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A high-frequency (HF) active sonar can be used to detect and track a small fast surface watercraft in shallow water based on the evolution of the watercraft wake observed in the sonar image sequence. An automatic detection and tracking (ADT) algorithm is described for this novel application. For each ping, the measurement of the target's polar position consists of 2 steps. First, the target bearing is estimated by finding the direction of arrival of the cavitation noise emitted by the watercraft. Then range measurements are extracted from the range profile (constant-angle cut of the sonar image) at the estimated target bearing. Range normalization and clutter map processing are used to reduce the number of false measurements. Estimates of the target's Cartesian position and velocity are updated at the sonar pulse repetition rate using the Kalman filter with debiased consistent converted measurements and nearest neighbour data association. The proposed algorithm is demonstrated using real data.