A NSZT Method for Frequency Estimation and Anti-noise Performance Analysis

Among all the frequency estimation algorithm, the spectrum zooming method has superiority for high resolution and excellent anti-noise performance, but it needs more computational resource. The typical spectrum zooming methods include Zoom fast Fourier transform (ZFFT), Chirp-Z transform (CZT) and zeropadding, which are all uniform spectrum zooming methods. A Nonuniform spectrum zooming transform (NSZT) method with higher accuracy, better anti-noise ability and higher efficiency is presented. To verify the proposed method, the Monte-Carlo simulations are performed. Results are presented and compared with the Cramer-Rao bound (CRB) method, showing that the proposed algorithm has the least Mean square error (MSE) among these algorithms. This NSZT method is used in a 24GHz Frequency modulated continuous wave (FMCW) radar system and an experiment for the real-time ranging is conducted. The experimental results show that the ranging error of the radar system is about 5mm in 10m, which verifies the feasibility of our proposed method.