Adaptive Tracking Method for Time-Varying Underwater Acoustic Channel Based on Dynamic Gaussian Window

The traditional recursive least squares (RLS) algorithm is limited in highly dynamic and noisy underwater channels. To overcome this, we introduce the time-varying Gaussian sliding window-based RLS (VGSRLS) algorithm, designed for enhanced channel tracking. The VGSRLS algorithm adaptively adjusts window length based on the signal’s instantaneous frequency variation. A rotation matrix reorients the Gaussian window toward the highest signal-to-noise ratio (SNR) direction, increasing channel tracking accuracy. Further, the algorithm adapts the Gaussian window shape along the highest SNR direction by combining dynamic window length and anisotropic adjustments, effectively suppressing noise from other directions and enhancing SNR. Simulation results confirm that VGSRLS achieves superior channel estimation accuracy, showing reduced mean squared deviation (MSD) under typical noise conditions in underwater environments compared to the SRLS-DCD algorithm.