Abstract

Micro-Doppler signals refer to Doppler scattering returns produced by the motions of the target other than gross translation. The small micro-motions of a subject, and even just parts of a subject, can be observed through the micro-Doppler signature it creates in response to an active emitter such as a radar, laser, and even acoustic emitters. These micro-Doppler signatures are produced by the kinematic properties of the subject's motion and can be used to extract the salient features of the subject's motion, and often, identify the subject. The rapidly declining cost of micro-Doppler-capable active sensors like radar with their dramatically improving capabilities, provide significant motivation in developing micro-Doppler techniques that can improve the exploitation of these sensors. Micro-Doppler techniques aim at extracting the micro-motion of the subject that may be unique to a particular subject class or activity in order to distinguish probable false alarms from real detections, as well as to increase the value of the information extracted from the sensor. The source of micro-motion depends on the subject and can be a rotating propeller on a fixed-wing aircraft, the multiple spinning rotor blades of a helicopter, or an unmanned aerial vehicle (UAV); the vibrations of an engine shaking a vehicle; an antenna rotating on a ship; the flapping wings of birds; the swinging arms and legs of a walking person; and many other sources. Confuser detections, such as birds for UAVs or animals for humans, can be interpreted as false alarms for a sensor system, so using the available micro-Doppler returns for classification can significantly reduce the sensor false alarm rate, thereby improving the utility of the sensor system. This study reviews the current research in micro-Doppler based on subject type, sensor capabilities, as well as environmental effects, and then proposes future research areas for micro-Doppler.

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