SIGNAL (programming language)

Algorithm

Control (management)

Engineering

Telecommunications

Computer science

Signal processing

Mathematics

Image (mathematics)

Signal reconstruction

Synchro

Instantaneous phase

Time–frequency analysis

Artificial intelligence

Programming language

Control theory (sociology)

Radar

Noise (video)

Electrical engineering

IEEE Transactions on Industrial Electronics

Traditional signal postprocessing methods suffer from the repeated assignment problem (RAP), which can result in inaccurate instantaneous frequency (IF) estimation and signal recovery. In this article, to solve this problem, a novel time-frequency (TF) analysis (TFA) method called the synchro-reassigning transform (SRT) is proposed. This method aims to obtain the ideal TF representation (TFR) by utilizing derivatives of the constructed amplitude function and a three-step selection rule to adaptively extract the TF coefficients on the IF trajectories in the TF plane, and reassigning these TF coefficients into a new TFR. In this way, SRT can eliminate the RAP, thus obtaining an approximately ideal TFR that helps to realize more accurate IF estimation and signal reconstruction. Furthermore, SRT shows satisfactory performance on signals with high nonlinear IFs or relatively close IFs, even under strong noise conditions. Two simulated signal and three real-life signals were used to demonstrate the performance of SRT.

Synchro-Reassigning Transform for Instantaneous Frequency Estimation and Signal Reconstruction