Determination Method of Effective Rank Degree and Matrix Dimension in SVD De-noising

RF signals are widely used in space telemetry, track and command (TT&C) field. However, in the transmission process, a lot of noise will be introduced due to the interference of equipment components, transmission channel, atmosphere, electromagnetic environment, etc., which will affect the subsequent analysis and processing of the receiving equipment. Based on the singular value decomposition (SVD) method for noise suppression of RF signals, the Letts' criterion method was proposed to determine the effective rank order of singular value sequence (SVS). The effect of SVD on noise suppression in different dimension matrices were compared and analyzed. Main influencing factors were put forward to choose the matrix dimension as a result. Finally, Hankel matrix dimension automatic determination system was built to realize the choice of the matrix dimension. The noise suppression effect was improved by 0.5dB at least which compared with the traditional matrix dimension determination method.