Analysis of the cross-target measurement fusion likelihood for RSSI-based sensors

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.