6 papers
Exactly Optimal Quickest Change Detection of Markov Chains
Jason J. Ford, Justin M. Kennedy, Caitlin Tompkins +2
This paper establishes that an exactly optimal rule for Bayesian Quickest Change Detection (QCD) of Markov chains is a threshold test on the no change posterior. We also provide a…
Exactly Optimal Bayesian Quickest Change Detection for Hidden Markov Models
Jason J. Ford, Jasmin James, Timothy L. Molloy
This paper considers the quickest detection problem for hidden Markov models (HMMs) in a Bayesian setting. We construct an augmented HMM representation of the problem that allows t…
Below Horizon Aircraft Detection Using Deep Learning for Vision-Based Sense and Avoid
Jasmin James, Jason J. Ford, Timothy L. Molloy
Commercial operation of unmanned aerial vehicles (UAVs) would benefit from an onboard ability to sense and avoid (SAA) potential mid-air collision threats. In this paper we present…
On the Informativeness of Measurements in Shiryaev's Bayesian Quickest Change Detection
Jason J. Ford, Jasmin James, Timothy L. Molloy
This paper provides the first description of a weak practical super-martingale phenomenon that can emerge in the test statistic in Shiryaev's Bayesian quickest change detection (QC…
A Novel Technique for Rejecting Non-Aircraft Artefacts in Above Horizon Vision-Based Aircraft Detection
Jasmin James, Jason J. Ford, Timothy L. Molloy
Unmanned aerial vehicle (UAV) operations are steadily expanding into many important applications. A key technology for better enabling their commercial use is an onboard sense and…
Quickest Detection of Intermittent Signals With Application to Vision Based Aircraft Detection
Jasmin James, Jason J. Ford, Timothy L. Molloy
In this paper 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 inte…