Real-time design of a space/spatial-frequency optimal filter for highly nonstationary two-dimensional signal estimation

Two-dimensional (2D) optimal 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, also proposed in this paper. The filter permits multiple FRS detection in the observed 2D signal point, enabling very efficient filtering (in real-time) of nonstationary monocomponent and multicomponent FM signals, highly concentrated in the S/SF space and exposed to the high white noise influence. The filter is verified on various mono- and multicomponent 2D test signals.