Abstract: To address the problem of false tracks that are easily generated during multi-target tracking with forward-looking sonar in reverberation environments, an underwater multi-target tracking method using sonar beam intensity as measurement information is proposed. This method incorporates target echo intensity into the measurement model, constructing a multi-target measurement model that combines range, azimuth, and intensity. Under the assumption of a Gaussian reverberation background, the intensity likelihood functions for target echoes and false alarms under cell-averaging constant false alarm rate are derived, and the likelihood function containing intensity information is integrated into the update process of the \delta -generalized labeled multi-Bernoulli filter. This integration aims to suppress the incorrect association of false-alarm measurements with target tracks and to improve the reliability of data association. Simulation and experiment results demonstrate that the \delta -generalized labeled multi-Bernoulli filter based on intensity measurements can effectively suppress false tracks. Furthermore, compared with the \delta -generalized labeled multi-Bernoulli filter that does not use intensity measurements, the proposed algorithm achieves more accurate target number estimation and better multi-target tracking performance.