Automated 3D Sonar Tracking of Unknown Objects
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Solution Overview
Problem
Current sonar imaging technologies face challenges in accurately tracking unknown objects with unknown shapes in underwater environments, particularly due to the sparsity of surfaces and noise in sonar data, which requires skilled operators and is inefficient in processing large amounts of raw data.
Innovation Solution
The use of large arrays of sonar detectors to produce 3D sonar images by segregating reflected sonar pings into defined shapes, assigning unique positions and orientations, and tracking these shapes over time, with automated techniques for data processing and noise reduction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual processing of sonar data is used, then operator skill can handle noise and sparsity, but processing efficiency is low and operator dependency is high
Solution Approach 1:
The system performs automated tracking and shape recognition without requiring manual operator intervention. The computer automatically processes sonar pings, segments point clouds, fits geometric shapes, and tracks objects through multiple pings, making the system self-sufficient and eliminating operator dependency while maintaining high processing efficiency
Solution Approach 2:
The patent replaces manual mechanical processing with automated computer-based algorithms. Instead of operators manually analyzing sonar data, the system uses automated point cloud segmentation, shape fitting algorithms, and tracking software to process data, substituting human manual work with computational automation
2Productivity
If automated processing is implemented, then processing efficiency improves, but handling unknown object shapes becomes more difficult
Solution Approach 1:
The patent segments the point cloud data into distinct clusters representing different objects, then further segments each object's point cloud to identify characteristic geometric features. This hierarchical segmentation allows the automated system to handle unknown shapes by breaking them down into recognizable geometric components that can be classified and tracked
Solution Approach 2:
The system changes parameters by fitting multiple candidate geometric shapes (sphere, cylinder, cube, cone, etc.) to each object and selecting the best fit based on statistical criteria. This parameter-based approach allows automated recognition of unknown shapes by comparing observed point distributions against known geometric models
3Measurement precision
If large arrays of sonar detectors are used, then data quality and resolution improve, but data processing complexity increases
Solution Approach 1:
The patent extracts only the relevant features from the large volume of sonar data by identifying and isolating point clouds that represent objects of interest. The system extracts geometric parameters, positions, and orientations from the raw detector data, separating useful information from the overwhelming amount of raw measurements to simplify subsequent processing
Solution Approach 2:
The system performs preliminary processing by pre-segmenting point clouds and pre-fitting candidate shapes before final tracking decisions are made. This preliminary organization of data structures and pre-computation of geometric parameters reduces the complexity of the main tracking algorithm by preparing the data in advance
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
This approach enables effective tracking of unknown objects in 3D space and time, improving accuracy and reducing operator dependency, while efficiently processing data to enhance the quality and resolution of sonar imaging.
Implementation Method 1
One or more large arrays of sonar detectors are used to produce three dimensional sonar images possible unknown objects. A series of sonar pings are sent into an insonified volume of water and the reflected or scattered sonar pings are analyzed
Implementation Method 2
the reflected or scattered sonar pings are analyzed to produce a 3 dimensional map of points which have scattered the sonar ping
Data Source
AI summary
Reflected sonar signals arising from one or more possible unknown objects are distinguished according to a first criterion, and possible shapes each having a defined unique associated point are assigned each of the possible unknown objects. Then the three dimensional points are tracked by the sonar system.