Tracking channel variations in a time-varying doubly-spread underwater acoustic channel

Channel impulse responses (CIRs) are estimated for a doubly-spread acoustic channel in this paper by (1) estimating explicitly the path-dependent Doppler frequency shifts assuming a time-invariant CIR for individual blocks of data, and (2) estimating the time-varying CIR symbol by symbol including the phase change due to the Doppler. For the latter, a subspace based tracker is used to track the time variation of the channel basis vectors with their amplitudes tracked using a Kalman filter aided with a state-space model. For each method, the performance is measured by the normalized signal prediction error, the error between the data and the predicted signal based on the estimated CIRs, assuming the transmitted signal is known. Analysis of at sea data shows a 7 dB improvement in signal prediction error by tracking CIR using the model-based approach compared with the conventional methods based on explicit Doppler estimation.

[1]  T. C. Yang,et al.  Improving channel estimation for rapidly time-varying correlated underwater acoustic channels by tracking the signal subspace , 2015, Ad Hoc Networks.

[2]  Lee Freitag,et al.  Improved Doppler tracking and correction for underwater acoustic communications , 1997, 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[3]  T. C. Yang,et al.  Model-Based Signal Subspace Channel Tracking for Correlated Underwater Acoustic Communication Channels , 2012, IEEE Journal of Oceanic Engineering.

[4]  Fengzhong Qu,et al.  A Two-Stage Approach for the Estimation of Doubly Spread Acoustic Channels , 2015, IEEE Journal of Oceanic Engineering.

[5]  Wen-Jun Zeng,et al.  Time delay and Doppler estimation for wideband acoustic signals in multipath environments. , 2011, The Journal of the Acoustical Society of America.

[6]  B.S. Sharif,et al.  A computationally efficient Doppler compensation system for underwater acoustic communications , 2000, IEEE Journal of Oceanic Engineering.

[7]  Wen-Bin Yang,et al.  Low probability of detection underwater acoustic communications using direct-sequence spread spectrum. , 2008, The Journal of the Acoustical Society of America.

[8]  Wen Xu,et al.  Fast estimation of sparse doubly spread acoustic channels. , 2012, The Journal of the Acoustical Society of America.

[9]  L. Freitag,et al.  This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination. IEEE JOURNAL OF OCEANIC ENGINEERING 1 Peer-Reviewed Technical Communication Multicarrier Communication Over Un , 2022 .

[10]  Bin Yang,et al.  Projection approximation subspace tracking , 1995, IEEE Trans. Signal Process..

[11]  J. Preisig,et al.  Estimation of Rapidly Time-Varying Sparse Channels , 2007, IEEE Journal of Oceanic Engineering.

[12]  P. Bello Characterization of Randomly Time-Variant Linear Channels , 1963 .