@inproceedings{cf26ec21096146849b7357b89ac851c1,
title = "Performance analysis of a track before detect dynamic programming algorithm via generalized pareto distribution",
abstract = "We analyze a dynamic programming (DP)-based track before detect (TBD) algorithm. By using the generalized Pareto distribution (GPD) in extreme value theory, we obtain explicit expressions for the performance measures of the algorithm such as probability of detection and false alarm. Our analysis has two advantages. First the unrealistic the distribution for data from the exponential class assumptions used in EVT are not required. Second, the probability of detection and false alarm curves obtained fit computer simulated performance results significantly more accurately than previously proposed analyses of the TBD algorithm.",
keywords = "Dynamic programming, Generalized pareto distribution, Track before detect",
author = "Liang Cai and Chunlei Cao and Yanhua Wang and Guoxiao Yang and Shulin Liu and Le Zheng",
year = "2013",
doi = "10.1049/cp.2013.0392",
language = "English",
isbn = "9781849196031",
series = "IET Conference Publications",
number = "617 CP",
booktitle = "IET International Radar Conference 2013",
edition = "617 CP",
note = "IET International Radar Conference 2013 ; Conference date: 14-04-2013 Through 16-04-2013",
}