Session C4a: Latest Advancement from GNSS Receiver and Localization Algorithm Manufacturers (10-Minute Presentations)

Barometric Integration for Wearable GNSS Receivers in Rapid Altitude Changes and Dense-Urban Environments
Song-Ying Li, Guang-Je Tsai, Tz-Chiau Su, Vic Li, Shi-Xian Yang, Airoha Technology
Location: Holiday 4-5 (Second Floor)
Date/Time: Thursday, Sep. 11, 5:20 p.m.

Global Navigation Satellite Systems (GNSS) are fundamental for outdoor navigation, offering precise positioning and velocity information. However, in dense urban environments, GNSS performance, particularly in altitude estimation, often deteriorates due to signal obstructions, multipath effects, and non-line-of-sight (NLOS) conditions. These challenges lead to in significant height inaccuracies and compromised trajectory reliability, which hinder seamless and stable navigation essential for various applications. Moreover, for the GNSS receivers in wearable devices, hardware limitations exacerbate these issues by leading to poorer signal reception. This results in less stable altitude measurements and greater fluctuations, undermining the reliability of navigation data. In our previous paper in 2023, “Performance Improvement of Wearable GNSS Navigation with Smart Sensor Aiding”, we integrated the 6-axis inertial measurement unit (IMU) to enhance the GNSS performance. However, with the incorporation of the IMU data, it primarily enhanced the planar positioning accuracy but offered limited improvement for vertical positioning. Consequently, the integration of a barometric sensor becomes crucial. Barometers provide complementary altitude data by measuring atmospheric pressure, which is less susceptible to the environmental interferences that plague GNSS signals. By leveraging barometric measurements, it is possible to enhance the accuracy of GNSS-derived altitudes and stabilize horizontal trajectory estimations. Additionally, barometer assisted GNSS systems can effectively mitigate altitude drift and improve overall positioning robustness in urban canyons where GNSS signal quality is frequently compromised. This integration not only optimizes vertical positioning but also contributes to more reliable planar navigation by providing consistent and continuous altitude references.
Airoha (a subsidiary of MediaTek) proposes a novel tightly integration with the barometer and GNSS engine together to achieve more accurate and stable altitude and position in challenging environments. There are two primary phases to effectively integrate barometric data with GNSS measurements, thereby enhancing altitude accuracy and trajectory stability. In the first phase, atmospheric pressure and temperature readings obtained from the barometric sensor are converted into relative altitude and relative vertical velocity using established pressure-altitude conversion formulas. Subsequently, the relative altitude information is integrated with the altitude and velocity from the GNSS receiver via Kalman Filter (KF). The KF serves as a robust tool for fusing the barometric and GNSS data, effectively mitigating the uncertainties and noise inherent in each sensor's measurements. The fusion process generates a refined estimate of both altitude and vertical speed, leveraging the complementary strengths of the barometer and GNSS. In the second phase, the fused altitude and velocity estimates are aided back into the position engine. By incorporating the enhanced altitude data, the position engine can correct and stabilize the GNSS-derived height measurements, thereby reducing altitude drift and improving overall positional accuracy. This feedback loop not only refines the vertical positioning but also contributes to more reliable horizontal trajectory calculations by providing consistent velocity references.
To validate the efficacy of our proposed method, we have designed a series of experiments targeting specific scenarios where our approach demonstrates significant advantages. Firstly, in environments characterized by rapid altitude changes, such as mountain climbing and skiing, our method provides more immediate altitude updates. This real-time responsiveness mitigates the limitations inherent in GNSS systems, where altitude estimations can be constrained or delayed due to signal degradation or weak reception of wearable application. By delivering timely altitude information, our approach enhances the reliability of activities involving swift elevation variations. Secondly, in dense urban areas where altitude changes are minimal, our method excels in maintaining altitude stability by effectively controlling excessive GNSS altitude estimation noise. Urban environments often present challenges such as multipath effects and signal blockages, which can introduce substantial noise into altitude measurements. Our approach filters out these inaccuracies, ensuring more precise and consistent altitude control. Lastly, for the scenarios involving indoor-outdoor transitions, such as moving through short tunnels or passing under bridges. In these cases, the transition from GNSS no fix to a valid fix might lead to huge altitude variation. Our method rapidly converges to accurate altitude estimates during these transitions, significantly enhancing precision during short outage periods. This rapid convergence is crucial for maintaining continuous and accurate altitude information, thereby improving the performance of systems reliant on seamless indoor-outdoor navigation.
In conclusion, Airoha’s GNSS chip exhibits the versatility by accommodating diverse barometer data inputs from different wearable devices, enabling real-time integration and time synchronization. Leveraging the Barometer-assisted algorithm, the chip achieves more immediate and stable altitude measurements compared to pure GNSS solutions. This enhancement facilitates the optimization of planar trajectories, resulting in improved accuracy and reliability. Experimental results also demonstrate the chip’s significant advantages across various scenarios, underscoring its potential to advance wearable technology applications. Overall, Airoha’s innovative GNSS chip offers a robust solution with sensor fusion for enhancing positional accuracy and performance in diverse environments.