Intelligent Assignment and Positioning Algorithm of Moving Target Based on Fuzzy Neural Network

• Published in: Ji suan ji ke xue Vol. 48; no. 8; pp. 246 - 252
• Main Authors: Qu, Li-cheng, Lyu, Jiao, Qu, Yi-hua, Wang, Hai-fei
• Format: Journal Article
• Language: Chinese
• Published: Chongqing Guojia Kexue Jishu Bu 01.08.2021; Editorial office of Computer Science
• Subjects: Accuracy; Algorithms; Artificial neural networks; Electromagnetic radiation; Field tests; Fuzzy logic; Geodetic accuracy; Geodetic coordinates; intelligent assignment|target positioning|fuzzy neural network|particle swarm optimization|intelligent video surveillance; Maneuverability; Monitoring; Moving targets; Neural networks; Optimization; Radar detection; Surveillance; Surveillance systems; Swarm intelligence; Target detection; Tracking; Unmanned aerial vehicles
• ISSN: 1002-137X
• DOI: 10.11896/jsjkx.200600050

In order to solve the problems of limited monitoring range, unreasonable allocation of monitoring resources, and untimely detection of moving targets in intelligent video surveillance systems under special application scenarios, the use of radar to detect electromagnetic waves has astrong penetration ability, large search range, and being not subject to special weather and optical conditions.Combined with the flexibility and maneuverability of unmanned aerial vehicles and automatic navigation vehicles, this paper proposes a radar-directed integrated linkage video surveillance model, and on this basis, studies a unified coordinate positioning system based on geodetic coordinates and intelligent assignment and positioning algorithm of moving target based on fuzzy neural network optimized by particle swarm optimization.The algorithm can automatically solve the control parameters of each camera in three dimensions of horizontal, vertical and zoom according to the radar detection signal, and combines the linkage c