A novel infrared object detection method based on the generalized cumulative sum in IRST system

Aiming at the infrared object detection applications, a novel generalized cumulative sum processing is presented. Since in a typical IRST application system, object appearing and vanishing can be regarded as the change-point detection problem in Statistics. One of the effective solutions is the generalized cumulative sum processing (GCUSUM). Analyses are focused on the detection threshold value selection of GCUSUM algorithm and relations among the threshold value and false alarm rate, detection probability and signal-noise rate. The further researches extend a uniform band IRST system into the multiple band IRST system and improve the realization of GCUSUM algorithm. Results of theoretical analysis and simulation show that our modified algorithm has excellent object detection performance in an infrared image sequences from a real IRST system.

[1]  R.M. Gagliardi,et al.  Application of Three-Dimensional Filtering to Moving Target Detection , 1983, IEEE Transactions on Aerospace and Electronic Systems.

[2]  Yair Barniv,et al.  Dynamic Programming Solution for Detecting Dim Moving Targets , 1985, IEEE Transactions on Aerospace and Electronic Systems.

[3]  Marco Lops,et al.  Sequential Detection of Markov Targets With Trajectory Estimation , 2008, IEEE Transactions on Information Theory.

[4]  S. W. Roberts.  Control chart tests based on geometric moving averages , 2000 .

[6]  Ian McConnell,et al.  Comparison of segmentation methods with standard CFAR for point target detection , 1998, Remote Sensing.

[7]  X. Rong Li,et al.  Sequential detection of targets in multichannel systems , 2003, IEEE Trans. Inf. Theory.

[8]  Alexander G. Tartakovsky,et al.  Adaptive sequential algorithms for detecting targets in a heavy IR clutter , 1999, Optics & Photonics.

[9]  D. Salmond,et al.  A particle filter for track-before-detect of a target with unknown amplitude , 2001 .

[10]  Venugopal V. Veeravalli,et al.  An efficient sequential procedure for detecting changes in multichannel and distributed systems , 2002, Proceedings of the Fifth International Conference on Information Fusion. FUSION 2002. (IEEE Cat.No.02EX5997).

[11]  Alexander G. Tartakovsky,et al.  Effective adaptive spatial-temporal technique for clutter rejection in IRST , 2000, SPIE Defense + Commercial Sensing.

[12]  E. S. Page.  A test for a change in a parameter occurring at an unknown point , 1955 .

[13]  M. Diani,et al.  Detection performance loss due to jitter in naval IRST systems , 2008, IEEE Transactions on Aerospace and Electronic Systems.