Abstract
AbstractModern low-altitude unmanned aircraft (UA) detection and surveillance systems mostly adopt the multi-sensor fusion technology scheme of radar, visible light, infrared, acoustic and radio detection. Firstly, this paper summarises the latest research progress of UA and bird target detection and recognition technology based on radar, and provides an effective way of detection and recognition from the aspects of echo modeling and micro motion characteristic cognition, manoeuver feature enhancement and extraction, motion trajectory difference, deep learning intelligent classification, etc. Furthermore, this paper also analyses the target feature extraction and recognition algorithms represented by deep learning for other kinds of sensor data. Finally, after a comparison of the detection ability of various detection technologies, a technical scheme for low-altitude UA surveillance system based on four types of sensors is proposed, with a detailed description of its main performance indicators.
Publisher
Cambridge University Press (CUP)
Cited by
2 articles.
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1. UAV airframe classification based on trajectory data in UTM collaborative environments;2023 26th International Conference on Information Fusion (FUSION);2023-06-28
2. UAV Airframe Classification Using Acceleration Spectrograms;18th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2023);2023