Multi-Sensor Noise Removal by Time-Frequency Signal Segmentation
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Solution Overview
Problem
Conventional methods using multiple reference sensors for noise removal from desired signals often result in insufficient accuracy due to the complexity of environmental noise types and the need for increased sensor numbers.
Innovation Solution
An information processing device and measurement system that acquires signal and noise measurement results from multiple sensors, divides them into frequency bands for each time segment, and performs signal processing to effectively remove noise using adaptive noise canceling techniques and frequency band division methods.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple reference sensors are used to remove various types of environmental noise, then the coverage of noise types is improved, but the measurement accuracy becomes insufficient due to the complexity of noise types and increased sensor numbers
Solution Approach 1:
The patent divides the time domain into multiple division segments and processes each segment separately through frequency band division. This segmentation approach allows the system to handle complex, time-varying noise characteristics more effectively by adapting to local variations in each segment, thereby improving measurement precision without requiring an excessive number of reference sensors.
Solution Approach 2:
The patent introduces frequency band division as an additional processing dimension beyond simple time-series filtering. By transforming the signal into multiple frequency bands and processing each band separately, the system enhances its ability to distinguish and remove different types of noise, improving accuracy while maintaining a manageable number of sensors.
2Adaptability or versatility
If the number of reference sensors is increased to cope with various environmental noise, then the noise coverage is improved, but the device complexity increases
Solution Approach 1:
The patent segments the frequency spectrum into multiple bands and processes each band independently. This allows the system to achieve comprehensive noise coverage across different frequency ranges using fewer reference sensors, as each sensor's data is utilized across multiple frequency bands through the division process, thereby reducing device complexity while maintaining adaptability.
Solution Approach 2:
The patent makes each reference sensor serve multiple functions by utilizing its data across multiple frequency bands. Through frequency band division, a single reference sensor contributes to noise removal in different frequency ranges, increasing the versatility and effectiveness of each sensor while reducing the total number of sensors required.
3Ease of manufacture
If time series filtering is applied to reference sensor data, then the processing is simple, but the noise removal accuracy is insufficient for complex environmental noise
Solution Approach 1:
The patent divides the time series into multiple division segments and applies frequency band division to each segment. This segmentation maintains relative processing simplicity while significantly improving noise removal accuracy, as each segment can be processed with appropriate filtering techniques tailored to its specific characteristics, avoiding the need for overly complex global processing.
Solution Approach 2:
The patent extends the processing from simple time-series filtering to two-dimensional processing by introducing frequency band division. This adds a frequency dimension to the processing, enabling more effective noise removal while maintaining computational feasibility through systematic organization of the processing steps.
Data Source
AI summary
Provided is an information processing device capable of improving the accuracy of removing noise from a result of measuring a desired signal when a plurality of reference sensors are used. An information processing device includes an acquisition unit configured to acquire signal measurement results of one or more signal sensors for measuring a mixed signal in which an objective signal and noise are mixed and noise measurement results of a plurality of reference sensors for measuring the noise and a signal processing unit configured to divide the signal measurement results and the noise measurement results acquired by the acquisition unit into a plurality of frequency bands for each of a plurality of division segments in a time domain and perform signal processing for removing the noise included in the mixed signal.