4.7 Article

A Kalman-based Doppler tracking algorithm for underwater acoustic spread spectrum communications

Journal

APPLIED ACOUSTICS
Volume 185, Issue -, Pages -

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.apacoust.2021.108374

Keywords

Underwater acoustic communications; Spread spectrum; Passband Doppler tracking; Kalman filter

Categories

Funding

  1. National Natural Science Foundation of China [61801137, 61901135, 61601134]
  2. National Natural Science Foundation of Heilongjiang [YQ2019D003]

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This paper investigates a method for dynamically tracking and compensating the Doppler spread of spread spectrum signals in underwater acoustic communications using a novel Kalman-based algorithm. The accurate estimation of waveform dilation/compression in the time domain and compensating magnitude distortion induced by velocity variation are achieved through processing passband signals with higher accuracy.
This paper investigates a method that dynamically tracks and compensates the Doppler spread of the spread spectrum signal in underwater acoustic communications. Due to the ultra-wideband property of the underwater acoustic signal, the Doppler spread is manifested as frequency shifting and time scaling, i.e., dilation or compression. The accurate estimation of the waveform dilation/compression in the time domain corresponds to the Doppler spread. A finer Doppler spread based on the passband signal can be discriminated due to the higher sampling rate than the baseband signal. In this paper, a novel Kalman-based Doppler tracking and compensation algorithm that operates on passband for underwater acoustic spread spectrum signal is addressed in a symbol-by-symbol fashion. The received signal is firstly correlated with the local passband reference signal to obtain the despreaded passband signal, and then a fractional time delay estimation on the passband signal by cosine waveform approximation is performed to achieve a higher accuracy of time delay estimation. The time difference of the two adjacent symbols is used as the input of the Kalman filter based on the delay-Doppler equation to estimate the instant Doppler factor sequentially. This algorithm adaptively changes the local reference signal based on the filtered Doppler factor for compensating magnitude distortion induced by the velocity variation. Both numerical simulation and experimental data analysis are presented to demonstrate the usability of the proposed algorithm. (C) 2021 Elsevier Ltd. All rights reserved.

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