An enhancing normalized inverse radon transform for parameter extraction of micro-Doppler
Wenchao Li, Boli Xiong, Gangyao Kuang · 2017 2nd International Conference on Frontiers of Sensors Technologies (ICFST) · 2017
The micro-Doppler induced by micro-motion in radar target represents an important characteristic made available for target recognition, which is usually manifest a sinusoid in the time-frequency (T-F) domain. Inverse Radon transform has been validated as an effective sinusoid detection method. Considered on the condition that multiple sinusoids existed in the T-F plane especially one is weaker relatively, this paper proposes an enhancing normalized inverse Radon transform (ENIRT) method to detect sinusoids in T-F plane as to extract the micro-Doppler parameters reflecting the target's intrinsic character. The improved method enhances weak sinusoidal curves firstly, and then inverse Radon transformed data is normalized by a normalization matrix. Preliminary results illustrates that the proposed algorithm improves sinusoidal curves detection performance in T-F plane.