Title :
New analytical approach to detection threshold of a dynamic programming track-before-detect algorithm
Author :
Shulin Liu ; Xinliang Chen ; Tao Zeng ; Le Zheng
Author_Institution :
Dept. of Electron. Eng., Beijing Inst. of Technol., Beijing, China
fDate :
8/1/2013 12:00:00 AM
Abstract :
Maintaining the constant false alarm rate (CFAR) is an important issue for the dynamic programming-based track-before-detect (DP-TBD) in low signal-to-noise ratio environment. However, the existing method for analysing the false alarm probability, based on extreme value theory (EVT), leads to the inaccuracy of the obtained detection threshold. In this study, a new analytical approach to compute the false alarm probability of DP-TBD is presented. In the proposed method, the generalised Pareto distribution is utilised to approximate the false alarm probability based on the peaks over threshold model, which can maintain CFAR for DP-TBD method in the low signal-to-noise environment effectively. Simulation results show that this approach provides a more accurate false alarm probability estimation than previous EVT methods.
Keywords :
Pareto distribution; approximation theory; dynamic programming; object tracking; probability; signal detection; CFAR; DP-TBD; EVT; approximation theory; constant false alarm rate; dynamic programming track-before-detect algorithm; extreme value theory; false alarm probability estimation; generalised Pareto distribution; peaks over threshold model; signal-to-noise ratio environment;
Journal_Title :
Radar, Sonar & Navigation, IET
DOI :
10.1049/iet-rsn.2012.0172