ISTB Calibration with SS RAIM for Satellite Positioning Availability
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Solution Overview
Problem
There is a need for improved positioning accuracy and availability in wireless communication systems, particularly in 5G NR, due to challenges in calibrating inter/intra system/signal time biases (ISTBs) and outlier detection in positioning protocols.
Innovation Solution
Calibrate a set of ISTBs for a set of satellites operating on different frequency bands or types to meet a first accuracy threshold, and perform outlier detection using solution separation (SS) receiver autonomous integrity monitoring (RAIM) to obtain an output from a positioning engine (PE) module.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If ISTB calibration is performed for satellites on different frequency bands or types, then positioning accuracy is improved, but system complexity increases
Solution Approach 1:
The patent segments the satellite set into different groups based on frequency bands or satellite types, and performs ISTB calibration separately for each group. This allows targeted calibration that improves positioning accuracy while avoiding the need to calibrate all satellites uniformly, thus managing system complexity.
Solution Approach 2:
The patent introduces ISTB calibration parameters specific to different frequency bands and satellite types. By adjusting these parameters based on the characteristics of each satellite group, the system achieves higher positioning accuracy without requiring a complete redesign of the positioning system.
2Reliability
If outlier detection using SS RAIM is performed, then positioning reliability is improved, but computational complexity increases
Solution Approach 1:
The patent performs preliminary ISTB calibration before conducting outlier detection using SS RAIM. This preliminary calibration reduces the computational burden during the outlier detection phase by pre-adjusting the time bias parameters, thereby improving positioning reliability while managing computational complexity.
Solution Approach 2:
The patent implements a feedback mechanism where the results of outlier detection are used to refine the ISTB calibration. This iterative process improves positioning reliability by continuously adjusting the calibration parameters based on detected outliers, while the feedback loop ensures that computational resources are used efficiently.
3Measurement precision
If ISTB calibration is performed to meet accuracy threshold, then positioning accuracy is improved, but calibration time increases
Solution Approach 1:
The patent applies local quality calibration by focusing ISTB calibration efforts on specific satellite groups that have the greatest impact on positioning accuracy. By calibrating only the necessary subsets of satellites rather than all satellites uniformly, the system achieves the required accuracy threshold while minimizing calibration time.
4Reliability
If SS RAIM is applied in challenging environments, then positioning availability is improved, but system complexity increases
Solution Approach 1:
The patent implements dynamic SS RAIM that adapts to challenging environments by adjusting the outlier detection thresholds and calibration parameters based on real-time conditions. This dynamic approach improves positioning availability in difficult environments while avoiding the need for overly complex static systems.
Data Source
AI summary
Aspects presented herein may enable a UE to calibrate inter/intra system/signal time biases (ISTB) for a positioning engine (PE) and refine/re-calibrate the calibrated ISTB continuously to achieve an improved positioning accuracy and performance. In one aspect, a UE calibrates a set of ISTBs for a set of satellites to meet a first accuracy threshold, where at least two satellites in the set of satellites operate on different frequency bands or are associated with different satellite types. The UE performs, based on the set of calibrated ISTBs, an outlier detection using solution separation (SS) receiver autonomous integrity monitoring (RAIM). The UE obtains an output of a PE module based on outlier information from the outlier detection.