Warped RSS Vector for Indoor Localization Accuracy
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Solution Overview
Problem
Existing indoor localization techniques, such as Sequence Based Localization (SBL), face challenges in accuracy due to factors like RF propagation loss and multipath fading, especially in environments with sparse or moderately dense beacon deployments, where the number of access points with known locations is limited.
Innovation Solution
The Warped RSS Sequence Based Localization (WR-SBL) method applies a linear transformation to received signal strength (RSS) values to generate a warped RSS vector, which is then used for localization, reorganizing SBL faces uniformly across the localization space without requiring additional hardware or software changes to the existing WIFI infrastructure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If traditional SBL is used for indoor localization, then the system is simple to implement with polynomial time complexity, but localization accuracy deteriorates in environments with sparse beacon deployments due to RF propagation loss and multipath fading
Solution Approach 1:
The patent applies a linear transformation (warping) to the received signal strength values to change the parameter space. This transformation adjusts the RSS values to compensate for propagation effects, thereby improving localization accuracy without adding system complexity. The transformed RSS values are then used in the existing SBL algorithm framework.
Solution Approach 2:
The patent replaces the direct use of raw RSS values with a transformed version that accounts for propagation loss and multipath fading. This substitution effectively compensates for environmental effects without requiring additional hardware or complex system changes, maintaining polynomial time complexity while improving accuracy.
2Measurement precision
If the number of beacon nodes is increased to improve localization accuracy, then measurement precision improves, but device complexity and deployment cost increase
Solution Approach 1:
By transforming the RSS parameters, the patent enables accurate localization with fewer beacon nodes. The transformation compensates for propagation effects that would otherwise require more beacons to resolve, thus improving accuracy while reducing the number of required beacon deployments.
3Measurement precision
If fingerprinting methods are used to improve localization accuracy, then measurement precision improves, but the system requires extensive site surveys and calibration data collection
Solution Approach 1:
The patent replaces the fingerprinting approach with a transformed RSS-based method that does not require extensive site surveys. Instead of collecting and storing fingerprint data for the entire environment, the transformation method processes RSS values in real-time without pre-calibration, eliminating the time-consuming fingerprinting setup phase.
Solution Approach 2:
The system performs self-calibration through the linear transformation of RSS values, automatically compensating for propagation effects without requiring external calibration data or site surveys. The algorithm adapts to the environment autonomously using the transformed signal strength measurements.
Data Source
AI summary
A method for localizing a mobile device in a physical space based on radio signals received from transmitters in the physical space includes a step of transforming a received signal strength vector to produce a transformed received signal strength vector. Sequence based localization is performed on the transformed RSS vector with a different ideal sequence centroid table.