Distributed cancellation-based multiple-source localization for wireless sensor networks

A low-complexity technique for multiple-source localization by wireless sensor networks is presented. The proposed technique is based on the Received Signal Strength (RSS) measurements of signals emitted by the sources. Also, all processing is performed at the sensor nodes in a decentralized fashion, and hence no “Fusion Center” is required. The proposed cancellation-based multiple-source localization (CBMSL) technique relies upon a proper iterative application of a new dominant-source localization (DSL) algorithm. More specifically, in the initial stage, the DSL estimates the location and power of the dominant source within the area of the network. Once the parameters of the dominant source have been estimated, they are broadcast to the network. Nodes receiving this message adjust their measurements by cancelling appropriately the components due to the dominant source. This cancellation implies that another source becomes the dominant one in the area of the sensor network. Based on the adjusted measurements, the dominant-source localization algorithm can be executed once again, to estimate the next dominant source, and so forth. Thus the above “successive cancellation” procedure can be used to estimate all sources in the network area. Efficient algorithms for all the above steps have been derived. Extensive simulation results have shown that the proposed technique could be a promising alternative for the problem at hand.