AoA Resolving and AP Voting for Client Location
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Solution Overview
Problem
Current location techniques using Angle-of-Arrival (AoA) heat maps face efficiency issues due to high computational and storage requirements, particularly in generating heat maps bounded by a received signal strength indicator (RSSI) model, which can significantly burden system resources.
Innovation Solution
The method involves performing AoA resolving at multiple access points (APs) to generate AoA values, identifying cross points where these values intersect, and using AP voting to determine scores for candidate locations, thereby limiting computations to a small geographic region and distinguishing between line-of-sight and non-line-of-sight paths.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If AoA heat maps are generated for location techniques, then location accuracy is improved, but computational complexity and system resource consumption increase significantly
Solution Approach 1:
The patent segments the continuous AoA measurement space into discrete heat map grids, allowing the system to process location data in manageable discrete units rather than continuous values. This segmentation enables efficient computation by mapping AoA measurements to specific grid cells, reducing the computational burden while maintaining location accuracy.
Solution Approach 2:
The patent performs preliminary computation of AoA heat maps before actual location determination occurs. By pre-calculating and storing heat map data in a bounded region, the system avoids performing computationally intensive AoA calculations during real-time location tracking, significantly reducing system resource consumption during operation.
2Quantity of substance
If the heat map computation region is bounded by RSSI model, then storage requirements are reduced, but computation time increases
Solution Approach 1:
The patent applies local quality by creating heat maps only in the bounded region where the client device is likely to be located, as determined by the RSSI model. This localized approach stores detailed heat map data only where needed, while using coarser or pre-determined boundaries elsewhere, optimizing both storage efficiency and computation time by focusing resources on the relevant spatial region.
3Measurement precision
If multiple APs are involved in location determination, then location accuracy is improved, but the number of computations increases proportionally
Solution Approach 1:
The patent merges the heat map data from multiple access points into a unified location determination process. By combining AoA measurements and heat map information from multiple APs simultaneously, the system achieves improved location accuracy through triangulation and voting mechanisms while reducing redundant computations that would occur if each AP processed locations independently.
Data Source
AI summary
Embodiments herein describe performing AoA resolving to identify a plurality of AoAs corresponding to a multipath signal and then using AP voting to identify a location of the client device. AoA resolving enables an AP to identify the different angles at which a multipath signal reaches the AP. That is, due to reflections, a wireless signal transmitted by a single client device may reach the AP using multiple paths that each has their own AoA. The AP can perform AoA resolving to identify the AoAs for the different paths in a multipath signal. In one embodiment, the AoAs for two APs (or a subset of the APs) can be used to identify cross points or intersection points that represent candidate locations of the client device. A voting module can determine whether those cross points corresponds to AoAs identified by the remaining APs.