A fast spectral moments estimation approach of radar echoes with low signal-to-noise ratio

A fast parameterized spectral moments estimation method is proposed for enhancing the estimation accuracy of the Doppler parameters of airborne weather radar echoes in low SNR scenarios. Covariance matrix decomposition is employed in the estimation, based on the assumption that the spectral of echoes from weather targets is subject to Gaussian distribution. Theoretical analysis suggests that the covariance matrix of the echoes conforms to the Vandermonde structure, thus the cost function for covariance-matrix-based spectral moment estimation can be interpreted by a DFT-type matrix. The cost function for fast spectral moment estimation is then computed by Fast Fourier Transform and Gaussian weighted sliding window. Simulation results demonstrate that the proposed method is capable of estimating spectral parameters of echoes even when the SNR is lower than 5 dB. And there is no compromise of estimation performance under a wide spectral width situation with this reduced computational complexity method.