Multi-Source Information Fusion for UAV State Estimation and Identification

Abstract

With the rapid development of UAV technology, low-altitude, slow-speed, small unmanned aircraft have become a growing threat to
public security. UAV monitoring and identification in complex environments present significant technical challenges. This paper investigates
multi-source information fusion for UAV state estimation and identification. A distributed fusion framework is constructed. It integrates radar,
electro-optical sensors, radio reconnaissance, acoustic sensing, and navigation deception modules. This study achieves reliable target UAV
detection via spatiotemporal registration, feature extraction, and decision-level fusion. The proposed method has been deployed in the lowaltitude security system of a critical facility. Results show that it improves the system's capability to detect, identify, and counter target UAVs.