Analysis of the cross-target measurement fusion likelihood for RSSI-based sensors
Jonathan P. Beaudeau, Mónica F. Bugallo, Petar M. Djurić · 2014
In this paper an analysis is conducted regarding the likelihood function of an RSSI-based sensor measurement that is affected by a target of interest (TOI) and an interfering target source. The interferer's true location is unknown but is assumed to be Gaussian distributed with known parameters. This analysis is motivated by its potential application within a multi-agent distributed tracking system, where each agent is tasked with tracking a single TOI while treating others as sources of interference. By exchanging TOI information, each agent can use the results established here to effectively compensate for “out-of-scope” target interference by fusing this external information. An exact analytical form is established for the aforementioned likelihood and a Gaussian approximation is analytically developed. An application of these results is presented through an example scenario, with computer simulation results demonstrating performance.