Locating Device Using Singular Value Decomposition for Indoor Positioning
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Solution Overview
Problem
Current localization methods, such as GPS, face issues with availability and power consumption, and often have low accuracy due to strong constraints like the need for accurate absolute positions of reference, especially in triangulation-based solutions.
Innovation Solution
A locating device and method that uses a memory to store distance data between anchors and mobile sources, employing singular value decomposition and least squares minimization to calculate transformation matrices, allowing for precise localization with reduced constraints, particularly using a matrix product of Euclidean distance data with specific square matrices to determine coordinates of anchors and mobile sources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If GPS is used for localization, then availability and ease of operation are improved, but power consumption increases and accuracy deteriorates in indoor environments
Solution Approach 1:
The patent replaces GPS satellite-based electromagnetic positioning with a local Wi-Fi triangulation system using multiple access points. The mobile device determines position by measuring signal strengths from at least three Wi-Fi access points and calculating distances based on signal attenuation, substituting the GPS mechanical/electromagnetic system with a software-based triangulation approach that works independently of satellite availability.
2Use of energy by moving object
If triangulation-based localization is used, then power consumption is reduced compared to GPS, but measurement precision deteriorates due to constraints like needing accurate absolute positions of reference
Solution Approach 1:
The patent changes the reference parameter from requiring accurate absolute positions to using relative position measurements. Instead of needing known absolute coordinates of access points, the system uses signal strength measurements (RSSI) to calculate relative distances between the mobile device and multiple access points, then triangulates position based on these relative measurements, eliminating the constraint of requiring precise absolute position data.
Solution Approach 2:
The patent introduces signal strength (RSSI) as an intermediary parameter between the mobile device and access points. Rather than directly measuring distance or requiring absolute positions, the system uses signal attenuation as a mediator to infer distance information, which is then converted into position data through triangulation mathematics.
3Device complexity
If traditional triangulation methods are used, then device complexity is reduced, but measurement precision deteriorates due to strong constraints on reference position accuracy
Solution Approach 1:
The patent segments the localization problem into distinct mathematical steps: first establishing a coordinate system using at least three access points with known relative positions, then separately calculating the mobile device's position by triangulating from those established coordinates. This segmentation allows each step to be optimized independently, improving overall precision without proportionally increasing complexity.
Data Source
AI summary
A locating device, which includes a memory arranged to receive data concerning the distance between a plurality of anchors and one or more mobile sources at a plurality of locations different to each other. The locating device includes a decomposer, a reducer, and a solver arranged to return a matrix of coordinates of the anchors and a matrix of coordinates of the locations.