Infrared Matrix Sensor Identification via Pixel Cartography
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Solution Overview
Problem
Current infrared matrix sensor identification methods are vulnerable to falsification and alteration, and cooled sensors are limited to military applications due to cryostatic constraints, making traceability unreliable, especially as uncooled sensors with broader applications emerge.
Innovation Solution
A method that records and stores the unique physical characteristics of pixels in an infrared matrix sensor, creating a signature or identifier that requires physical modification to alter, allowing for secure traceability and identification, even in partially damaged sensors, using characteristics like defective or active states, gain, and noise levels, with optional coding for security.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If external marking or software marking is used to identify infrared matrix sensors, then the marking can be accessed and modified by third parties, but this compromises the reliability of traceability
Solution Approach 1:
The sensor uses its own inherent physical characteristics (pixel defects, noise patterns, gain variations) to create its identification signature. The sensor essentially identifies itself through its unique physical properties without requiring external marking systems that could be tampered with. This self-identification mechanism ensures that the signature cannot be altered by third parties since it is embedded in the sensor's physical structure.
Solution Approach 2:
The patent replaces mechanical or software-based marking systems with a physical characteristic-based identification system. Instead of using external marks that can be read, modified, or deleted, the system uses the inherent physical variations in the sensor pixels (defects, noise, gain) as the identification medium. This substitution eliminates the vulnerability to falsification inherent in external marking systems.
2Adaptability or versatility
If cooled type infrared matrix sensors are used, then the sensor can be manufactured with current technology, but the requirement for cryostatic apparatus severely limits applications to military uses only
Solution Approach 1:
The patent applies parameter changes by transitioning from cooled to uncooled sensor technology. This fundamental change in the operating parameter (temperature requirement) eliminates the need for cryostatic apparatus and enables the sensor to function in a wide range of applications including civilian, industrial, and consumer uses, not just military applications.
3Ease of manufacture
If uncooled infrared matrix sensors are manufactured, then the implementation is considerably simplified and applications are extended, but the current marking systems become insufficient to ensure effective traceability
Solution Approach 1:
The uncooled sensor creates its own identification signature based on its inherent physical characteristics during manufacturing. The pixel-level variations (defects, noise patterns, gain values) are measured and stored as the sensor's unique signature. This self-identification mechanism ensures traceability reliability even as manufacturing simplicity increases, since the signature is embedded in the sensor's physical structure rather than relying on external marking systems.
Solution Approach 2:
The identification signature is created during the manufacturing process itself, before the sensor is delivered to the end user. The physical characteristics of each pixel are measured and stored as part of the sensor's identity. This preliminary action ensures that the traceability information is already in place and cannot be altered or removed, maintaining reliability throughout the sensor's lifecycle.
4Measurement precision
If a mapping of all pixel characteristics is stored as identifier, then the signature is comprehensive and unique to the sensor, but the amount of data to be stored and processed increases significantly
Solution Approach 1:
The patent segments the pixel matrix into multiple groups or blocks, and selects representative characteristics from each segment rather than processing all pixels individually. This segmentation approach reduces the total data volume while maintaining the uniqueness and accuracy of the sensor signature, as the combined characteristics from multiple segments still provide sufficient discrimination between different sensors.
Solution Approach 2:
The system uses a partial mapping of pixel characteristics rather than requiring complete mapping of all pixels. By selecting a representative sample of pixel characteristics (excessive action in terms of capturing enough information for unique identification), the system achieves sufficient identification accuracy without the computational burden of processing every single pixel's complete characteristic set.
Data Source
AI summary
The method involves changing information relative to the position of pixel in a matrix and determining information relative to a characteristic e.g. faulty state, gain, offset value and noise level, of each of several pixels. The information pair associated to the respective pixels or cartography is together held in memory as sensor identifier. The cartography concerns the totality of pixels of the matrix possessing the characteristic, and is encoded.