Efficient Bayesian track-before-detect

Date

2006-10-11

Author

Tekinalp, Serhat
Alatan, Abdullah Aydın

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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This paper presents a novel Bayesian recursive track-before-detect (TBD) algorithm for detection and tracking of dim targets in optical image sequences. The algorithm eliminates the need for storing past observations by recursively incorporating new data acquired through sensor to the existing information. It calculates the likelihood ratio for optimal detection and estimates target state simultaneously. The technique does not require velocity-matched filtering and hence, it is capable of detecting any target moving in any direction. The algorithm is tested with both synthetic and real video sequences, and is shown to be capable of performing sufficiently well for very low signal-to-noise ratio situations.

Subject Keywords

Target detection and tracking, Dim target detection, Track-before-detect, Recursive Bayesian estimation

URI

https://hdl.handle.net/11511/43924

DOI

https://doi.org/10.1109/icip.2006.312988

Collections

Department of Electrical and Electronics Engineering, Conference / Seminar

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Citation Formats

S. Tekinalp and A. A. Alatan, “Efficient Bayesian track-before-detect,” 2006, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/43924.