Cross-Correlation Function of Signals and Wind Speed Estimation in Weather Radar Networks
Introduction: Due to the active promotion of weather radar networks based on small weather radars, the development of effective signal processing algorithms for such systems is important. Purpose: We develop mean wind speed estimation algorithms for weather radar networks, and analyze their performance. Results: In the paper, we discuss the derivation of a general expression for the signals cross-correlation function in a bistatic weather radar network, and make a conclusion that the signals in the system are independent. The core result is a two-step algorithm of wind speed estimation which is based on estimating the mean Doppler frequency and the efficient spectral bandwidth. The paper discusses a number of simplifications of the proposed algorithm with lower computational difficulty. Computer simulation has been carried out to compare the quality of the proposed algorithms. The main conclusion is that the performance of the mean Doppler frequency and the efficient spectral bandwidth estimation at the first step are of critical importance. Simplifications at the second step have little impact on the overall algorithm performance. Practical relevance: The obtained results can be used in the development of weather radar networks for mean wind speed vector estimation.