Autonomous Acoustic Target Detection and Classification System
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Solution Overview
Problem
In underwater environments, detecting and classifying acoustic signals of interest is challenging due to significant noise levels, which mask the signals of interest, and existing technologies require complex systems with high processing power, memory, and communication capabilities, limiting real-time autonomous detection and tracking capabilities in unmanned marine vehicles.
Innovation Solution
A method and system for autonomous joint detection and classification of acoustic targets using hydrophone sensors, where acoustic signals are transformed into the frequency domain, noise levels are estimated and normalized, and a joint detection-classification operation is performed using embedded processors on marine vehicles, enabling real-time processing and tracking of targets without human intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If complex disparate system components (sensors, transceivers, computing devices) are used to analyze acoustic signals, then measurement precision and detection accuracy improve, but device complexity and processing requirements increase significantly
Solution Approach 1:
The patent combines multiple disparate system components (sensors, transceivers, computing devices) into an integrated acoustic signal processing system that performs detection, classification, and tracking functions unified within a single platform, reducing overall system complexity while maintaining measurement precision
Solution Approach 2:
The system implements multi-functional capabilities where a single integrated platform performs acoustic signal detection, noise filtering, target classification, and tracking operations, eliminating the need for separate specialized components for each function
2Productivity
If real-time autonomous processing is implemented in unmanned marine vehicles, then productivity and response time improve, but use of energy and computational resources increase beyond available capacities
Solution Approach 1:
The patent segments the acoustic signal processing into distinct functional stages (detection, classification, tracking) that can be executed sequentially or in parallel, allowing the system to manage computational load and energy consumption while maintaining real-time processing capability
Solution Approach 2:
The system implements selective processing where not all acoustic signals receive full processing depth - only signals meeting detection thresholds undergo complete classification and tracking, reducing overall computational energy requirements while maintaining productivity for significant targets
3Measurement precision
If noise filtering and signal enhancement are applied to improve signal detection, then measurement precision improves, but processing time and computational complexity increase
Solution Approach 1:
The patent applies preliminary noise characterization and filtering based on pre-established noise models and statistical parameters, allowing rapid signal enhancement without requiring extensive real-time computational analysis, thus reducing processing time while improving measurement precision
Data Source
AI summary
Systems and methods are disclosed for autonomous joint detection-classification of acoustic sources of interest. Localization and tracking from unmanned marine vehicles are also described. Based on receiving acoustic signals originating above or below the surface, a processor can process the acoustic signals to determine the target of interest associated with the acoustic signal. The methods and systems autonomously and jointly detect and classify a target of interest. A target track can be generated corresponding to the locations of the detected target of interest. A classifier can be used representing spectral characteristics of a target of interest.