Alternative approaches to data compression for distributed detection
Fuat Çoğun, Steven Kay · 2016
In this paper, the distributed detection problem of linear and nonlinear signals embedded in white Gaussian noise (WGN) is considered. First, the asymptotically optimal generalized likelihood ratio test (GLRT) detector is derived for both signal models. It is found that the GLRT detector requires the submission of all observed data to the central processor which is practically infeasible. Thus, several test statistics based on compressing the observed data at each sensor are proposed. Monte Carlo simulations are carried out to plot the receiver operating characteristic (ROC) curves in order to compare the performance of the proposed detectors for a nonlinear signal example.