Wireless Link Counting for Non-Line-of-Sight Motion Localization

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Solution Overview

Problem

Existing motion detection systems struggle to accurately determine the location and presence of objects in a space using wireless signals, particularly in environments without line-of-sight, and lack robustness in detecting motion and presence without optical sensors.

Innovation Solution

A method and system that utilize wireless communication devices to analyze channel information and beamforming state to generate probabilities of motion, employing a Bayesian estimation framework to refine these probabilities recursively, using wireless mesh networks and motion probe signals to detect and locate motion based on changes in channel response and beamforming properties.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If wireless signals are used to detect motion without optical sensors, then the system can operate in environments without line-of-sight, but the measurement precision and reliability of motion detection deteriorates

Engineering Contradiction:
Improveability to detect motion without line-of-sightVSAvoidaccuracy of motion location determination
Core Design Contradiction:
Adaptability or versatilityVSMeasurement precision

Solution Approach 1:

The system segments the detection space into multiple zones associated with different wireless communication devices. Each device independently monitors its local channel information and beamforming state, dividing the overall detection task into manageable segments that can be processed separately and then combined to achieve accurate location determination without requiring direct line-of-sight to the moving object

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

Wireless communication devices are given dual functionality: they serve both as communication nodes and as motion detection sensors. The same wireless signals used for communication are also utilized to extract channel information and beamforming state for motion detection, eliminating the need for dedicated optical sensors and enabling operation in environments without line-of-sight while maintaining detection capability

Inventive Principle:
Principle #6Universality (Multi-functionality)

2Reliability

If multiple wireless communication devices are used to improve detection accuracy, then the reliability of motion detection improves, but the device complexity and processing requirements increase

Engineering Contradiction:
Improverobustness of motion detectionVSAvoidcomplexity of processing channel information
Core Design Contradiction:
ReliabilityVSDevice complexity

Solution Approach 1:

The system merges the processing functions of multiple wireless communication devices by having them all report their channel information and beamforming state measurements to a central controller or coordinating device. This consolidation approach maintains the reliability benefits of multiple sensors while centralizing the complex processing tasks, preventing individual device complexity from escalating

Inventive Principle:
Principle #5Merging (Combining)

Solution Approach 2:

The system implements feedback mechanisms where wireless communication devices continuously monitor and report changes in channel information and beamforming state. This feedback loop enables the network to track motion events in real-time, with each device providing incremental information that collectively improves detection reliability without requiring any single device to handle the entire processing burden

Inventive Principle:
Principle #23Feedback

Data Source

PatentEP3963361B1Determining motion detected from wireless signals based on wireless link counting
Publication Date: 2026.01.28 COGNITIVE SYST
  • EP3963361B1 patent drawingFigure 1
  • EP3963361B1 patent drawingFigure 2A
  • EP3963361B1 patent drawingFigure 2B

AI summary

In a general aspect, a method for determining a location of motion detected by wireless communication devices in a wireless communication network includes obtaining a set of motion indicator values associated with a time frame. The set of motion indicator values indicates motion detected from wireless links during the time frame, each motion indicator value associated with a respective wireless link. The method also includes identifying a subset of the wireless links based on a magnitude of their respective motion indicator values relative to other motion indicator values in the set of motion indicator values. The method additionally includes generating count values for the wireless communication devices connected to the wireless communication network during the time frame. The method further includes generating a probability vector based on the count values and comprising values for the connected wireless communication devices.