Linear frequency modulated reverberation suppression using time series models

Abstract

When active radar and sonar systems are used for target detection and tracking, boosting target detection, and tracking efficiency is the most important challenge in real-time reverberation. To eliminate reverberation when transmitting linear frequency modulated (LFM) signals, this study employs time series techniques such as autoregressive (AR), moving average (MA), and autoregressive moving average (ARMA). The primary purpose of this research is to whiten LFM reverberation by transforming it to a fractional domain using the fractional Fourier transform (FrFT). The LFM reverberation is a highly coloured noise whose frequency fluctuates according to the stationary hitting frequency. As a reference signal, the proposed methods make use of the adjacent signal block. The effectiveness of FrFT-based AR, MA, and ARMA pre-whitening for LFM reverberation reduction was assessed, and the results were presented.