Quickest Detection of Intermittent Signals with Application to Vision-Based Aircraft Detection

Abstract

In this brief, we consider the problem of quickly detecting changes in an intermittent signal that can (repeatedly) switch between a normal and an anomalous state. We pose this intermittent signal detection (ISD) problem as an optimal stopping problem and establish a quickest ISD rule with a threshold structure. We develop bounds to characterize the performance of our ISD rule and establish a new filter for estimating its detection delays. Finally, we examine the performance of our ISD rule in both a simulation study and an important vision-based aircraft detection application where the ISD rule demonstrates improvements in detection range and false alarm rates relative to the current state-of-the-art aircraft detection techniques.