OSA's Digital Library

Applied Optics

Applied Optics


  • Editor: Joseph N. Mait
  • Vol. 52, Iss. 12 — Apr. 20, 2013
  • pp: 2531–2545

Estimating detection and identification probabilities in maritime target acquisition

Jonathan M. Nichols, Kyle P. Judd, Colin C. Olson, James R. Waterman, and James D. Nichols  »View Author Affiliations

Applied Optics, Vol. 52, Issue 12, pp. 2531-2545 (2013)

View Full Text Article

Enhanced HTML    Acrobat PDF (1398 KB)

Browse Journals / Lookup Meetings

Browse by Journal and Year


Lookup Conference Papers

Close Browse Journals / Lookup Meetings

Article Tools



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

OCIS Codes
(110.2960) Imaging systems : Image analysis
(010.0280) Atmospheric and oceanic optics : Remote sensing and sensors

ToC Category:
Imaging Systems

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)

Sort:  Author  |  Year  |  Journal  |  Reset  


  1. R. G. Driggers, J. S. Taylor, and K. Krapels, “Probability of identification cycle criterion (N50/N90) for underwater mine target acquisition,” Opt. Eng. 46, 033201 (2007). [CrossRef]
  2. S. Moyer, J. G. Hixon, T. C. Edwards, and K. Krapels, “Probability of identification of small hand-held objects for electro-optic forward-looking infrared systems,” Opt. Eng. 45, 063201 (2006). [CrossRef]
  3. R. H. Vollmerhausen, E. Jacobs, and R. G. Driggers, “New metric for predicting target acquisition performance,” Opt. Eng. 43, 2806–2818 (2004). [CrossRef]
  4. A. M. Mood, F. A. Graybill, and D. C. Boes, Introduction to the Theory of Statistics, 3rd ed. (McGraw-Hill, 1974).
  5. J. D. O’Conner, P. O’Shea, J. E. Palmer, and D. M. Deaver, “Standard target sets for field sensor performance measurements,” Proc. SPIE 6207, 62070U (2006). [CrossRef]
  6. W. A. Link and R. J. Barker, Bayesian Inference with Ecological Examples (Academic, 2010).
  7. P. Walley, “Inferences from multinomial data: learning about a bag of marbles,” J. R. Statist. Soc. B 58, 3–57 (1996).
  8. W. L. Quirin, Probability and Statistics (Harper & Row, 1978).
  9. R. G. Driggers, P. G. Cox, J. Leachtenauer, R. Vollmerhausen, and D. A. Scribner, “Targeting and intelligence electro-optical recognition modeling: a juxtaposition of the probabilities of discrimination and the general image quality equation,” Opt. Eng. 37, 789–797 (1998). [CrossRef]
  10. V. Dhar and Z. Khan, “Comparison of modeled atmosphere-dependent range performance of long-wave and mid-wave ir iamgers,” Infrared Phys. Technol. 51, 520–527 (2008). [CrossRef]
  11. W. K. Hastings, “Monte carlo sampling methods using markov chains and their applications,” Biometrika 57, 97–109 (1970). [CrossRef]
  12. J. M. Nichols, M. Currie, F. Bucholtz, and W. A. Link, “Bayesian estimation of weak material dispersion: theory and experiment,” Opt. Express 18, 2076–2089 (2010). [CrossRef]
  13. A. N. Kolmogorov, Foundations of Probability (Chelsea, 1956).

Cited By

Alert me when this paper is cited

OSA is able to provide readers links to articles that cite this paper by participating in CrossRef's Cited-By Linking service. CrossRef includes content from more than 3000 publishers and societies. In addition to listing OSA journal articles that cite this paper, citing articles from other participating publishers will also be listed.

« Previous Article  |  Next Article »

OSA is a member of CrossRef.

CrossCheck Deposited