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Helicopter classification via period estimation and time-frequency masks

Zhang, Rui and Li, Gang and Clemente, Carmine and Varshney, Pramod K. (2015) Helicopter classification via period estimation and time-frequency masks. In: 6th IEEE Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP 2015), 2015-12-13 - 2015-12-16.

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Abstract

The rotation of blades of a helicopter induces a Doppler modulation around the main Doppler shift, which is commonly called the micro-Doppler signature and can be used for target classification. In this paper, an automatic helicopter classification method is proposed by estimating the period of the micro-Doppler signature and identifying the number of blades via time-frequency masks. The advantages of this method are threefold: (1) it determines the number of blades automatically; (2) it significantly reduces the computational burden compared to the classical model dictionary-based classification methods; (3) it is robust with respect to the inclination of the helicopter. The effectiveness of the proposed approach is validated by using both synthetic and real data.