Acoustic Contact Tracking via Level Set Contour Evolution
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Solution Overview
Problem
Existing acoustic signal detection systems, such as sonar, face challenges in accurately imaging and tracking targets in highly cluttered environments due to embedded information loss between pings and inadequate compensation for ocean water characteristics, leading to poor detection and tracking performance.
Innovation Solution
The use of image processing methods, specifically the Level Set methodology, for extracting and analyzing acoustic data to predict signal features and kinematic characteristics of targets, enabling improved detection and tracking in cluttered environments by bounding regions of signal statistic consistency and change, and accommodating topological changes like target crossing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If acoustic signal detection systems use traditional signal processing methods, then the system structure remains simple, but the detection precision and tracking accuracy deteriorate in highly cluttered environments
Solution Approach 1:
The patent replaces traditional acoustic signal processing methods with image processing techniques. Acoustic signals are transformed into image representations (range-Doppler images, time-frequency images), and image processing algorithms (level set methods, contour evolution) are applied to extract contact information. This substitution enables precise tracking in cluttered environments by leveraging the visual pattern recognition capabilities of image processing rather than conventional signal analysis.
Solution Approach 2:
The patent transforms acoustic signal parameters (time, frequency, range, Doppler shift) into spatial image parameters (x, y coordinates, intensity). This parameter transformation allows the application of image processing algorithms to acoustic data, enabling the use of contour evolution and level set methods to track contacts through clutter by analyzing the spatial distribution and temporal evolution of signal features in the transformed domain.
2Loss of information
If acoustic signals are processed using conventional methods, then the processing time is short, but the loss of information between pings increases
Solution Approach 1:
The patent implements continuous tracking by evolving contours across multiple consecutive image frames. The level set methodology maintains and updates contact boundaries throughout the sequence, ensuring that information about contact position, shape, and motion is preserved continuously rather than being lost between discrete pings. This continuous action allows the system to track contacts through occlusions and maintain information across the entire observation period.
Solution Approach 2:
The patent performs preliminary transformation of acoustic signals into image representations before applying processing algorithms. By pre-processing the data into a format suitable for image analysis and establishing initial contours, the system prepares the information in advance for efficient tracking. This preliminary action reduces information loss by ensuring that all relevant features are captured and represented in the image domain before the tracking algorithm begins.
3Reliability
If traditional sonar systems are used, then the system cost is low, but the reliability of contact tracking in cluttered environments deteriorates
Solution Approach 1:
The patent replaces traditional acoustic signal processing with image processing methodology. Acoustic range-Doppler maps and time-frequency representations are converted into image formats, and level set-based contour evolution algorithms are applied to reliably track contacts. This substitution significantly improves tracking reliability in cluttered environments by using the robustness of image processing techniques to distinguish true contacts from background noise and clutter.
Solution Approach 2:
The patent introduces image representations as an intermediary between the acoustic sensor and the tracking algorithm. Acoustic signals are first transformed into range-Doppler images or time-frequency images, which serve as an intermediate representation that highlights contact features while suppressing clutter. This intermediary transformation enables the subsequent application of reliable contour-based tracking methods that are insensitive to the complexities of the original acoustic signal.
4Adaptability or versatility
If acoustic signals are analyzed without image processing, then the computational resources required are low, but the ability to resolve crossing and occluding targets deteriorates
Solution Approach 1:
The patent substitutes traditional signal analysis with image processing methods that are inherently better at handling topological changes. Image-based contour evolution and level set methods can naturally accommodate targets that cross, occlude, or change shape by tracking the continuous deformation of contours. This substitution provides the adaptability needed to resolve crossing and occluding targets, as the image processing framework can handle arbitrary contour configurations and topological transitions.
Solution Approach 2:
The patent employs dynamic contour evolution to track contacts that move, cross, or occlude one another. The level set methodology allows contours to deform, split, and merge dynamically in response to the underlying signal features. This dynamic approach enables the system to adapt to changing target configurations, automatically adjusting the contour topology to follow crossing or occluding contacts through their entire trajectories.
Data Source
AI summary
A system for processing one or more detection signals from an acoustic signal detection system to image and track one or more contacts within a medium including a computer configured to receive the detection signal and a computer readable medium operatively coupled to the computer, that is capable of applying an image processing method to one or more images derived from the received one or more detection signals to estimate the kinematic characteristics of the one or more contacts.