Polarized Multistatic GPR Array for Real-Time Subsurface Detection
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Solution Overview
Problem
Current GPR systems fail to produce real-time radar tomography images of subsurfaces and are ineffective in detecting changes in objects over time due to high data storage costs and inefficient processing of previous scan data, particularly when detecting objects with short extent across the medium, such as cracks or pipelines.
Innovation Solution
A polarized detection system using a multistatic GPR array with transceiver antenna pairs oriented at different angles to preprocess and post-process return signals, generating reconstructed images and applying attribute- and topology-based change detection by comparing attributes and topology of new objects to a constellation database of previously detected objects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If current GPR systems use conventional single-static antenna arrays to scan subsurfaces, then the system structure is simple and easy to operate, but real-time radar tomography images cannot be produced and detection speed is insufficient
Solution Approach 1:
The system divides the antenna array into multiple independent transmitter and receiver elements arranged in a multistatic configuration. Each transmitter-receiver pair operates independently to collect radar returns from different geometric perspectives, enabling parallel signal acquisition that achieves real-time imaging capability while maintaining manageable system complexity through modular architecture
Solution Approach 2:
The system transitions from conventional single-static to multistatic antenna geometry, adding spatial dimensionality to the radar configuration. Multiple transmitters and receivers are positioned at different locations and orientations to create a three-dimensional sampling network, enabling real-time tomographic reconstruction without proportionally increasing overall system complexity
2Reliability
If GPR systems store and process large amounts of data from previous scans to detect changes, then change detection capability is improved, but data storage costs and processing time increase significantly
Solution Approach 1:
The system extracts only the essential change detection information from radar returns by comparing amplitude and phase characteristics between current and previous scans. Instead of storing and processing complete datasets, the system extracts differential features that indicate object changes, significantly reducing data storage requirements and processing time while maintaining reliable change detection capability
Solution Approach 2:
The system performs preliminary processing of radar signals by maintaining a database of previously detected objects and their characteristics. Before full change detection analysis, the system pre-processes returns by comparing them against the historical database to identify potential changes, enabling efficient processing by focusing computational resources only on suspicious areas rather than analyzing entire datasets
3Measurement precision
If conventional GPR systems use single-orientation antennas to scan subsurfaces, then the antenna array is simple to manufacture, but objects with short extent across the medium cannot be effectively detected
Solution Approach 1:
The system employs antennas with different orientation qualities at different positions within the array. Each transmitter-receiver pair is configured with specific polarization and angular orientations optimized for detecting objects with particular geometries. This local differentiation in antenna characteristics enables detection of objects with short extent across the medium while maintaining reasonable manufacturing complexity through standardized antenna components
Solution Approach 2:
The system uses asymmetric antenna orientations and polarizations rather than uniform configurations. Transmitters and receivers are positioned and oriented at different angles to create diverse viewing geometries, enabling detection of small or short-extent objects that would be invisible to symmetric single-orientation systems. The asymmetric configuration achieves superior detection precision using commercially available asymmetric antenna elements
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
Enables real-time detection of subsurface objects and changes by suppressing extraneous signals, improving detection of objects with short extent, and efficiently processing large datasets to identify new objects, thus enhancing the detection of buried landmines and other subsurface defects in various fields.
Implementation Method 1
ultra wideband ground-penetrating radar ('GPR') antennas
Implementation Method 2
When a radar signal strikes a subsurface object, it is reflected back as a return signal to a receiver
Implementation Method 3
DART-BASED DETECTION AND DISCRIMINATION UTILIZING WAVE POLARIZATION AND OBJECT ORIENTATION
Data Source
AI summary
A polarized detection system performs imaging, object detection, and change detection factoring in the orientation of an object relative to the orientation of transceivers. The polarized detection system may operate on one of several modes of operation based on whether the imaging, object detection, or change detection is performed separately for each transceiver orientation. In combined change mode, the polarized detection system performs imaging, object detection, and change detection separately for each transceiver orientation, and then combines changes across polarizations. In combined object mode, the polarized detection system performs imaging and object detection separately for each transceiver orientation, and then combines objects across polarizations and performs change detection on the result. In combined image mode, the polarized detection system performs imaging separately for each transceiver orientation, and then combines images across polarizations and performs object detection followed by change detection on the result.