Multi-Sensor State Data Integration Using Response Function Normalization
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Solution Overview
Problem
Existing sensor systems face limitations in capturing a wide range of intensity and spectral sensitivity, leading to inaccurate and less meaningful representation of environmental states due to deviations in signal processing and manipulation, especially when combining data from multiple sensors with different sensitivities.
Innovation Solution
A method and system for integrating and processing sensor signals by applying intensity and spectral response functions to determine accurate energy values, followed by normalization and compositing these values for meaningful display, reversing the conventional conversion and manipulation processes to maintain data integrity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If sensor data from multiple sensors with different sensitivities is integrated using conventional methods, then the quantity of data is increased, but the measurement precision deteriorates due to signal processing deviations
Solution Approach 1:
The patent applies parameter changes by transforming sensor output values through intensity response functions and spectral response functions. This converts data from sensors with different sensitivities and spectral ranges into a common reference frame, allowing precise integration while preserving measurement accuracy across multiple sensors with varying characteristics
Solution Approach 2:
The patent introduces intermediary processing steps including intensity response function application, spectral response function application, and normalization. These intermediaries act as mediators that harmonize data from different sensors before integration, eliminating processing deviations while maintaining the quantity benefits of multi-sensor data
2Adaptability or versatility
If sensor output values are converted and manipulated to match different sensitivities, then the adaptability of the system is improved, but the device complexity increases due to additional processing steps
Solution Approach 1:
The patent implements universality by creating a standardized processing pipeline that handles multiple sensor types through common intensity response functions and spectral response functions. This universal approach enables the system to integrate sensors with different sensitivities and spectral ranges using the same methodology, reducing operational complexity despite the multi-step process
Solution Approach 2:
The patent uses parameter changes through intensity response functions and spectral response functions to adapt sensor outputs. While this adds processing steps, it provides a systematic and automated approach that manages complexity through consistent mathematical transformations rather than ad-hoc adjustments for each sensor type
3Ease of operation
If conventional sensor data integration methods are used, then the ease of operation is maintained, but the reliability of the composite data deteriorates under extreme conditions
Solution Approach 1:
The patent applies preliminary action by pre-characterizing each sensor's intensity response and spectral response before integration. This advance preparation creates lookup tables and response functions that automate the integration process, maintaining ease of operation while ensuring reliable and accurate composite data even under extreme environmental conditions through pre-computed correction factors
Data Source
AI summary
The invention relates to sensor system arrangements and configurations. In particular, the invention provides methods, devices, systems and computer program products for integrating, compositing and/or processing data representing a measurable state within a region-of-interest, that has been received from a plurality of sensors that respectively have different input sensitivities, spectral sensitivity ranges and/or input capture ranges.