Inertial Measurement Unit Location Recognition via Path Signature Matching
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Solution Overview
Problem
Existing methods for determining a person's location using an inertial measurement unit (IMU) are prone to significant errors due to noise and biases in the sensors, especially as time from the last known position increases.
Innovation Solution
The system identifies locations of interest (LOIs) within an environment, determines a reference path signature for each LOI, and stores these signatures with corresponding LOI data. It then generates a current path signature for a moving device and compares it to the stored reference signatures to determine the device's location.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If continuous integration techniques are used to estimate position from IMU signals, then position estimation can be performed without external infrastructure, but measurement precision deteriorates significantly over time due to sensor noise and biases
Solution Approach 1:
The system performs preliminary action by capturing and storing reference IMU signal sequences at known locations before actual navigation. These reference sequences are obtained in advance during a calibration phase, allowing the system to compare current IMU readings against pre-captured references to determine position, thereby avoiding cumulative integration errors.
Solution Approach 2:
The system creates copies of IMU signal sequences at known reference locations and stores them for later comparison. Instead of continuously integrating noisy IMU data, the system captures the characteristic signal patterns (copies) at specific locations and matches them against current readings, preserving measurement precision without requiring external infrastructure.
2Reliability
If RF-based RTLS technologies such as beacon and receiver devices are deployed, then location estimation reliability improves in indoor environments, but device complexity and infrastructure requirements increase
Solution Approach 1:
The system enables self-service by using the IMU device itself to both navigate and determine position without external RF infrastructure. The IMU unit captures its own signal sequences, stores reference patterns locally, and performs autonomous position determination by comparing current readings against its own stored references, eliminating the need for beacons, receivers, or complex deployment infrastructure.
Solution Approach 2:
The IMU device performs multiple functions: it serves as both the navigation sensor and the position determination system. By capturing, storing, and comparing its own signal sequences, the single IMU unit accomplishes what would otherwise require separate infrastructure components, reducing overall system complexity while maintaining reliability.
Data Source
AI summary
Methods and program code for determining a location of a device within an environment and for calibrating the environment. Example computer readable medium for determining a location of a device within an environment comprises program code that when executed by one or more processors, causes the one or more processors to determine a current path signature for a device moving within an environment, compare the current path signature with a stored reference path signature corresponding to a location of interest (LOI) within the environment, and if it is determined that the current path signature corresponds to the stored reference path signature, determine the location of the device to be the same as a location of the LOI within the environment.