High precision parameter estimation algorithm for chirp signals based on fractional Fourier transform with iterative correction

Radar signal parameter estimation is a critical issue in signal processing, electronic warfare, and related domains. Radar signal parameter estimation refers to the precise calculation of original radar transmission parameters such as frequency, modulation slope, pulse width, etc. The Fractional Fourier transform, renowned for its robust concentration abilities on chirp signals, excels in effectively filtering linear frequency-modulated signals despite its drawbacks of high computational complexity and limited estimation accuracy. Considering the condition, this article proposes a fast estimation algorithm based on the modified interpolation efficient Fractional Fourier transform and Radon-Wigner transform which aims to address the low accuracy and high computational complexity of linear frequency modulation (LFM) signal parameter estimation at a low signal-to-noise ratio. Specifically, iterative filtering reduces algorithmic computational load to a certain extent, while interpolation methods enhance parameter estimation precision. The proposed algorithm is evaluated on simulated datasets and compared against other algorithms for comprehensive assessment. Consequently, extensive experiments assert that the proposed method has a smaller calculation cost than the other algorithms, and the estimated RMSE is smaller.