Doppler and Channel Estimation Using Superimposed Linear Frequency Modulation Preamble Signal for Underwater Acoustic Communication

Author:

Lv Chenglei12,Sun Qiushi1,Chen Huifang134ORCID,Xie Lei13

Affiliation:

1. College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou 310027, China

2. Interdisciplinary Student Training Platform for Marine Areas, Zhejiang University, Hangzhou 310027, China

3. Zhejiang Provincial Key Laboratory of Information Processing, Communication and Networking, Hangzhou 310027, China

4. Zhoushan Ocean Research Center, Zhejiang University, Zhoushan 316021, China

Abstract

Due to the relative motion between transmitters and receivers and the multipath characteristic of wideband underwater acoustic channels, Doppler and channel estimations are of great significance for an underwater acoustic (UWA) communication system. In this paper, a preamble signal based on superimposed linear frequency modulation (LFM) signals is first designed. Based on the designed preamble signal, a real-time Doppler factor estimation algorithm is proposed. The relative correlation peak shift of two LFM signals in the designed preamble signal is utilized to estimate the Doppler factor. Moreover, an enhanced channel estimation algorithm, the correlation-peak-search-based improved orthogonal matching pursuit (CPS-IOMP) algorithm, is also proposed. In the CPS-IOMP algorithm, the excellent autocorrelation characteristic of the designed preamble signal is used to estimate the channel sparsity and multipath delays, which are utilized to construct the simplified dictionary matrix. The simulation and sea trial data analysis results validated the designed preamble, the proposed Doppler estimation algorithm, and the channel estimation algorithm. The performance of the proposed Doppler factor estimation is better than that of the block estimation algorithm. Compared with the original OMP algorithm with known channel sparsity, the proposed CPS-IOMP algorithm achieves a similar estimation accuracy with a smaller computational complexity, as well as requiring no prior knowledge about the channel sparsity.

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Science and Technology Department of Zhejiang Province

Natural Science Foundation of Zhejiang Province

Publisher

MDPI AG

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