Reflective Sonar Beamforming via Acoustic Reflection
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Solution Overview
Problem
Conventional sonar beamforming techniques face scalability issues due to cubic growth in processing burden as the number of receivers increases, limiting resolution and requiring costly advanced processors, while frequency steering also struggles with scalability and high processing demands.
Innovation Solution
The reflective sonar imaging assembly uses a reflective surface to map angular information to pixel locations, reducing processing operations and allowing for a wide field of view without conventional beamforming, enabling scalable sonar imaging with lower hardware and processing requirements by transferring only pixel values for each range cell.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional beamforming techniques are used, then sonar imaging can be achieved, but the processing burden grows cubically with the number of receivers, limiting scalability and requiring costly advanced processors
Solution Approach 1:
The patent replaces the mechanical/computational beamforming system with an optical analog system using acoustic waves. The reflective surface performs the beamforming function through physical reflection and focusing of sound waves, eliminating the need for complex digital signal processing. This substitution transforms the cubic complexity computational problem into a linear complexity physical process, where processing burden scales with the number of receivers rather than the square or cube of receivers.
Solution Approach 2:
The patent introduces a reflective surface as an intermediary component between the receivers and the imaging process. This reflective surface acts as a physical mediator that performs angular-to-spatial mapping through its geometric properties, converting the complex beamforming computation into a simple geometric reflection process. The intermediary transforms the problem from one requiring extensive digital processing to one solved by physical optics principles.
2Measurement precision
If the number of receivers is increased to improve resolution, then imaging quality improves, but the processing burden increases cubically, eventually preventing further addition of receivers
Solution Approach 1:
The patent replaces the computational beamforming system with an optical analog system using acoustic waves. The reflective surface performs the beamforming function through physical reflection and focusing of sound waves, eliminating the need for complex digital signal processing. This substitution transforms the cubic complexity computational problem into a linear complexity physical process, where processing burden scales with the number of receivers rather than the square or cube of receivers.
Solution Approach 2:
The patent enables dynamic scaling of the receiver array without corresponding increases in processing complexity. By using the reflective surface for beamforming, the system can add receivers to improve resolution while the processing burden increases only linearly, allowing continuous scalability. The system dynamics change from being processing-limited to being only receiver-count-limited, enabling ongoing improvement of imaging resolution.
3Measurement precision
If frequency steering is used to obtain high resolution imaging from low channel count, then imaging resolution improves, but scalability remains an issue with increased processing demands
Solution Approach 1:
The patent replaces the computational beamforming system with an optical analog system using acoustic waves. The reflective surface performs the beamforming function through physical reflection and focusing of sound waves, eliminating the need for complex digital signal processing. This substitution transforms the cubic complexity computational problem into a linear complexity physical process, where processing burden scales with the number of receivers rather than the square or cube of receivers.
Solution Approach 2:
The patent changes the fundamental parameter of how beamforming is achieved - from digital frequency steering to physical acoustic reflection. By changing the beamforming mechanism from computational frequency manipulation to geometric acoustic reflection, the system achieves high resolution imaging without the associated processing demands. This parameter change fundamentally alters the complexity-scaling relationship.
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 reduces processing burdens and costs, allowing for high-quality sonar imaging with improved scalability and reduced hardware needs, as the processing burden grows linearly with the number of receivers, independent of frequency and angular resolution.
Implementation Method 1
the reflective surface may cause the sonar returns to be reflected to form reflected sonar returns
Data Source
AI summary
A reflective sonar imaging system is provided. The system includes a reflective sonar imaging assembly. The reflective sonar imaging assembly includes a receiving aperture, a reflective surface defining a concave shape, and a receiver positioned between the reflective surface and the receiving aperture. The system also includes a display and processing circuitry. The reflective surface is configured to cause sonar returns to be reflected as reflected sonar returns toward the receiver. The sonar returns enter the reflective sonar imaging assembly through the receiving aperture, and the receiver is configured to receive the reflected sonar returns. The receiver is configured to generate sonar return data using the reflected sonar returns that are received, and the processing circuitry is configured to receive the sonar return data and generate one or more sonar images based on the sonar return data. The display is configured to present the sonar image(s).