RF Device Signature via EMR Vector Space Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing device identification systems struggle to accurately differentiate between devices of the same make and model due to variations in electromagnetic radiation (EMR) emissions caused by service history, repairs, and physical changes, which are not effectively addressed by current vehicle detection methods.
Innovation Solution
A system comprising a radio frequency (RF) receiver, signal processor, and signature generator that samples EMR, generates pulses, selects those above a threshold, computes a vector space, and compares pulses to establish a unique device signature, using techniques like Fast Fourier Transforms and Singular Value Decomposition to filter noise and associate pulses with device identifiers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional vehicle detection methods are used to identify devices, then the system is simple to operate, but it cannot accurately differentiate between devices of the same make and model due to variations in EMR emissions
Solution Approach 1:
The patent segments the EMR signal into multiple frequency bands and analyzes temporal characteristics within each band. By dividing the complex EMR signal into manageable segments (frequency bands and time windows), the system can extract distinctive features from each segment and combine them for accurate device identification, resolving the contradiction between measurement precision and device complexity
Solution Approach 2:
The patent transitions from traditional single-dimension detection to multi-dimensional analysis by examining EMR signals across multiple frequency bands and temporal dimensions. This dimensional expansion allows the system to capture subtle variations in EMR emissions that differentiate devices of the same make and model, achieving high identification accuracy without excessive complexity
2Measurement precision
If EMR sampling and spectral analysis are performed to capture device characteristics, then device identification accuracy is improved, but the processing time and computational resources increase
Solution Approach 1:
The patent performs preliminary action by pre-establishing EMR signatures for devices during a registration phase. These pre-computed signatures are stored for rapid comparison during operational identification, eliminating the need for complex real-time analysis and significantly reducing processing time while maintaining high differentiation capability
Solution Approach 2:
The patent applies partial action by selecting and analyzing only the most informative frequency bands and temporal characteristics rather than processing the entire EMR spectrum in detail. This selective approach captures sufficient device differentiation information while minimizing computational overhead and processing time
Data Source
AI summary
Exemplary systems and methods are directed to establishing a signature for a device emitting electromagnetic radiation (EMR). The system includes a radio frequency (RF) receiver, a signal processor, and a signature generator. The RF receiver samples detected EMR, generate pulses having characteristics that are a function of the EMR, and select generated pulses in a spectral band having energy above a predetermined threshold. The signal processor establishes a set of correlated pulses, computes a vector space associated with the set of correlated pulses, and compares each pulse in the set of correlated pulses to a basis of the vector space for establishing a device signature, and associates pulses having a threshold percentage of energy within the basis in a database with a device identifier.