Indoor Positioning Using VLC and Pedestrian Dead Reckoning
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Solution Overview
Problem
Indoor positioning systems using visible light communications (VLC) face challenges when only one illumination source is detected, leading to ambiguity in device heading and positioning errors due to gaps in VLC data and limited computing power, especially when multiple light sources are not simultaneously in view.
Innovation Solution
Combining VLC with pedestrian dead reckoning (PDR) using a particle filter approach, where inertial sensors extrapolate candidate locations and headings based on initial detections, and camera images of light sources are used to refine estimates, even when VLC codes are not continuously detected, allowing for continuous indoor positioning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If VLC positioning is used with single illumination source detection, then device location can be determined, but heading ambiguity and positioning errors occur
Solution Approach 1:
The patent combines VLC positioning with PDR (pedestrian dead reckoning) to create a hybrid positioning system. When only one illumination source is detected, the system merges inertial sensor data from PDR with VLC measurements to determine device heading and position, eliminating the heading ambiguity that occurs with single-source VLC detection alone.
Solution Approach 2:
The patent introduces an intermediary approach by using a particle filter that integrates multiple data sources (VLC measurements and inertial sensor data) to resolve heading ambiguity. The particle filter acts as a mediator that combines information from different positioning methods to produce reliable heading determination even when VLC alone cannot provide it.
2Measurement precision
If continuous VLC detection is required for accurate positioning, then positioning accuracy is maintained, but system reliability decreases during VLC data gaps
Solution Approach 1:
The system prepares for VLC data gaps by maintaining a particle filter that continuously tracks possible device positions and headings. This cushioning approach ensures that when VLC data is unavailable, the system already has pre-computed candidate states that can be quickly evaluated, preventing positioning interruptions.
Solution Approach 2:
The patent implements a dynamic positioning system that adapts between VLC-based positioning and PDR-based positioning based on data availability. The particle filter dynamically adjusts its state estimates and weights depending on whether VLC data is currently being received, allowing seamless transition between different positioning modes to maintain continuous tracking.
3Reliability
If particle filter approach is used to combine VLC and PDR, then positioning reliability improves, but computational complexity increases
Solution Approach 1:
The system uses a particle filter with a limited number of particles rather than exhaustive computation. By using a sufficient but not excessive number of particles, the system achieves reliable positioning estimates while keeping computational complexity manageable for mobile device processors.
4Measurement precision
If multiple illumination sources are required simultaneously in view, then heading accuracy improves, but coverage range is limited
Solution Approach 1:
The patent creates a universal positioning system that can operate in multiple modes: when multiple illumination sources are visible, it uses VLC for accurate heading determination; when only one source is visible or none are visible, it switches to or integrates with PDR. This multi-functionality allows the system to maintain positioning capabilities across the entire indoor coverage area regardless of illumination source visibility.
Data Source
AI summary
A method comprising: A) using a mobile device's camera to capture a first image; B) by reference to a first illumination source appearing in the first image, determining first heading information of the mobile device; C) as the mobile device moves to a second location, using one or more inertial sensors of the mobile device to extrapolate a plurality of extrapolated first candidate locations and respective first candidate headings of the mobile device; D) at the second location, using the camera to capture a second image; E) by reference to a second illumination source appearing in the second captured image, determining a plurality of second candidate locations and respective second candidate headings of the mobile device; and F) based on a comparison of the extrapolated first candidate locations and headings with the second candidate locations and headings, determining at least one estimated location and respective heading of the mobile device.