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Miniaturized Doppler radar sensor (DRS) for noncontact motion detection is a hot topic in the microwave community. Previously, small-scale physiological signals such as human respiration and heartbeat rates are the primary interest of study. In this paper, we propose a comprehensive approach that can be used to improve the demodulation linearity of microwave DRSs, such that detailed time-domain motion information ranging from micro-scale to large scale can be accurately reconstructed. Experiments show that based on a digital-IF receiver architecture, dynamic dc offset tracking, and the extended differentiate and crossmultiply arctangent algorithm, the displacement and velocity of both micrometer-scale vibration of a tuning fork and meter-scale human walking can be accurately recovered. Our work confirms that substantial time-domain motion information is carried by the signals backscattered from moving objects. Retrieval of such information using DRSs can be potentially used in a wide range of healthcare and biomedical applications, such as motion pattern recognition and bio-signal measurements.Index Terms-Digital-IF receiver, Doppler radar sensor (DRS), extended differentiate and cross-multiply (DACM), gradient descent, motion imaging.

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