机科学 ›› 2019, Vol. 46 ›› Issue (5): 50-56.doi: 10.11896/j.issn.1002-137X.2019.05.007
李秀琴, 王天荆, 白光伟, 沈航
LI Xiu-qin, WANG Tian-jing, BAI Guang-wei, SHEN Hang
摘要: 针对传感器网络中基于接收信号强度(Received Signal Strength,RSS)的多目标定位具有天然稀疏性的问题,提出了基于压缩感知的两阶段多目标定位算法,该算法将基于网格的多目标定位问题分解为粗定位和细定位两个阶段。粗定位阶段,根据序贯压缩感知原理确定最优观测次数,然后利用lp最优化问题重构出目标所在的初始候选网格;细定位阶段,由四分法不断划分候选网格,根据最小残差原则估计目标在候选网格中的确切位置。仿真结果表明,相较于传统的基于l1最优化的多目标定位算法,基于压缩感知的两阶段多目标定位算法在目标个数未知的场景下具有更优的定位性能,且明显减少了定位时间。
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