Multi-radar Signal Level Fusion Detection Algorithm based on Fast Time Accumulation

Aiming at the problem of multi-radar joint detection, the performance of non-coherent accumulation detection algorithm under fast time sampling is analyzed. In order to improve the detection performance, two fast time phase-coherent accumulation detection algorithms are designed based on Generalized...

Full description

Saved in:
Bibliographic Details
Published in2020 IEEE International Conference on Information Technology,Big Data and Artificial Intelligence (ICIBA) Vol. 1; pp. 1487 - 1492
Main Authors Xuan, Fang, Lin, Zhou
Format Conference Proceeding
LanguageEnglish
Published IEEE 06.11.2020
Subjects
detection
Detection algorithms
Detectors
fast time
fusion
Multi-radar
Radar
Radar detection
Receivers
signal level
Signal to noise ratio
Time-frequency analysis
Online AccessGet full text
DOI10.1109/ICIBA50161.2020.9277453

Cover

More Information
Summary:Aiming at the problem of multi-radar joint detection, the performance of non-coherent accumulation detection algorithm under fast time sampling is analyzed. In order to improve the detection performance, two fast time phase-coherent accumulation detection algorithms are designed based on Generalized Likelihood Ratio Test (GLRT): 1. Fusion detection algorithm based on rapid phase-coherent accumulation in a single station;2. Detection algorithm based on overall signal fusion. From the perspective of theory and simulation, the performance of the two improved methods for detecting low-speed or stationary targets is better than that of the non-coherent accumulation detection method. Method 1 is suitable for distributed networking, while method 2 is suitable for centralized networking. The improved algorithm can extract target Doppler features while fusion detection, and provide information for target recognition and motion analysis.
DOI:10.1109/ICIBA50161.2020.9277453