Portable Communication Device Localization with Precomputed Signal Maps
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Solution Overview
Problem
Conventional location determination in indoor environments without a location beacon system is challenging, often relying on triangulation from cell towers with poor signal strength, leading to imprecise location estimation.
Innovation Solution
A portable communication device (PCD) uses a path-based scanning and data collection technique with a measuring wheel to create a precomputed environment dataset, refining odometry data for precise location determination by comparing wireless access point data with a stored dataset on the device, eliminating the need for remote computation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional location determination using cell tower triangulation is used in indoor environments without location beacon systems, then location determination can be achieved, but location precision deteriorates due to poor received signal strength
Solution Approach 1:
The system performs preliminary data collection by having a mobile device traverse the indoor environment and precompute a dataset mapping wireless signal characteristics to locations. This precomputed environment dataset is stored locally on the mobile device, enabling accurate location determination without requiring actual time-consuming server computations during use.
Solution Approach 2:
The patent creates a local copy of the environment dataset on the mobile device that replicates the information normally available only from remote servers. This copied dataset contains precomputed mappings between wireless signal characteristics and locations, allowing the device to determine location independently without external server assistance.
2Measurement precision
If path-based scanning and data collection is performed to create environment datasets, then location precision is improved, but device complexity and resource consumption increase
Solution Approach 1:
The patent extracts and refines only the essential components needed for location determination from the complete odometry data collection process. The environment dataset is simplified to contain only the necessary wireless signal characteristics and location mappings, removing unnecessary complexity while preserving location precision.
Solution Approach 2:
The mobile device performs self-service by collecting its own environment data and storing it locally. The device uses its own wireless subsystem and processors to compare received signals against the stored environment dataset, eliminating the need for external server computation resources and reducing overall system complexity.
3Power
If cloud servers are used to provide computation resources for location determination, then processing capability is improved, but loss of information and dependency on external systems increases
Solution Approach 1:
The system performs preliminary computation of the environment dataset locally on the mobile device during an initial data collection phase. This precomputed dataset is stored in the device's memory, enabling all subsequent location determination operations to be performed independently without requiring continuous connection to or computation resources from external cloud servers.
Solution Approach 2:
The mobile device becomes self-sufficient by storing the environment dataset locally and using its own onboard processors to perform location determination. The device compares wireless access point data against the stored dataset using its internal processors, eliminating dependency on external servers and maintaining full data independence throughout operation.
Data Source
AI summary
In an example, a method includes obtaining, at a portable communication device (PCD), an environment dataset comprising point data. Each point data has a position and respective wireless signal data at that position within a fixed environment. Wireless access point data is received from one or more wireless access points in the fixed environment and includes a unique access point identifier and received signal strength values. The PCD compares the wireless access point data and the environment dataset and determines a best match for the received wireless access point data in the environment dataset, which is identified as a location.