To ensure the safety of the human occupied vehicle (HOV), an acoustic localization algorithm is proposed based on the virtual moving long baseline (VMLBL) technique. The influence factors on positioning error are analyzed. Instead of deploying transponders on the seafloor in advance, a set of manoeuvres are conducted to localize the HOV. First, based on the property of the innovation, an improved Kalman filter algorithm is used to perform outlier rejection and information correction for the range information. In this way, the influence of outlier can be overcome. Secondly, the VMLBL is constructed by fusing the moving radius vector of the HOV and the range information between the HOV and the ship. Then, the initial position results are calculated by the least squares method. To obtain more accurate position results, a cascade Kalman filter is utilized for trajectory smoothing and the final positioning result can be achieved. Simulations and sea trial data processing results show that the effective rate of data can reach 951% with positioning error less than 10%. The final positioning results are consistent with those of the ultrashort baseline positioning system. Thus, the proposed algorithm can provide an effective auxiliary way to localize the HOV.