3D Sonar Image Construction Using Depth Slice Segmentation
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Solution Overview
Problem
Conventional sonar systems fail to effectively differentiate objects in an underwater environment and provide a detailed, intuitive 3D image, lacking real-time tracking capabilities and efficient processing for object characteristics.
Innovation Solution
The method involves generating a 3D matrix from sonar return data, identifying clusters of returns associated with objects, and processing these to create a 3D image, allowing differentiation between the sea floor and objects, with real-time tracking and characterization of object size, shape, and movement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional sonar systems are used to detect underwater objects, then basic detection capability is provided, but the ability to differentiate objects and provide detailed 3D images is insufficient
Solution Approach 1:
The sonar return data is segmented into multiple 2D slices at different depths, which are then processed independently to identify objects and generate 3D coordinates. This segmentation allows complex 3D object differentiation to be broken down into manageable 2D analysis steps, improving measurement precision without proportionally increasing overall system complexity.
Solution Approach 2:
The system transitions from conventional 2D sonar displays to 3D visualization by adding the depth dimension. 2D sonar returns are enhanced with depth information to create 3D coordinates (x, y, z), enabling intuitive spatial representation of objects and significantly improving object differentiation and environmental visualization.
2Loss of information
If 3D sonar imaging is implemented to provide detailed environmental visualization, then object differentiation improves, but processing complexity and computational requirements increase
Solution Approach 1:
The system performs preliminary processing by organizing sonar returns into 2D slices at specific depth intervals before 3D reconstruction. This preliminary organization of data by depth layers simplifies subsequent object identification and 3D coordinate calculation, reducing overall processing complexity while preserving environmental detail information.
Solution Approach 2:
The system creates simplified 2D representations (copies) of the underwater environment at different depth slices. These 2D copies are easier to process and analyze than complete 3D data, allowing efficient object identification which is then reconstructed into 3D coordinates to maintain full environmental detail information.
3Productivity
If real-time tracking of objects is implemented in 3D space, then object characterization capability improves, but processing time and computational load increase
Solution Approach 1:
Object tracking is segmented into independent 2D plane analyses that are processed separately and then combined. By tracking objects in 2D slices first and then reconstructing 3D positions, the system achieves comprehensive object characterization while reducing the computational burden of direct 3D tracking, thereby decreasing processing time.
4Measurement precision
If 3D matrix generation from sonar returns is performed to create detailed images, then image detail and object identification improve, but computational efficiency decreases
Solution Approach 1:
The system processes data in 2D dimensions (creating 2D slices at different depths) before combining them into 3D coordinates. This approach maintains high image detail precision by preserving all spatial information while improving computational efficiency, as 2D processing is less computationally intensive than direct 3D matrix generation.
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 the generation of detailed 3D sonar images in real-time, allowing for effective differentiation and tracking of objects, improving computational efficiency and reducing noise, thus enhancing underwater environment visualization.
Implementation Method 1
Sonar transducer elements, or simply transducers, may convert electrical energy into sound or vibrations at a particular frequency
Implementation Method 2
The transducer may receive the reflected sound (the 'sonar returns') and convert the sound energy into electrical energy
Implementation Method 3
These sonar returns provide time data that represents the time taken by the sound wave to travel from the transducer to the object and return as sonar returns to the transducer. Using the time in combination with the known speed of sound, a distance to the location of each sonar return may be determined
Data Source
AI summary
Methods, apparatuses, and computer program products are therefore provided for producing a 3D image of an underwater environment. An example method for providing an image of an underwater environment includes analyzing sonar returns to identify and display objects, such as fish or debris, in a 3D view. Such an image allows for differentiation between the sea floor and objects in a 3D sonar view. Some example methods provide for real-time tracking of fish. Further, the fish or other objects may be displayed over a continuous surface geometry based on sonar returns from a lake, sea, or river “floor.”