IMU-Enhanced Two-Way Ranging for Multipath Error Correction
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Solution Overview
Problem
Existing two-way ranging (TWR) systems suffer from precision issues due to noise and multipath interference, especially in unstructured environments, causing measurement errors and reduced precision in the presence of non-line-of-sight (NLOS) conditions, which are prominent at higher frequencies, and reflected signals, especially in unstructured environments.
Innovation Solution
A system and method for inertial measurement unit (IMU)-enhanced TWR that integrates IMU circuitry with radio and processor components to enhance precision by using dead-reckoning estimates, Bayesian filtering, and NLOS identification algorithms, improving precision and reducing size, weight, power, and cost (SWAPC) without additional infrastructure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional TWR systems are used in unstructured environments, then device complexity remains low, but measurement precision deteriorates due to noise and multipath interference
Solution Approach 1:
The patent combines TWR radio ranging with IMU dead-reckoning into a unified positioning system. The IMU provides continuous motion tracking that complements the intermittent TWR measurements, creating a hybrid system that leverages the strengths of both technologies to achieve centimeter-level precision in challenging environments.
Solution Approach 2:
The patent introduces Bayesian filtering as an intermediary processing layer that fuses TWR range measurements with IMU odometry data. This filtering mechanism reconciles the two different measurement types, eliminating multipath errors and noise while maintaining system simplicity by using software-based integration rather than additional hardware infrastructure.
2Speed
If TWR measurements are taken at higher frequencies to improve response time, then speed increases, but measurement precision worsens due to prominent multipath interference
Solution Approach 1:
The patent implements feedback through continuous IMU monitoring that tracks device motion between TWR measurements. This feedback mechanism allows the system to predict expected position changes and compare them with actual TWR measurements, identifying and correcting multipath errors in real-time while maintaining high update rates.
Solution Approach 2:
The patent dynamically adjusts the fusion of TWR and IMU data based on motion characteristics. During periods of high motion or suspected multipath interference, the system relies more heavily on IMU dead-reckoning, while during stable periods it incorporates more TWR measurements, optimizing both speed and precision adaptively.
3Measurement precision
If additional infrastructure is added to improve TWR precision, then measurement precision improves, but device complexity and cost increase
Solution Approach 1:
The patent enables the system to self-correct for multipath errors and noise using only the IMU sensors already present in modern devices. The IMU provides self-contained motion tracking that does not require external infrastructure, allowing the system to maintain high precision through software-based fusion algorithms rather than additional hardware.
Data Source
AI summary
In an approach to two-way ranging, a system includes a first entity. The first entity includes: a first inertial measurement unit (IMU) circuitry configured to measure a first change in position of the first entity; radio circuitry configured to communicatively couple with one or more additional entities; and processor circuitry. The processor circuitry is configured to: measure a range to a second entity using two way ranging (TWR); receive an odometry measurement from the second entity; and determine a range estimation to the second entity based on a previous range to the second entity and the odometry measurement.