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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 adoi:10.1109/sam.2012.6250509 dblp:conf/ieeesam/RadRL12 fatcat:a54ldurfafbjhos6z3kqscqbbq