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Description
High-rate delay and motion estimation is important for maneuvering underwater platforms using direct-sequence spread-spectrum signals. Conventional frame- or symbol-level estimators provide limited temporal resolution, while direct differentiation of noisy delay measurements amplifies velocity-estimation errors. This paper proposes an adaptive delay-Doppler tracking method based on chip-level DSSS correlation observations. Sliding correlation and three-point interpolation are used to obtain sub-sample delay measurements. A coarse frame-level Doppler estimate is first obtained from the synchronization signal, and the residual Doppler variation is then extracted from the phase differences between consecutive complex correlation peaks after removing the BPSK data-dependent phase. A constant-acceleration Kalman tracker is then developed to jointly estimate propagation delay, radial velocity, and acceleration. Its measurement covariance is adaptively adjusted according to the peak-to-sidelobe ratio and localpeak curvature. Simulations show that the proposed method reduces thedelay and velocity RMSE compared with a fixed-covariance Kalman filter.Results from a Songhua Lake experiment further demonstrate that theestimated radial velocity is consistent with the GPS-derived reference. The proposed method enables DSSS communication waveforms to provide high-update-rate motion estimates without an additional acoustic ranging signal.