Open AccessCognitive target detection based on Bayesian approach in radar
Author(s) -
Ma Ning,
Wang Li,
Tang Jun,
Liao Qingmin,
Zhang Yunlei
Publication year - 2019
Publication title -
the journal of engineering
Language(s) - English
Resource type - Journals
ISSN - 2051-3305
DOI - 10.1049/joe.2019.0513
Subject(s) - a priori and a posteriori , computer science , bayesian probability , radar , detector , artificial intelligence , algorithm , machine learning , pattern recognition (psychology) , philosophy , epistemology , telecommunications
Cognitive radar (CR), which uses a closed‐loop feedback perception‐action cycle system, aims to develop a higher level of intelligence. In this study, the authors develop an efficient Bayesian approach to target detection in CR. The approach, which uses the Neyman‐Pearson criterion with priori probability, can improve the target detection effectively. The recursive form of computing priori probability is also discussed. Numerical simulations illustrate that the proposed target detector can improve the performance of detection with the usage of priori probability, which can be computed recursively using the previous measurements.