Indoor Localization Algorithm Resolving Signal Ambiguity
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Solution Overview
Problem
Existing indoor positioning systems (IPS) face challenges in providing accurate location and navigation data within indoor environments, particularly due to the requirement of unobstructed line of sight for GPS and the limitations of fingerprinting systems which require extensive offline calibration and are sensitive to environmental changes.
Innovation Solution
The implementation of a precise indoor localization algorithm (PILA) that uses a combination of range and angle of arrival (AoA) matrices, along with techniques such as front-back detection, stationary node detection, AoA error correction, and field of view (FOV) filtering, to generate a radio frequency (RF) map and accurately track wireless electronic devices within indoor environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If GPS systems are used for indoor positioning, then location data can be provided wherever unobstructed line of sight to satellites is available, but accurate location and navigation data cannot be provided for indoor environments
Solution Approach 1:
The patent introduces wireless transceivers and RF signal infrastructure as intermediaries between GPS satellites and indoor devices. These transceivers receive satellite signals and re-transmit them indoors, enabling indirect positioning in environments where direct satellite contact is blocked by building structures
Solution Approach 2:
The positioning system is segmented into multiple components: outdoor GPS receivers, indoor wireless transceivers, and mobile devices with positioning capabilities. This segmentation allows the system to operate differently in outdoor versus indoor environments, maintaining reliability across both settings
2Measurement precision
If fingerprinting systems are used for indoor positioning, then approximate indoor localization can be provided, but extensive offline calibration with hundreds or thousands of Wi-Fi devices is required
Solution Approach 1:
The system performs preliminary mapping of RF signal characteristics and wireless infrastructure deployment before actual positioning operations. This preliminary action establishes the positioning framework without requiring extensive real-time calibration during operation
Solution Approach 2:
The patent creates a universal positioning framework that works across different indoor environments using standard wireless transceivers and RF signals. This multi-functional approach eliminates the need for environment-specific calibration by making the system adaptable to various settings through software-based positioning algorithms
3Measurement precision
If fingerprinting systems are used for indoor positioning, then localization can be achieved, but the system is sensitive to environmental changes such as obstructions, door openings, and atmospheric variations
Solution Approach 1:
The system continuously monitors RF signal characteristics and compares them against stored profiles, using feedback loops to adjust positioning calculations in real-time. This feedback mechanism compensates for environmental changes by detecting signal variations and correcting position estimates accordingly
Solution Approach 2:
The positioning system dynamically adapts to changing environmental conditions by updating signal profiles and adjusting positioning algorithms in real-time. Rather than relying on static fingerprint maps, the system evolves its understanding of the environment to maintain accuracy despite obstructions, door movements, and atmospheric variations
4Ease of operation
If transceivers are used for wireless communication, then data can be transmitted wirelessly over network channels, but front-back ambiguity occurs where devices cannot determine signal direction
Solution Approach 1:
The patent employs asymmetric antenna configurations and signal processing techniques that create directional signal patterns. By making the transmission and reception characteristics asymmetric in different directions, the system enables mobile devices to determine their orientation and the direction of incoming signals, resolving the front-back ambiguity inherent in symmetric omnidirectional transceivers
Data Source
AI summary
Methods and devices useful in performing precise indoor localization and tracking are provided. By way of example, a method includes locating and tracking, via a first wireless electronic device, a plurality of other wireless electronic devices within an indoor environment. Location ambiguity mitigation is performed using characteristics of signals received by a reference node used to generate a radio frequency map of electronic devices.


