Micro-Doppler Super-Resolution Using Iterative Adaptive Approach

Micro-Doppler signatures refer to the time-varying Doppler frequency modulation induced by the motion of multiple parts or features of a target or scene, in addition to the bulk motion of the target. Radar experts have extensively utilized micro-Doppler signatures to identify targets displaying micro-motions. The short-time Fourier transform (STFT) is commonly employed for extracting micro-Doppler signatures in radar applications. The STFT is designed to enhance either temporal or spectral resolution or to achieve a balance between them. In this paper, we introduce the application of Doppler super-resolution utilizing the Iterative Adaptive Approach (IAA) method, commonly employed for angle estimation. The proposed technique enhances temporal resolution by achieving super-resolution in Doppler estimation while utilizing a reduced number of samples for the spectral domain. This technique is applied to generate spectrograms with finer resolutions, aiming to improve the performance of micro-Doppler classification methods. This paper demonstrates the enhanced performance of micro-Doppler classification achieved with IAA through analysis of real radar data.