Syntactic Landmine Detector Using GPR Impedance Sequences
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Solution Overview
Problem
Current landmine detection systems face challenges in distinguishing landmines from clutter, particularly due to the small size and reduced magnetic signatures of antipersonnel mines and soil anomalies, which limit their ability to image internal and external structures effectively.
Innovation Solution
The use of syntactic pattern recognition with Ground Penetrating Radar (GPR) signals to identify impedance discontinuities and process them using finite state machines and multi-correlators, allowing for the differentiation of landmines from clutter and other non-landmines by analyzing the unique spatial sequences of impedance discontinuities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional GPR signal processing techniques are used to improve detection sensitivity, then detection capability is improved, but the ability to discriminate landmines from clutter deteriorates due to increased false alarms from soil anomalies and detritus
Solution Approach 1:
The patent segments the GPR signal processing into distinct functional components: clutter removal module, feature extraction module, and pattern recognition module. This segmentation allows each module to specialize in specific tasks, improving overall discrimination accuracy while maintaining detection sensitivity.
Solution Approach 2:
The patent transitions from traditional one-dimensional signal amplitude analysis to multi-dimensional feature space analysis by extracting multiple features (time-domain, frequency-domain, and wavelet-domain features) and using neural networks to classify patterns in this expanded feature space, thereby improving discrimination capability.
2Measurement precision
If signal processing power is increased to improve landmine detection, then detection sensitivity is improved, but computational complexity and processing time increase
Solution Approach 1:
The patent performs preliminary clutter removal and feature extraction before final pattern recognition, preprocessing the signals to reduce complexity. By removing clutter early in the processing chain, subsequent pattern recognition operations work with simplified data, reducing overall computational burden.
Solution Approach 2:
The patent replaces traditional mechanical signal processing methods with neural network-based pattern recognition. The neural networks automatically learn and extract relevant features from the preprocessed signals, substituting complex manual feature engineering and reducing computational complexity while maintaining high detection sensitivity.
3Productivity
If traditional pattern recognition methods are used for landmine identification, then processing speed is maintained, but discrimination accuracy deteriorates due to variability in landmine signatures and soil conditions
Solution Approach 1:
The patent implements dynamic adaptation through neural networks that can learn and adapt to varying soil conditions and landmine types. The system dynamically adjusts its recognition patterns based on training data from different environmental conditions, maintaining high discrimination accuracy across diverse scenarios while preserving real-time processing capability.
Solution Approach 2:
The patent changes the parameter space by using multiple signal domains (time, frequency, wavelet) and transforming signals into these different representations. By analyzing patterns across multiple parameter domains rather than relying on single-domain features, the system achieves higher discrimination accuracy while maintaining processing efficiency through parallel computation.
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
This approach enables accurate discrimination and localization of landmines by generating spatial sequences that match known patterns, improving detection and reducing false alarms, even in challenging soil conditions and varying environmental factors.
Implementation Method 1
Ground penetrating RADARs (GPR) have been used for landmine detection for some 20 years
Implementation Method 2
the received signal is processed to locate discontinuities in impedance
Data Source
AI summary
Disclosed is a Syntactic Landmine Detector. The syntactic landmine detector processes a received signal from a ground penetrating RADAR which contains at least one spatial sequence, the spatial sequence containing relative spatial information locating impedance discontinuities. The spatial sequence is then associated with at least one physical characteristic of a landmine.