Iterative Time-Varying Filter Algorithm Based on Discrete Linear Chirp Transform

TL;DR

This paper presents a novel iterative time-varying filter algorithm based on the discrete linear chirp transform, which effectively denoises broadband non-stationary signals by leveraging sparse representations, outperforming existing methods like DFrFT.

Contribution

The paper introduces a new DLCT-based filtering algorithm for broadband signals, demonstrating improved denoising performance over existing DFrFT-based methods.

Findings

DLCT algorithm achieves higher filtering quality than DFrFT.

Simulation results confirm the effectiveness of the DLCT approach.

The method provides better local signal decomposition for non-stationary signals.

Abstract

Denoising of broadband non--stationary signals is a challenging problem in communication systems. In this paper, we introduce a time-varying filter algorithm based on the discrete linear chirp transform (DLCT), which provides local signal decomposition in terms of linear chirps. The method relies on the ability of the DLCT for providing a sparse representation to a wide class of broadband signals. The performance of the proposed algorithm is compared with the discrete fractional Fourier transform (DFrFT) filtering algorithm. Simulation results show that the DLCT algorithm provides better performance than the DFrFT algorithm and consequently achieves high quality filtering.