仅依赖连通度的压缩感知多目标定位方法

doi:10.11959/j.issn.1000-436x.2016103

Abstract

Abstract:

A multiple targets localization method was proposed from mere connectivity,and the multiple targets posi-tioning problem was converted to sparse vector resolving by compressive sensing theory,which was applied to the indoor localization of intensive references distribution.The connectivity to the references was collected as the only measurement data,and targets locations were figured out by minimum l₁-norm algorithm.When measurement data was compressed tol 1 bit,the fixed point iteration algorithm combined with semi-definite relax was proposed to figure out targets locations.As for the simulation results,compared with MDS-MAP,DV-Hop and RSS-CS algorithms,the average location error is less than 1 grid by the mere connectivity of N -bit and 1-bit quantization CS localization,of which the occupied bit quan-tity are reduced to less than 4 times and 16 times of RSS localization observation value respectively.

Key words: multiple targets localization, compressive sensing, connectivity, 1-bit quantization

Lei LIU,Jian-jun ZHANG,Yang LU,Xing WEI,Jiang-hong HAN. Multiple targets localization via compressive sensing from mere connectivity[J]. Journal on Communications, 2016, 37(5): 152-164.

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References 18

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