Sparse multi-target localization using cooperative access points

Hadi Jamali-Rad, Hamid Ramezani, Geert Leus
2012 2012 IEEE 7th Sensor Array and Multichannel Signal Processing Workshop (SAM)  
In this paper, a novel multi-target sparse localization (SL) algorithm based on compressive sampling (CS) is proposed. Different from the existing literature for target counting and localization where signal/received-signal-strength (RSS) readings at different access points (APs) are used separately, we propose to reformulate the SL problem so that we can make use of the cross-correlations of the signal readings at different APs. We analytically show that this new framework can provide a
more » ... rable amount of extra information compared to classical SL algorithms. We further highlight that in some cases this extra information converts the under-determined problem of SL into an over-determined problem for which we can use ordinary leastsquares (LS) to efficiently recover the target vector even if it is not sparse. Our simulation results illustrate that compared to classical SL this extra information leads to a considerable improvement in terms of number of localizable targets as well as localization accuracy.
doi:10.1109/sam.2012.6250509 dblp:conf/ieeesam/RadRL12 fatcat:a54ldurfafbjhos6z3kqscqbbq