Modular Geoacoustic Processing System for Sensor Adaptability
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Solution Overview
Problem
Long arrays of geoacoustic sensors require a modular and flexible processing system capable of detecting, classifying, and localizing vibrational energy across diverse terrestrial environments, differing significantly from marine sonar applications, due to their extensive span and varied propagation conditions.
Innovation Solution
A modular processing system that includes a data acquisition system, low-level processing for signal detection and classification, and high-level processing for target tracking and alert generation, utilizing a distributed architecture and software implementation to analyze data from multiple channels in real-time, allowing for independent operation with various sensor types and flexible adaptation to different zones and environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a processing system is designed for marine sonar applications, then it can handle maritime sensor data, but it cannot effectively process geoacoustic sensor data from terrestrial environments with diverse propagation conditions
Solution Approach 1:
The patent implements a universal processing system that can handle multiple sensor types (geophones, fiber-optic sensors) and different environmental conditions through a common architecture. The system uses standardized data acquisition interfaces and unified processing algorithms that adapt to various sensor configurations without requiring separate dedicated systems for each sensor type or environment.
Solution Approach 2:
The processing system is divided into modular components including data acquisition modules, signal processing modules, and analysis modules that can be independently configured and deployed. This segmentation allows the system to be scaled and adapted to different geoacoustic applications while maintaining a consistent overall architecture, reducing complexity through manageable modular units.
2Area of stationary object
If the sensor array spans greater distances to cover larger areas, then the coverage area increases, but the diversity of propagation environments increases making processing more difficult
Solution Approach 1:
The system applies local processing techniques where signal characteristics are analyzed and processed according to the specific propagation conditions of each local zone. Different processing parameters and algorithms are applied to different segments of the sensor array based on the local environmental characteristics, allowing the system to handle diverse propagation conditions across large coverage areas effectively.
3Speed
If real-time processing is implemented for immediate situational awareness, then response time is reduced, but the computational load and system complexity increase
Solution Approach 1:
The system performs preliminary signal conditioning, filtering, and feature extraction at the data acquisition stage before full analysis. This preliminary processing prepares the data in advance, reducing the computational burden during real-time analysis and enabling faster response times without proportionally increasing overall system complexity.
Data Source
AI summary
A system for analyzing a plurality of channels of data received from a sensor array. The system includes a data acquisition system that receives and independently processes each channel. A low-level processing section receives each channel of processed data and identifies signals of interest in one channel. Signals of interest are stored in an event database. A high-level processing section analyzes data occurring over a preset duration of time and across multiple channels of data and communicates with an operator machine interface. The operator machine interface provides analysis to an operator. Further aspects of the system characterize the data in order to indicate the data source and alert the operator to signals having certain predefined characteristics.