Formation wing-beat modulation (FWM) effect in radar signals of bird flocks: Theory and implication
No. 129, Luoyu Road
Wuhan, Hubei, China 430079
Abstract: Radar ornithology has revealed the existence of modulation signals in radar echoes from bird flocks, yet the underlying scattering mechanism responsible for this modulation remains largely unexplored. This proposal presents our research on the radar signals emitted by bird flocks, focusing on the analysis of this modulation using the micro-Doppler theory. We discover that the modulation originates from the flapping gaits of birds within the flock, resulting in a distinctive pattern known as the Formation Wing-Beat Modulation (FWM) effect. The FWM effect manifests as a collection of spectral peaks with similar amplitudes, evenly spaced at specific intervals. Furthermore, our investigation establishes the correlation between FWM signals and key parameters such as bird number, wing-beat frequency, and flight phasing strategy. Experimental validations are conducted using multiple radar systems, including a Ku-band surface surveillance radar, X-band coastal surveillance radar, and X-band air surveillance radar. These experiments confirm the presence of FWM signals in radar echoes from ground birds, sea birds, and migratory birds across various scenarios. The practical implications of FWM signals are significant, as they provide valuable tools for quantifying bird numbers and estimating the average wingbeat rate of birds. Moreover, we highlight the interference caused by bird clutters on micro-Doppler radar detection of drones, emphasizing the importance of considering FWM in drone detection systems. This groundbreaking finding not only contributes to the classification of birds from drones but also facilitates the quantification of bird migration numbers and the estimation of bird flight behavior within the domains of radar ornithology and aeroecology. By shedding light on the previously unexplored scattering mechanism of bird flocks, our research paves the way for advancements in understanding avian dynamics and their interactions with radar systems.
Dr. Jiangkun Gong is a postdoctoral fellow at the State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing at Wuhan University in China. He is working with Professor Deren Li, who is an Academician of the Chinese Academy of Sciences & the Chinese Academy of Engineering, and the Euro–Asia Academy of Sciences. He has developed an independent solution of radar automatic target recognition (ATR) for recognizing radar signals of uncooperative targets, which are mainly low, slow, and small (LSS) targets, such as hostile drones, birds, and maritime objects.