On the sliding matrix function based Wiener filter for highly nonstationary two-dimensional FM signal estimation

Real-time design of the two-dimensional (2D) Wiener filter for highly nonstationary 2D signal estimation is developed. It is based on the real-time results of space/spatial-frequency (S/SF) analysis, on the correspondence of filter's region of support (FRS) to the signal's local frequency (LF) and on the real-time LF estimation algorithm, implemented by the sliding matrix operation. The filter permits multiple FRS detection in the observed 2D signal point, enabling very efficient real-time filtering of nonstationary multicomponent FM signals, highly concentrated in the S/SF space and exposed to the high white noise. The design is proven through the verification of the sliding matrix operation and by the simulation.