Particle-filter-based detection schemes

The problem of detecting whether or not a signal is present is often encountered. Several detection strategies lead to a likelihood ratio test against a threshold. In a simple setting explicit expressions for the likelihood can be obtained. However when the signal to be detected is generated by a nonlinear, non-Gaussian dynamical system it is in general impossible to obtain an expression for the probability of the signal under the hypothesis that it is present. Recently, so called particle filters have been proposed to solve nonlinear, non-Gaussian filtering problems. In this paper we show that the filtering solution obtained by a particle filter can be used to construct the likelihood ratio, needed to perform the likelihood ratio test for detection. Here we will show that different detection schemes can be used. These schemes have in common that they use the output of a particle filter for the purpose of detecting the possible presence of a target. Furthermore we will go into aspects that are of importance when actually building such a particle filter based detector.