An improved design of adaptive directional time-frequency distributions based on the Radon transform

Adaptive directional time-frequency distribution (ADTFD) is an efficient TFD, which has outperformed most of the adaptive and fixed TFDs. However, two drawbacks of ADTFD have made this method inconvenient for processing real-world signals, such as biomedical signals. First, the high computational cost of the ADTFD and second, the sensitivity of the ADTFD to the presence of noise. This paper addresses these problems and introduces a computationally efficient variant of the ADTFD with robust construction in low SNR. In the proposed method, instead of iterative filtering in different directions, which is computationally expensive, the optimized directions are estimated using Radon transform of the modulus of the signal's ambiguity function. The achieved results show an improvement inversely proportional to the number of signal's auto-terms in contrast to the ADTFD.