In animal production, behavioral selection is becoming increasingly important to improve the docility of livestock. Several behavioral traits, including motion, are experimentally recorded in order to characterize the reactivity of animals and investigate its genetic determinism. Behavioral analyses are often time consuming because large numbers of animals have to be compared. For this reason, automatization is needed to develop high throughput data recording and efficient phenotyping. Here we

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... ntroduce a new method to monitor the position and motion of an individual sheep using a 24 GHz frequency-modulated continuous-wave radar in a classical experimental paradigm called the arena test. The measurement method is non-invasive, does not require equipping animals with electronic tags, and offers a depth measurement resolution less than 10 cm. Parasitic echoes (or "clutters") that could alter the sheep backscattered signal are removed by using the singular value decomposition analysis. In order to enhance the clutters mitigation, the direction-of-arrivals of electromagnetic backscattered signals are derived from applying the MUltiple Signals Classification algorithm. We discuss how the proposed automatized monitoring of individual sheep could be applied to a wider range of species and experimental contexts for animal behavior research.