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一种基于重力正演理论的海底地形反演迭代算法

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重力数据反演海底地形的方法是获取全球海底地形数据的重要途径.针对传统地形反演算法需要间接引入经验参数的问题,本研究以不采用经验公式为原则,从空间域方法入手,结合重力正演公式,建立重力异常与地形之间的解析观测方程,采用最小二乘方法进行求解.为了得到观测方程最优解,建立牛顿迭代关系,引入正则化参数,增强方程组的收敛性.顾及边缘效应对正演的影响,采用双线性插值算法对原始重力异常数据进行加密处理和无约束网格扩充以削弱误差.在太平洋海域(155°E~156'E,16°N~17°N)构建了 1'×1'分辨率的海底地形模型,并通过船测水深数据验证.相比于传统空间域算法——重力地质法,本研究方法的均方根误差降低了 12.7%,验证了其可行性与准确性.
A seafloor topography inversion iterative algorithm based on gravity forward modeling theory
The method of seafloor topography inversion from gravity data is an important way to obtain global seafloor topography.Aiming to solve the problem that traditional topography inversion algorithms need to indirectly introduce empirical parameters,this study,based on the principle of not adopting empirical formulas,established analytical observation equations between gravity anomalies and terrains by using the spatial domain method and the gravity orthogonal formulas,and solved the equations by the least squares method.In order to obtain the optimal solutions to the observation equations,Newtonian iterative relations were established and regularization parameters were introduced to enhance the convergence of the equations.Considering the influence of the edge effect on the regularization,a bilinear interpolation algorithm was used to encrypt the raw gravity anomaly data and the means of unconstrained grid expansion to weaken the error.Moreover,a 1'× 1'resolution seafloor topographic model was constructed in the Pacific Ocean(155°E~156°E,16°N~17°N),which was verified by the ship-surveyed bathymetry data,and the root mean squared error was reduced by about 12.7%compared with the traditional spatial-domain algorithm,gravity geology method,which verified the feasibility and accuracy of the proposed method.

gravity datagravity forward modelingtopography inversionregularization parameteredge effect

公维梁、屠泽杰、孙月文、邢赛、赵福玺、阳凡林

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山东科技大学测绘与空间信息学院,山东青岛 266590

浙江省水利河口研究院(浙江省海洋规划设计研究院),浙江杭州 310020

自然资源部海洋测绘重点实验室,山东青岛 266590

重力数据 重力正演 地形反演 正则化参数 边缘效应

广东省促进经济高质量发展(海洋经济发展)海洋六大产业专项项目山东科技大学科研创新团队支持计划项目

GDNRC[2023]422019TDJH103

2024

山东科技大学学报(自然科学版)
山东科技大学

山东科技大学学报(自然科学版)

CSTPCD北大核心
影响因子:0.437
ISSN:1672-3767
年,卷(期):2024.43(3)