Signal Positioning of Lightning Detection and Warning System Combining Direction of Arrival Algorithm and Capon Algorithm
2025
Yiming Han | Bin He | Hongchun Shu
Aiming at the poor warning effect and slightly low precision of signal positioning in the traditional lightning detection and warning system, the research utilizes the artificial intelligence approach to signal positioning in the lightning detection and warning system for performance improvement. The study first digitized the lightning signal using the arrival direction algorithm and then used the Capon algorithm based on the digitized processing to reduce the interference and improve the accuracy of lightning positioning. The results indicated that the root mean square error value and positioning angle error of lightning warning signal positioning data processing by hybrid algorithm were 6.72% and 5.93%, respectively. Meanwhile, the percentage of detection efficiency and real time was 96.36% and 95.16%, respectively, and the anti-interference ability was 94.02%. Moreover, the average value of time-consuming lightning warning positioning and the positioning error were 2.39 s and 2.69%, respectively. Moreover, the performance of all the comparison indexes was better than that of the comparison methods. This indicates that the method not only improves the precision of lightning signal positioning but also enhances the stability and real-time performance of the system. It has significant application potential in the field of lightning detection and warning and can effectively improve the precision and timeliness of lightning warning.
Afficher plus [+] Moins [-]Mots clés AGROVOC
Informations bibliographiques
Cette notice bibliographique a été fournie par Multidisciplinary Digital Publishing Institute
Découvrez la collection de ce fournisseur de données dans AGRIS