Underwater Sonar Point Cloud Interpolation via Optical Calibration
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Solution Overview
Problem
Underwater sonar systems face challenges in generating complete point clouds due to sparse data at greater distances and missing points at closer ranges, leading to incomplete representations of underwater environments.
Innovation Solution
A sensing system comprising an underwater sonar array and a computing module that acquires point cloud information, rearranges points into a matrix, performs interpolation calculations to fill missing points based on neighboring depth values, and optionally uses image data for calibration to enhance depth value accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If the underwater sonar is positioned at a greater distance from the seabed to cover a larger area, then the sensing coverage is improved, but the point cloud becomes sparse and incomplete
Solution Approach 1:
The patent introduces an intermediary processing system that combines sonar point cloud data with optical image data. The optical images serve as a mediator to fill in the sparse regions of the sonar point cloud, particularly in areas where the sonar distance is greater from the seabed. This hybrid approach allows maintaining large sensing coverage while compensating for the sparsity and incompleteness of sonar-only data.
Solution Approach 2:
The patent merges two different sensing modalities - acoustic sonar point cloud data and optical image data - into a unified representation. By combining the strengths of both sensing systems (sonar's ability to penetrate water and cover large areas, and optical sensors' ability to provide detailed surface information), the system achieves both large coverage area and complete point cloud data.
2Quantity of substance
If the underwater sonar is positioned at a shorter distance from the seabed to capture more detailed points, then the point cloud density is improved, but the sensing coverage area is reduced
Solution Approach 1:
The patent segments the sensing task between two different modalities: sonar handles the large-area coverage and coarse structure detection, while optical sensors handle the detailed surface capture in closer regions. This segmentation allows each sensor to operate in its optimal range - sonar at greater distances for coverage and optical sensors at closer distances for density - without requiring a single sensor to compromise between the two objectives.
Solution Approach 2:
The patent adds another dimension to the data by combining three-dimensional sonar point cloud information with two-dimensional optical image information. This multi-dimensional fusion allows the system to achieve both large coverage (from sonar's 3D spatial mapping) and high density (from optical images' detailed surface capture) by leveraging different dimensional strengths of each sensing modality.
3Productivity
If traditional interpolation methods are used to fill missing points, then the processing speed is improved, but the accuracy of depth values deteriorates
Solution Approach 1:
The patent introduces optical image data as an intermediary source to improve depth value accuracy. Instead of relying solely on traditional interpolation methods that only use sonar data, the system uses optical images as a mediator to provide additional depth information. This intermediary data source helps maintain measurement precision while avoiding the need for complex, time-consuming interpolation algorithms.
Solution Approach 2:
The patent creates a composite data structure that combines sonar point cloud information with optical image information. This composite approach integrates two different data types with complementary strengths - the spatial structure from sonar and the detailed surface information from optical sensors - to achieve both processing efficiency and high depth value accuracy without relying on traditional interpolation alone.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system effectively addresses the issue of incomplete point clouds by interpolating missing depth values and calibrating them using image data, resulting in more comprehensive and accurate representations of underwater environments.
Implementation Method 1
In a case that an underwater sonar is used to obtain point clouds
Data Source
AI summary
The present invention proposes a method for sensing underwater point cloud. The method includes: acquiring point cloud information through an underwater sonar array, where the point cloud information contains multiple points; rearranging these points into a matrix which includes the aforementioned points and multiple missing points; and for each missing point, interpolating its depth value based on the depth values of several neighboring points.