Geoid Generation via Three Computation Spaces and Airborne Gravity
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Solution Overview
Problem
Existing systems for determining heights and generating height information, such as geoids, often rely on inaccurate or inconsistent data, leading to faulty designs and potential hazards in critical infrastructure development, including public and private projects that depend on spatial and elevation information.
Innovation Solution
A computing device configured with processor-executable instructions to receive airborne navigation, gravity, and LiDAR data, generating position information, gravity field information, orthometric height information, and a geoid, with a three-space method that subtracts topographical effects, performs downward continuation, and integrates to determine a more accurate geoid, creating a feedback loop for improved accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional height determination systems are used, then the complexity of the system is low, but the accuracy and reliability of height information deteriorates
Solution Approach 1:
The patent divides the geoid determination process into three distinct computational spaces: (1) observed space with topography, (2) intermediate space without topography, and (3) Helmert space. This segmentation allows each space to handle specific aspects of the computation, improving accuracy while managing complexity through structured division of the computational task.
Solution Approach 2:
The patent introduces an intermediate computational space that acts as a mediator between the observed space with topography and the final Helmert space. This intermediate space removes topographical effects to create a simplified gravitational field representation, which then serves as input for the final geoid computation, thereby improving measurement precision through staged processing.
2Measurement precision
If airborne gravity data is collected and processed, then the accuracy of geoid determination is improved, but the time and computational resources required increase
Solution Approach 1:
The patent performs preliminary processing by removing topographical effects in the intermediate space before conducting the final geoid computation. This preliminary action simplifies the gravitational field data, making subsequent computations more efficient and reducing the overall processing time while maintaining high accuracy.
Solution Approach 2:
The patent applies different processing approaches to different computational spaces according to their specific requirements. The observed space undergoes topography removal, the intermediate space undergoes gravitational field computation, and the Helmert space undergoes final geoid determination. This localized processing optimizes computational efficiency at each stage while achieving high overall accuracy.
3Reliability
If multiple data sources (airborne gravity, LiDAR, navigation) are integrated, then the reliability of height information is improved, but the device complexity and data processing requirements worsen
Solution Approach 1:
The patent merges multiple independent data sources (airborne gravity data, LiDAR data, and navigation data) into a unified geoid determination system. By combining these diverse data types through the three-space computational framework, the system achieves improved reliability and consistency of height information, as each data source compensates for the limitations of the others.
Data Source
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AI summary
Airborne gravity measurements may be added to the collection of airborne LiDAR so that it may be used to produce a digital elevation model (DEM), which may be used along with gravity data to produce an improved geoid, which may be used to produce an improved DEM based on the improved orthometric heights. A computing device may be configured to receive airborne navigation, gravity and LiDAR data, generate position information based on the navigation data, generate gravity field information based on the gravity data and the position information, generate orthometric height information based on the LiDAR data and the position information, and generate a geoid based on the gravity field and orthometric height information. The computing device may also generate a geoid model based on the gravity field and an existing DEM, and generate the orthometric height information based on the LiDAR data, position information, and geoid model.