Seafloor real-time positioning is important for the instantaneous detection of seafloor crustal motion, seismic activities, hydrological rapid variations and rapid geodetic datum updates. Current GNSS-Acoustic (GNSS-A) seafloor positioning usually utilizes batch processing of long-term observations in the postprocessing mode. Seafloor real-time positioning can be achieved using sequential processing of the epoch-wise observations. We propose the sequential GNSS-A seafloor point positioning method with modeling of the sound speed variation in the kinematic survey. We propose real-time modeling of the sound speed variation using oceanography analysis data and we then calculate the random walk (RW) process noise of the acoustic nadir total delay (NTD) caused by the sound speed variation. The experiments conducted in the South China Sea and Japan Trench validate the method performance in terms of epoch-wise positioning accuracy, high-resolution sound speed variation, and filter convergence time. The difference between the estimated sound speed and the in situ sound velocity profiles was 0.128 m/s root mean square. The vessel track of the line and circle combination performs best with a high positioning accuracy and a short convergence time. The position in real-time sequential processing with the modeled NTD RW process noise converged to a 3D range of 0.125 m from the static post-determined position. The a posteriori residual of the acoustic travel time observations was equivalently 0.270 m in range. These findings can improve the temporal resolution of the GNSS-A positioning and oceanography.

海底实时定位对于海底地壳运动、地震活动、水文快速变化和大地基准快速更新的瞬时检测具有重要意义。目前的GNSS-声学（GNSS-A）海底定位通常在后处理模式下利用长期观测的批处理。通过对历元观测的顺序处理可以实现海底实时定位。我们提出了连续 GNSS-A 海底点定位方法，并对运动学测量中的声速变化进行建模。我们提出使用海洋学分析数据对声速变化进行实时建模，然后计算由声速变化引起的声学最低点总延迟（NTD）的随机游走（RW）过程噪声。在南海和日本海沟进行的实验验证了该方法在历元定位精度、高分辨率声速变化和滤波器收敛时间方面的性能。估计声速与现场声速剖面之间的差异为 0.128 m/s 均方根。直线与圆组合的船舶轨迹表现最好，定位精度高，收敛时间短。实时顺序处理中的位置与建模的 NTD RW 过程噪声收敛到距静态后确定位置 0.125 m 的 3D 范围。声学走时观测的后验残差相当于 0.270 m 的范围。这些发现可以提高 GNSS-A 定位和海洋学的时间分辨率。