Dynamic Threshold Sonar for Accurate Bottom Detection
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Solution Overview
Problem
Conventional sonar systems often provide erroneous bottom detections due to increased noise in sonar data, leading to inaccurate surface detection, particularly in noisy environments.
Innovation Solution
A dynamic threshold sonar system that captures sonar data, generates a bottom return threshold based on noise characteristics, and detects surfaces by identifying data samples exceeding the dynamically determined threshold, thereby improving detection accuracy and avoiding false positives.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional fixed threshold methods are used for surface detection, then the system operation is simple, but the measurement precision deteriorates in noisy environments leading to erroneous detections
Solution Approach 1:
The patent applies dynamics by transitioning from fixed thresholds to dynamically adjustable thresholds that adapt to changing noise conditions. The system automatically modifies detection thresholds based on real-time analysis of sonar data characteristics, allowing optimal performance across varying environmental conditions without manual intervention.
Solution Approach 2:
The patent implements feedback mechanisms where the system continuously monitors sonar data quality and noise levels, then uses this information to adjust detection thresholds. This closed-loop approach ensures that the threshold setting responds to actual data conditions, improving detection accuracy while maintaining automated operation.
2Measurement precision
If dynamic threshold adjustment is implemented to improve detection accuracy, then the measurement precision improves, but the device complexity increases
Solution Approach 1:
The patent applies self-service by enabling the sonar system to automatically analyze its own data quality and generate appropriate detection thresholds without external intervention. The system performs self-diagnosis of noise conditions and self-adjusts operational parameters, reducing the need for complex external control mechanisms while maintaining high detection accuracy.
3Productivity
If fixed search windows are used, then the processing speed is fast and simple, but the productivity deteriorates due to inability to adapt to varying bottom depths
Solution Approach 1:
The patent applies dynamics by implementing dynamically adjustable search windows that automatically adapt to varying bottom depths and detection requirements. The system modifies window parameters based on real-time conditions, enabling efficient operation across diverse environments without manual reconfiguration.
Solution Approach 2:
The patent implements universality by creating a search window system that can automatically adapt to multiple different operating conditions and depth ranges. The dynamic window management provides universal functionality across varying scenarios, eliminating the need for separate fixed-window configurations for different conditions.
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 enhances the accuracy of surface detection by dynamically adjusting thresholds and search windows based on noise levels, reducing false detections and providing efficient and reliable bottom depth determination.
Implementation Method 1
Sonar may be used to detect surfaces such as the bottom of a body of water
Implementation Method 2
a sonar receiver configured to receive acoustic returns from the sonar transducer and convert the acoustic returns into arrays of time differentiated sonar data samples
Data Source
AI summary
Techniques are disclosed for systems and methods to provide dynamic threshold sonar systems for mobile structures. A dynamic threshold sonar system may include sonar equipment configured to capturing sonar data by receiving and converting acoustic returns into arrays of time differentiated sonar data samples, and a processor communicatively coupled to the sonar receiver. The processor may be configured to receive the sonar data samples and determine noise characteristics of the sonar data. The processor may determine a threshold for surface detection based on the noise characteristics and detect a surface, and determine a distance to the surface, based on a comparison of the sonar data to the threshold that has been determined based on the same sonar data.