This letter aims to show the potential of using polarimetric parameters to distinguish between large birds and unmanned aerial vehicles (UAV) of comparable size in the context of a modern long range air defence radar. Time is a critical resource in such systems and techniques for robust noncooperative target recognition (NCTR) not relying on spatial resolution or long dwell times are highly desired. Furthermore, methods less dependent on target micro-motion are in many cases required. Methods exploiting polarimetric features are shown to have potential in both cases. An experiment in S-band shows that a simple Nearest-neighbor classifier can achieve good separation between UAVs and birds both with and without detectable micromotion based on a set of polarimetric parameters alone.
Although periodic amplitude modulation of echoes from birds were observed in the very first recordings of birds with radar, few publications on the topic are found in the literature. The phenomenon, which tends to be correlated with the wing beat frequency (WBF), has been suggested as a feature for discrimination between bird species. Early studies were reported mainly in the 1960s and 1970s, however, several questions remain unanswered. Is such modulation prevalent, if so what causes it, how does it vary with aspect angle and signal to noise ratio (SNR), how sensitive is it choice of carrier frequency, and what is its potential as a feature for classification in a real scenario? This paper seeks to address several of these question. The discussion and results presented are based on analysis of X-band radar data and video of flying gannets. These measurements are supported with electromagnetic predictions of 3D gannet models.
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