Technical gazette, Vol. 31 No. 3, 2024.
Original scientific paper
https://doi.org/10.17559/TV-20230703000781
Multi-Environment Adaptive Fast Constant False Alarm Detection Algorithm Optimization Strategy
Wei Li
orcid.org/0009-0004-3573-4386
; School of Electronic Information Engineering, Geely University of China, Chengdu, 641423
Qian Wang
; School of Electronic Information Engineering, Geely University of China, Chengdu, 641423
Yuan-shuai Lan
; School of Electronic Information Engineering, Geely University of China, Chengdu, 641423
Chang-song Ma
; School of Electronic Information Engineering, Geely University of China, Chengdu, 641423
Abstract
It takes a long time to detect target information in noisy radar information and reduce the probability of false alarm. Therefore, it has become a research direction to reduce the probability of false alarm and the time of effective target detection. This paper introduces a new method to reduce the occurrence of false alarm in non-uniform environment and improve the efficiency of target detection. The proposed method involves a faster and more stable method that involves preprocessing the data set, splitting it into smaller parts, and utilizing a KTH minimum value M determined by an ordered statistics class constant false alarm detection algorithm. Each data point in the small segment is then compared to M, anything above M is classified as a target, and anything below M is ignored as clutter. Then ESVI-CFAR detection was performed on the selected target to obtain the final detection result. Experimental results show that the proposed method is superior to the traditional VI-CFAR and has better target detection performance.
Keywords
data set; ESVI-CFAR; false alarm probability; noise; VI-CFAR
Hrčak ID:
316378
URI
Publication date:
23.4.2024.
Visits: 55 *