Extensions of the Chernoff Importance Sampling Method

Abstract

Importance sampling is a technique used to reduce the number of Monte Carlo trials needed to attain a given estimation error. Recently a technique called Chernoff importance sampling was developed which enabled greater reduction of Monte Carlos by a Chernoff-like bound. In this work we extend the results of Chernoff importance sampling to the estimation of probability of false alarm for single pulse greatest of, least of, median, and skew greatest of CA-CFAR detectors. In addition to this, we develop a Chernoff importance sampling methodology for multi-pulse CFAR detectors that do not have known analytic forms for the probability of false alarm as a function of threshold.