Micro-Doppler Feature Extraction of Rotating Structures of Aircraft Targets with Terahertz Radar

Abstract

The micro-Doppler features formed by the micro-motion of rotating blades of rotors and turbines are of great significance for aircraft target detection and recognition. Mastering the micro-motion features is the premise of radar target identification. The blades’ length and rotation rate are vital parameters for classifying aircraft targets. One can instantly judge the type and state of the targets by extracting micro-Doppler features. To extract the micro-Doppler features of rotating blades of the turbine target, we utilized microwave-band and terahertz-band radar to simulate the target and extract the Doppler frequency-shift information. For a turbine model with an obvious blade tip structure, we propose an algorithm based on wavelet coefficient enhancement and inverse Radon transform, integrating the time–frequency analysis with image processing. Under low SNR, this method allows for a high-accuracy parameter estimate. For a two-bladed rotor model without an obvious blade tip structure, we conducted an actual measurement experiment on the model utilizing a 120 GHz radar, and we propose a parameter estimation algorithm based on the fitting of the time–frequency distribution. By fitting the data of the time–frequency diagram, the micro-motion characteristic parameters of the rotor target were obtained. The simulation and experimental results demonstrate the benefits of terahertz radar in target detection, and indicate that the proposed algorithms have the characteristics of high extraction precision and insensitivity to noise.