Until recently, human surveillance has primarily been accomplished using video cameras. However, radar offers unique advantages over optical sensors, such as being able to operate at far distances, under adverse weather conditions, and at nighttime, when optical devices are unable to acquire meaningful data. Radar is capable of recognizing human activities by classifying the micro-Doppler signature of a subject. Micro-Doppler is caused by any rotating or vibrating parts of a target, and results in frequency modulations centered about the main Doppler shift caused by the translational motion of the target [1]. Thus, the rotation of a helicopter blade, wheels of a vehicle, or treads of a tank all result in micro-Doppler. In the case of humans, the complex motion of the limbs that occur in the course of any activity all result in a micro-Doppler signature visually distinguishable from other targets, even animals [2]-[3], which can then be exploited for human detection [4]-[5], automatic target recognition (ATR) [6]-[7], and activity classification [8].
A kinect-based human micro-doppler simulator
IEEE Aerospace and Electronic Systems Magazine ; 30 , 5 ; 6-17
2015-05-01
2891328 byte
Article (Journal)
Electronic Resource
English
Dynamic Doppler simulator Patent
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