Hardware implementation of a system for highly nonstationary two-dimensional FM signals estimation based on the sliding matrix function

Abstract

Optimal filter for highly nonstationary two-dimensional (2D) FM signals estimation is developed in this paper. The developed system uses a space-varying approach in real-time analysis of 2D nonstationary signals, related to the space/spatial-frequency (S/SF) domain tool based on the 2D cross-terms-free Wigner distribution. The system is based on the correspondence of the filter's region of support (FRS) to the local frequency (LF) of the filtered signal. By implementing the LF estimation, the system performs filtering of nonsationary 2D signals. The estimation has been implemented by the sliding matrix operation, which presents the central part of the developed design. The developed filter permits multiple FRS detection in the observed 2D signal point. In this way it enables a very efficient real-time filtering of nonstationary monocomponent and 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. It is also tested by the simulation on the multicomponent highly nonstationary noisy signal filtering.