"Statistics 101" for multisensor, multitarget data fusion

IEEE Aerospace and Electronic Systems Magazine

Volumn 19, Issue 1 II, 2004, Pages 53-64

  Mahler, Ronald P S ^a  

^a MS U2S26 ^*  (United States)

Author keywords

[No Author keywords available]

Indexed keywords

MATHEMATICAL MODELS; OBJECT RECOGNITION; STATISTICAL METHODS; TRACKING (POSITION);

FINITE SET STATISTICS; MULTIPLE SENSOR MULTIPLE TARGET DATA FUSION;

SENSOR DATA FUSION;

EID: 1442338380     PISSN: 08858985     EISSN: None     Source Type: Journal    
DOI: 10.1109/MAES.2004.1263231     Document Type: Article

References (33)

1. El-Fellah, A., Zajic, T., Lazja-Rooks, B., and Mehra, R. (2001) Multitarget nonlinear filtering based on spectral compression and probability hypothesis density. In I. Kadar (Ed.), Signal Processing, Sensor Fusion, and Target Recognition X, SPIE Proceedings, 4380 (2001), 207-216.
2. Ballantyne, D. J., Chan, H. Y., and Kouritzin, M. A. (2001) A branching particle-based nonlinear filter for multi-target tracking. In Proceedings of 2001 International Conference on Information Fusion, Montreal, Aug. 7-10, 2001.
3. Bar-Shalom, Y., and Li, X-R. (1993) Estimation and Tracking: Principles, Techniques, and Software. Boston: Artech House, 1993.
4. Challa, S., Vo, B-N., and Wang, X. (2002) Bayesian approaches to track existence - IPDA and random sets. In Proceedings of 5th International Conference on Information Fusion, Vol. II, (2002) 1228-1235.
5. Daley, D. J., and Vere-Jones, D. (1988) An Introduction to the Theory of Point Processes. New York: Springer-Verlag, 1988.
6. Doucet, A., de Freitas, N., and {Gordon}, N. (Eds.) (2001) Sequential Monte Carlo Methods in Practice. Springer, 2001.
7. Goodman, I. R., Mahler, R. P. S., and Nguyen, H. T. (1997) Mathematics of Data Fusion. Boston: Kluwer Academic Publishers, 1997.
8. Hoffman, J. R., Mahler, R., Ravichandran, R., Mehra, R., and Musick, S. (2003) Robust SAR ATR via set-valued classifiers: New results. In I. Radar (Ed.), Signal Processing, Sensor Fusion, and Target Recognition XII, SPIE Proceedings, 5096, 139-150.
9. Hue, C., Le Cadre, J.-P., and Peréz, P. (2002) Sequential Monte Carlo methods for multiple target tracking and data fusion. IEEE Transactions on Signal Processing, 50, 2 (2002), 309-325.
10. Lanterman, A. D. (2003) Sampling from multitarget Bayesian posteriors for random sets via jump-diffusion processes. In I. Kadar (Ed.), Signal Processing, Sensor Fusion, and Target Recognition XII, SPIE Proceedings, 5096, 300-311.
11. Lanterman, A. D., Miller, M. I., Snyder, D. L., and Miceli, W. J. (1994) Jump-diffusion processes for the automated understanding of FLIR scenes. In F. A. Sadjadi (Ed.), Automatic Target Recognition IV, SPIE Proceedings, 2234 (1994), 416-427.
12. Mahler, R. (2003) Bayesian cluster tracking using a generalized Cheeseman approach. In I. Kadar (Ed.), Signal Processing, Sensor Fusion, and Target Recognition XII, SPIE Proceedings, 5096, 334-345.
13. Mahler, R. (2002) An extended first-order Bayes filter for force aggregation. In O. Drummond (Ed.), Signal and Data Processing of Small Targets 2002, SPIE Proceedings, 4729 (2002), 196-207.
14. Mahler, R. (1998) Global posterior densities for sensor management. In M. K. Kasten and L. A. Stockum (Eds.), Acquisition, Tracking, and Pointing XII, SPIE Proceedings, 3365 (1998), 252-263.
15. Mahler, R. (2000) An Introduction to Multisource-Multitarget Statistics and Its Applications. Lockheed Martin Technical Monograph, Mar. 15, 2000.
16. Mahler, R. (2003) Multisensor-multitarget sensor management: A unified Bayesian approach. In I. Kadar (Ed.), Signal Processing, Sensor Fusion, and Target Recognition XII, SPIE Proceedings, 5096, 222-233.
17. Mahler, R. Objective functions for Bayesian control-theoretic sensor management, II: MHC-like approximation. In S. Butenko, R. Murphey, and P. Paralos (Eds.), New Developments in Cooperative Control and Optimization, Boston: Kluwer Academic Publishers, to be published.
18. Mahler, R. (2002) Random set theory for target tracking and identification. In D. L. Hall and J Llinas (Eds.), Handbook of Multisensor Data Fusion, Boca Raton, FL: CRC Press, 2002, 14-1-14-133.
19. Mahler, R. Tractable multistep sensor management via MHT. Proceedings of the Workshop on Multi-Hypothesis Tracking: A Tribute to Samuel Blackman, San Diego, CA, May 30, 2003, to be published.
20. Mahler, R., Leavitt, P., Warner, J., and Myre, R. (1999) Nonlinear filtering with really bad data. In I. Kadar (Ed.), Signal Processing, Sensor Fusion, and Target Recognition VIII, SPIE Proceedings, 3720 (1999), 59-70.
21. Mahler, R., and Zajic, T. (2002) Bulk multitarget tracking using a first-order multitarget tracking filter. In I. Kadar (Ed.), Signal Processing, Sensor Fusion, and Target Recognition XI, SPIE Proceedings, 4729 (2002), 175-186.
22. Moreland, M., and Challa, S. A multi-target tracking algorithm based on random sets. In Proceedings of 6th International Conference on Information Fusion, Cairns, Australia, July 8-11, 2003.
23. Musick, S., Kastella, K., and Mahler, R. (1998) A practical implementation of joint multitarget probabilities. In I. Kadar (Ed.), Signal Processing, Sensor Fusion, and Target Recognition VII, SPIE Proceedings, 3374 (1998), 26-37.
24. Musicki, D., Evans, R., and Stankovic, S. (1994) Integrated probabilistic data association. IEEE Transactions on Automatic Control, 39, 6 (1994), 1237-1241.
25. Naylor, J. C. and Smith, A. F. M. (1982) Application of a method for the efficient computation of posterior distributions. Applied Statistics, 31, 3 (1982).
26. Portenko, N., Salehi, H., and Skorokhod, A. (1997) On optimal filtering of multitarget tracking systems based on point processes observations. Random Operators and Stochastic Equations, 1 (1997), 1-34.
27. Sidenbladh, H. Multi-target particle filtering for the probability hypothesis density. In Proceedings of 6th International Conference on Information Fusion, Cairns Australia, July 8-11, 2003.
28. Sidenbladh, H., and Wirkander, S-L. Tracking random sets of vehicles in terrain. In Proceedings of 2003 IEEE Workshop on Multi-Object Tracking, Madison WI, June 21, 2003.
29. Sorensen, E., Brundage, T., and Mahler, R. (2001) None-of-the-above (NOTA) capability for INTELL-based NCTI. In I. Kadar (Ed.), Signal Processing, Sensor Fusion, and Target Recognition X, SPIE Proceedings, 4380 (2001), 281-287.
30. Stoyan, D., Kendall, W. S., and Meche, J. (1995) Stochastic Geometry and Its Applications, (2nd ed.). New York: Wiley, 1995.
31. van Trees, H. L. (1968) Detection, Estimation, and Modulation Theory, Part I: Detection, Estimation, and Linear Modulation Theory. New York: Wiley, 1968.
32. Vo, B., Singh, S., and Doucet, D. Sequential implementation of the PHD filter for multi-target tracking. In Proceedings of 6th International Conference on Information Fusion, Cairns, Australia, July 8-11, 2003.
33. Zajic, T., Hoffman, J., and Mahler, R. (2000) Scientific performance metrics for data fusion; new results. In I. Kadar (Ed.), Signal Processing, Sensor Fusion, and Target Recognition IX, SPIE Proceedings, 4052 (2002) 172-182.