An Improved Parameter Estimation of Hfm Signals Based on Irls Linear Fitting of Extracted Group Delay

作     者：Yao, Shuai Zhang, Yixuan Xu, Yanan Gu, Yian Cao, Hongli 

作者机构：Key Laboratory of Underwater Acoustic Signal Processing of Ministry of Education Southeast University Nanjing210096 China Hangzhou Applied Acoustic Research Institute Hangzhou310012 China Department of Electronic and Electrical Engineering University College London London United Kingdom 

出 版 物：《SSRN》 

年 卷 期：2023年

核心收录：

主　　题：Group delay 

摘      要：To address the issue of robust parameter estimation of hyperbolic frequency modulated (HFM) signals under low signal-to-noise ratios (SNRs), an improved algorithm based on iteratively reweighted least squares (IRLS) linear fitting of extracted group delay is proposed. The algorithm includes three main steps. First, a novel method for estimating the frequency distribution range (FDR) of an HFM signal is presented, which involves analyzing the transient features of the amplitude spectrum (AS). Second, the spectrum phase (SP) is unwrapped in the estimated FDR to extract the group delay (GD) of the HFM signal. Last, parameter estimation of the HFM signal is achieved by fitting the GD, which is a linear function of the reciprocal of the frequency, using the IRLS linear fitting method. The simulation results have shown that for SNR ≥ -14 dB, the normalized root mean square errors (NRMSEs) estimated by the proposed estimator are 1.5 dB higher than those estimated by the spectrum phase unwrapping (SPU) estimator, including the starting frequency and period slope. Furthermore, experimental results based on sea trial data have also verified the validity and feasibility of the proposed estimator. © 2023, The Authors. All rights reserved.