This work describes several approaches to the estimation of target detection and identification probabilities as a function of target range. A Bayesian approach to estimation is adopted, whereby the posterior probability distributions associated with these probabilities are analytically derived. The parameter posteriors are then used to develop credible intervals quantifying the degree of uncertainty in the parameter estimates. In our first approach we simply show how these credible intervals evolve as a function of range. A second approach, also following the Bayesian philosophy, attempts to directly estimate the parameterized performance curves. This second approach makes efficient use of the available data and yields a distribution of probability versus range curves. Finally, we demonstrate both approaches using experimental data collected from wide field-of-view imagers focused on maritime targets.
© 2013 Optical Society of America
Original Manuscript: November 20, 2012
Revised Manuscript: January 28, 2013
Manuscript Accepted: January 30, 2013
Published: April 11, 2013
Jonathan M. Nichols, Kyle P. Judd, Colin C. Olson, James R. Waterman, and James D. Nichols, "Estimating detection and identification probabilities in maritime target acquisition," Appl. Opt. 52, 2531-2545 (2013)