UWB Sensor Localization Diagnosis via Anchor Clustering
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Solution Overview
Problem
Current wireless localization systems, particularly those using Wi-Fi or Bluetooth Low Energy, face inaccuracies due to sensor errors or failures, and existing diagnostic protocols are not time-efficient or cost-effective.
Innovation Solution
A method and system for diagnosing sensor performance of an ultra-wide band (UWB) sensor localization for a vehicle, which involves receiving sensor signals from UWB anchors and a tag, aligning the signals, determining intersections, clustering points, calculating clustering quality and variance, and identifying erratic anchors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If wireless localization systems use Wi-Fi or Bluetooth Low Energy, then coverage and accessibility are improved, but measurement precision deteriorates due to sensor errors and failures
Solution Approach 1:
The system changes the fundamental measurement parameter from radio wave triangulation (Wi-Fi/Bluetooth) to time-of-flight measurement (UWB). By measuring the actual time it takes for a signal to travel between anchors and tag at the speed of light, the system achieves centimeter-level precision while maintaining wide coverage area.
Solution Approach 2:
The patent replaces the mechanical/electrical signal processing system of Wi-Fi and Bluetooth with an electromagnetic time-of-flight measurement system. UWB uses extremely wide bandwidth electromagnetic pulses to measure distance directly through time measurement, substituting the traditional approach of inferring position from signal strength or triangulation.
2Reliability
If diagnostic protocols are implemented to identify sensor failures, then reliability is improved, but productivity deteriorates due to increased computation time and costs
Solution Approach 1:
The diagnostic system is fully automated and self-executing. The ECU automatically collects sensor data, performs consistency checks, identifies erratic anchors, and adjusts localization calculations without requiring external intervention or complex computation, making the process both reliable and efficient.
Solution Approach 2:
Instead of comprehensively analyzing all possible sensor failure modes with complex algorithms, the system applies a focused partial action by checking only the essential consistency relationships between anchor measurements. This targeted approach achieves sufficient reliability without excessive computation.
Data Source
AI summary
Systems and methods for diagnosing sensor performance of a UWB sensor localization are provided. The system comprises a UWB tag, at least four UWB anchors, and a gateway. The gateway comprises an ECU arranged to receive sensor signals from the UWB anchors. The ECU comprises a preprocessing module arranged to align the sensor signals defining aligned data and is arranged to determine intersections of the aligned data defining points of intersections. The system further comprises a clustering module arranged to cluster the points of intersections defining at least one cluster of points of the UWB anchors to calculate a clustering quality and a clustering variance of each of the at least one cluster. The ECU is arranged to find a clustering contribution of each anchor defining a first contribution low of one of the anchors and is arranged to determine an erratic anchor based the first contribution low.