Micro-Doppler Frequency Extraction and Scatterer Classification for a Smooth-Surfaced Cone-Shaped Precession Target Under Narrowband Radar

Abstract

The micro-Doppler (μD) characteristics of ballistic targets are crucial for estimating motion and structural parameters, as well as for target recognition. However, existing time-frequency (TF) analysis methods are predominantly nonparametric and suffer from limited resolution, making it challenging to accurately extract μD TF curves. This limitation hampers further applications in this domain. Therefore, under narrowband radar observation conditions, this article proposes a method for μD TF characteristics extraction and scatterer type identification, specifically for smooth-surfaced cone-shaped precession targets. The method first utilizes sliding-window Root-MUSIC to extract the instantaneous μD frequencies of the target. Then, the inverse Radon transform (IRT) and You Only Look Once version 5 algorithm are applied to locate and identify the peaks of cone vertex and cone base after IRT. Based on the peaks, the μD TF trend curves can be reconstructed using the Radon transform (RT). The extracted instantaneous μD frequencies are then associated according to the trend curves, enabling the reconstruction of the μD frequencies for the cone vertex and cone base. Experiments validate the effectiveness and noise robustness of the proposed method. The results demonstrate that the estimation accuracy of the proposed method is independent of the sampling interval and significantly outperforms traditional nonparametric methods.