Wireless Sensing Motion Detection Using Enhanced Channel Information
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Solution Overview
Problem
Existing wireless sensing technologies face challenges in efficiently utilizing multiple IoT devices for accurate motion detection and localization, particularly in indoor environments with multipath propagation and limited bandwidth.
Innovation Solution
The method involves receiving wireless signals through a wireless multipath channel, obtaining a time series of channel information, and computing enhanced channel information by transforming and emphasizing specific components. This enhanced information is then used to compute motion information, enabling effective sensing tasks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If multiple IoT devices are used for wireless sensing, then the coverage and sensing capability are improved, but the system complexity and difficulty of coordinating devices increase
Solution Approach 1:
The patent segments the wireless sensing system into multiple independent IoT devices (transmitters and receivers) that can be deployed throughout the venue. Each device independently performs sensing measurements, and the results are aggregated by a coordinator. This segmentation allows the system to achieve comprehensive coverage while keeping individual device complexity low.
Solution Approach 2:
The patent makes IoT devices universal by enabling them to serve multiple functions: they act as both transmitters and receivers for wireless sensing measurements, and can be configured for different sensing tasks. This multi-functionality reduces the need for specialized equipment and simplifies system deployment.
2Speed
If channel information is processed in the time domain, then the processing speed is improved, but the measurement precision for motion detection deteriorates
Solution Approach 1:
The patent transforms channel information from the time domain to the frequency domain using Fast Fourier Transform (FFT). This dimensional change enables the system to extract frequency-based features (such as Doppler shifts and multipath components) that are more indicative of motion, thereby improving measurement precision while maintaining processing efficiency through the computationally efficient FFT algorithm.
3Ease of manufacture
If all multipath components are processed equally, then the processing simplicity is improved, but the measurement precision for motion detection deteriorates
Solution Approach 1:
The patent applies local quality by differentiating the processing of different multipath components based on their characteristics. The system identifies and emphasizes components that are most sensitive to motion (such as those with significant Doppler shifts or time variations) while downweighting or ignoring stable components. This selective processing improves motion detection precision without requiring complete processing of all components.
Solution Approach 2:
The patent extracts and focuses on specific multipath components that are most relevant for motion detection. By using FFT and correlation analysis, the system identifies and extracts frequency components that indicate motion presence, separating these from irrelevant multipath components. This extraction approach improves measurement precision by concentrating computational resources on the most informative components.
4Measurement precision
If bandwidth is increased to capture more multipaths, then the measurement precision is improved, but the device complexity and energy consumption increase
Solution Approach 1:
The patent changes the processing parameters by applying FFT to transform time-domain signals into frequency-domain representations. This parameter transformation enables the system to extract motion information from frequency components without requiring increased physical bandwidth. The FFT operation effectively multiplies the information capacity within the existing bandwidth by creating frequency bins that reveal motion characteristics.
Data Source
AI summary
Wireless sensing using measurement enhancement is described. In one example, a described method comprises: receiving a wireless signal transmitted by a transmitter through a wireless multipath channel of a venue, wherein the received wireless signal differs from the transmitted wireless signal due to the wireless multipath channel and a motion of an object in the venue; obtaining a time series of channel information (TSCI) of the wireless multipath channel based on the received wireless signal, wherein each channel information (CI) comprises N1 CI components (CIC); for each respective CI having N1 CIC of the TSCI, computing a respective enhanced CI (ECI) having N2 CIC; computing a motion information (MI) based on the ECI of the TSCI; and performing a sensing task based on the MI.