Progressive Receiver Gain Offset for Venue Positioning
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Solution Overview
Problem
Existing mobile device location determination methods using relative positioning technologies are resource-intensive due to the need to compensate for receiver gain differences between devices, leading to delays in providing accurate location information.
Innovation Solution
The implementation of a progressive receiver gain offset method, which initially estimates receiver gain offset at a coarse level of granularity and progressively refines it at increasingly finer levels, reducing computational complexity and resource consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If compensation for receiver gain differences is performed using traditional methods, then location accuracy is improved, but resource consumption and calculation time increase significantly
Solution Approach 1:
The patent segments the receiver gain offset estimation into multiple levels of granularity: venue-level estimation followed by region-level refinement. This hierarchical segmentation allows the system to perform coarse estimation first (using fewer resources) and then progressively refine the accuracy only for specific regions, rather than performing full precision calculations across the entire venue.
Solution Approach 2:
The patent performs preliminary venue-level receiver gain offset estimation before conducting detailed region-level localization. This preliminary action establishes a baseline compensation that can be applied broadly, reducing the computational burden required for subsequent precise location determination in specific regions.
2Measurement precision
If full precision compensation calculations are performed, then location accuracy is improved, but user experience deteriorates due to delays
Solution Approach 1:
The patent divides the compensation calculation into sequential stages: a fast venue-level estimation stage followed by a more precise but computationally intensive region-level refinement stage. This segmentation allows the system to provide quick initial location estimates while offering the option for progressive refinement, thereby reducing perceived delay for users.
Solution Approach 2:
The patent implements partial compensation by performing venue-level estimation for all locations and only performing the more computationally intensive region-level refinement when higher precision is specifically needed. This partial action approach balances accuracy requirements with time constraints, avoiding unnecessary full precision calculations.
3Measurement precision
If receiver gain offset estimation is performed at fine granularity levels, then location accuracy is improved, but computational complexity increases
Solution Approach 1:
The patent segments the computational domain into hierarchical levels: venue-level (coarse) and region-level (fine). By performing estimation at the coarser venue level first, the system reduces the overall computational complexity while maintaining the capability for fine-grained accuracy when needed in specific regions.
Solution Approach 2:
The patent performs preliminary venue-level receiver gain offset estimation that serves as a foundation for subsequent region-level refinement. This preliminary computation simplifies the overall problem by establishing baseline parameters that reduce the complexity of subsequent fine-grained calculations.
Data Source
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AI summary
The description relates to receiver gain offset. One example can obtain data sensed by a mobile device at a position. The example can evaluate the sensed data and survey data to identify a venue proximate to the position. The survey data of the venue can be organized into regions and then individual regions can be organized into sub-regions. The example can compare signal strengths of the sensed data to signal strengths of the survey data to identify the position relative to an individual region. The comparison can utilize a receiver gain offset estimation between the mobile device and another device that acquired the survey data. The example can refine the receiver gain offset estimation and attempt to identify the position relative to an individual sub-region within the individual region utilizing the refined receiver gain offset estimation.