Sensor-to-sensor assistance for distributed signal detection

This paper analyzes the problem of distributed composite signal detection in a sensor-to-sensor (S2S) scenario. Based on the classical Generalized Likelihood Ratio Test (GLRT) and Bayesian approaches, some insights are provided for extending classical detection theory to cooperative environments. As a result, innovative decision rules are proposed by taking advantage of prior information from neighboring sensors (for instance, using maximum likelihood estimates of the unknown parameters). Simulation results are provided confirming the outperforming behavior of the proposed collaborative techniques.