A.A. Monakov, Yu.A. Monakov
The presented paper is devoted to the synthesis and analysis of signal processing algorithms for parameter estimation of the atmospheric turbulence in airborne weather radars. For definition of degree of the turbulence danger for aircraft, it is necessary to measure the mean value and the standard deviation of the wind speed in an observable area. This task is equivalent to estimation of the mean frequency and the spectrum width of detected weather signals. In article some algorithms of estimation, including the pulse pair method, which is often used in meteorological radars, are considered. A comparative analysis of different algorithms of estimation of the signal power, mean frequency and effective spectrum width for weather signals is presented. The analysis of the proposed algorithms testifies that the algorithm based on the correlogram method of random signal spectral analysis has better characteristics. This method combines simplicity of realization, wide aperture of the frequency respond function, and good statistical properties. Simulation showed that, when the number of signal samples N = 256 and the SNR is more than 20°dB, the standard deviation of the estimation errors of the mean frequency and the spectrum width do not exceed 12% and 10 % of the true spectrum width respectively for weak, moderate and high turbulence. Analytical calculations prove this conclusion.