Abstract
Micro-Doppler is generated from targets with simple harmonic motions, characterized by a sinusoidal instantaneous frequency in the time-frequency plane. This type of micro-Doppler arises from vibrating or rotating targets, which are commonly present in indoor settings. It is shown that the use of basis functions matched to the sinusoidal micro-Doppler signatures proves effective in identifying the micro-Doppler components in indoor imaging. These functions are optimum in the maximum likelihood (ML) sense. Asymptotic properties of the proposed linear decomposition are derived. The basis decomposition provides enhanced phase and frequency resolutions and is robust to noise. It is strongly dependent on the Bessel function (of the first kind) characteristics. Simulation results are presented to demonstrate the effect of non-orthogonality of the basis functions and the respective frequency and phase resolution properties of the decomposition.
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