Gravity geologic method is one of the important to derive seafloor topography by using altimetry-gravity, and its committed step is gridding of regional gravity anomaly. Hence, we proposed a topography constraint factor weight optimization (TCFWO) method based on ordinary kriging method. This method fully considers the influence of topography factors on the construction of regional gravity grid besides horizontal distance. The results of regional gravity anomaly models constructed in the Markus-Wake seamount area show that the TCFWO method is better than ordinary kriging method. Then, the above two regional gravity models were applied to invert the seafloor topography. The accuracy of derived topographic models was evaluated by using the shipborne depth data and existing seafloor topography models, including ETOPO1 and V19.1 model. The experimental results show that the accuracy of ST_TCFWO (seafloor topography model inverted by TCFWO method) is better than ST_KR (seafloor topography model inverted by kriging method) and ETOPO1 model. Compared with the ST_KR, the accuracy of the ST_TCFWO has improved about 26%. In addition, the accuracy of seafloor topography is affected by the variation of depth, the distribution of control points and the type of terrain. In different depth layers, the ST_TCFWO has better advantages than ST_KR. In the sparse shipborne measurements area, the accuracy of ST_TCFWO is better than that of V19.1, ETOPO1 and ST_KR. Moreover, compared to other models, ST_TCFWO performs better in flat submarine plain or rugged seamount area.

The use of satellite altimetry to recover marine gravity anomalies allows for the rapid acquisition of seafloor topography on a wide range of regional scales. Currently, the commonly used approaches for inverting seafloor topography have been focused on the linear correlation between gravity anomalies and seafloor topography and have disregarded the effect of density contrast between the crust and seawater on depth. Therefore, we proposed a variable density and topography constraint combined modification (VDTCCM) method by deriving Parker’s formula and the Bouguer plate formula by introducing variable density and topography factors. This method can effectively recover topography-related nonlinear terms of gravity anomalies. Subsequently, the seafloor topography of the South China Sea was estimated by applying the VDTCCM method and was defined as Seafloor topography one (ST1), and following, the accuracy was evaluated using shipborne sounding data (SSD). The results indicate that the ST1 model’s SSD-checked accuracy is 23.34% and 39.42% higher than the common international models of ETOPO1 and DTU10, respectively. Moreover, the ST1 model has advantages in mapping rugged areas, showing more detailed topographical features. Consequently, the VDTCCM method can provide beneficial references for the construction of seafloor topography models on a large regional scale using gravity anomalies recovered from satellite altimetry.

This paper presents a study on enhancing the efficiency of underwater gravity matching navigation path planning in a three-dimensional environment. Firstly, to address the challenges of the computational complexity and prolonged calculation times associated with the existing three-dimensional path planning algorithms, a novel Three-Dimensional Along-Path Obstacle Profiling (TAOP) algorithm is introduced. The principles of the TAOP algorithm are as follows: (1) unfolding obstacles along the path using the path obtained from two-dimensional planning as an axis, interpolating water depth values based on downloaded terrain data, and subjecting obstacles to dilation treatment to construct a dilated obstacle profile for path segments; (2) conducting height direction course planning and a secondary optimization of the path based on the profile contours of the dilated obstacles; and (3) integrating height planning with the path points from two-dimensional planar planning to obtain a complete path containing all turning points in the three-dimensional space. Secondly, gravity anomaly data are utilized to delineate gravity suitability areas, and a three-dimensional planning environment that is suitable for underwater gravity matching navigation is established by integrating seafloor terrain data. Under identical planning environments and parameter conditions, the performance of the TAOP algorithm is compared to that of the RRT* algorithm, Q-RRT* algorithm, and Depth Sorting Fast Search (DSFS) algorithm. The results show that, compared to the RRT* algorithm, Q-RRT* algorithm, and DSFS algorithm, the TAOP algorithm achieves efficiency improvements of 15.6 times, 5.98 times, and 4.04 times, respectively.