Tag: consumer

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Sub-Meter Accuracy in Consumer Smartphones: Advancements and Challenges in GNSS Positioning

By Shahabuddin Amerudin

Source: https://blog.junipersys.com

Sub-meter accuracy in the context of GNSS (Global Navigation Satellite System) refers to the capability of a receiver to determine its position with an accuracy of less than one meter, typically in the range of centimeters or decimeters. This level of accuracy is highly desirable for various applications, including augmented reality, precise navigation, surveying, agriculture, and other location-based services where high precision is crucial.

To achieve sub-meter accuracy, GNSS receivers need access to highly accurate and precise satellite positioning data. Traditional consumer-grade GNSS receivers, such as those found in smartphones, typically provide accuracy in the range of a few meters, which is sufficient for many general navigation purposes but not suitable for applications requiring high precision.

Several factors contribute to the challenge of achieving sub-meter accuracy in consumer smartphones:

  1. Limited Observables: Consumer smartphones typically have limited access to the satellite constellations and signals. For instance, they may receive only L1 (single frequency) signals from GPS and Galileo constellations, while multi-frequency access is limited to only certain satellites.
  2. Noisy Environment: Smartphones have compact designs, and their GNSS antennas are often shared with other communication hardware like Bluetooth and Wi-Fi receivers. This setup leads to noisy electromagnetic interference, reducing the signal quality from GNSS satellites.
  3. Signal Quality and Multipath: The quality of GNSS signals received by smartphones can be affected by factors like multipath, where the signals bounce off surrounding objects, causing inaccuracies in the position calculation.
  4. Real-Time Constraints: Achieving sub-meter accuracy in real-time is more challenging than post-processing data after collection. Real-time positioning requires fast and efficient algorithms that can handle the limited observations and noisy environment of smartphones.

To address these challenges and achieve sub-meter accuracy, researchers and developers have been working on innovative methodologies and algorithms. Some of the techniques used to improve accuracy in consumer smartphones include:

  1. Precise Point Positioning (PPP): PPP is a GNSS positioning technique that can achieve high accuracy by using advanced mathematical models to account for ionospheric and tropospheric errors. By combining dual-frequency measurements when available and using real-time ionospheric models, PPP can enhance the accuracy of single-frequency observations.
  2. SFDF Combination: Single-Frequency Dual-Frequency (SFDF) combination is a method to combine L1 (single frequency) and L5 (dual-frequency) observations in smartphones. This technique compensates for the lack of dual-frequency measurements in most satellites, improving the accuracy of positioning results.
  3. Signal-to-Noise Ratio (SNR) Weighting: SNR is a measure of the signal quality received by the smartphone’s GNSS receiver. Applying SNR weighting in the positioning algorithm can help filter out poor-quality measurements and improve the overall accuracy.
  4. Pre-processing Filters: Implementing pre-processing filters to remove poor-quality observations caused by multipath or other interference can enhance the accuracy of the final position solution.
  5. Real-Time Corrections: Accessing real-time corrections from GNSS augmentation systems or base stations can significantly improve the accuracy of the positioning results.

Despite the challenges, ongoing research and advancements in GNSS technology have made it possible to achieve sub-meter accuracy on consumer smartphones. By implementing sophisticated algorithms, utilizing real-time corrections, and optimizing the use of available observations, smartphone users can experience improved accuracy, making it suitable for various high-precision applications.

Suggestion for Citation:
Amerudin, S. (2023). Sub-Meter Accuracy in Consumer Smartphones: Advancements and Challenges in GNSS Positioning. [Online] Available at: https://people.utm.my/shahabuddin/?p=6588 (Accessed: 31 July 2023).
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A Review: Accuracy for the Masses: Real-Time Sub-Meter in a Consumer Receiver?

By Shahabuddin Amerudin

Accuracy for the Masses: Real-Time Sub-Meter in a Consumer Receiver?

Authors: Joshua Critchley-Marrows, Marco Fortunato and William Roberts

Publication Date: April 6, 2020

The article discusses a new methodology aimed at achieving sub-meter Global Navigation Satellite System (GNSS) accuracies in consumer devices such as smartphones. The goal is to enable applications like augmented reality and visually impaired navigation to function with higher precision. The article explores the challenges of achieving high accuracy in mass-market GNSS receivers, especially in the context of real-time positioning. It also introduces an alternative approach to Precise Point Positioning (PPP) to improve accuracy in challenging receiver environments.

Key Points:

  1. Challenges in Mass-Market GNSS Receivers: Mass-market GNSS receivers in consumer devices have limitations such as limited observation data from satellite constellations and restricted access to multi-frequency measurements. Additionally, the design of smartphones, with shared antennas and other communication hardware, can introduce noise and interference, affecting positioning accuracy. As a result, the typical accuracy achievable in ideal conditions is a few meters.
  2. Sub-Meter Accuracy Goals: The article sets a benchmark of achieving 50 cm accuracy for smartphone positioning due to the increasing demand for location-based apps requiring higher precision.
  3. The FLAMINGO Initiative: The methodology presented in the article is developed as part of the FLAMINGO initiative, which enables real-time PPP and Real-Time Kinematic (RTK) GNSS positioning on smartphones. The FLAMINGO service has achieved sub-meter positioning accuracies in real-time, but it relies on base station infrastructure within approximately 30 km of the user.
  4. Methodology Overview: The proposed methodology involves modifications to traditional GNSS processing. It includes a preprocessing stage to remove poor GNSS observables, a combination of single-frequency PPP with dual-frequency ionospheric-free combination, and signal-to-noise ratio and elevation-based noise weighting.
  5. Poor-Measurement Rejection: The preprocessing stage filters out poor GNSS observables using three detection strategies: Code-Minus-Carrier, Phase Range Rate, and Pseudorange Rate. These strategies identify and remove observations with errors caused by factors like multipath or cycle slips.
  6. SFDF Combination: To compensate for the mix of single-frequency and dual-frequency observations from smartphones or mass-market receivers, the methodology proposes the use of SFDF (Single Frequency, Dual Frequency) combination. This combination reduces error terms and improves vertical accuracy.
  7. Model Weighting: The methodology uses both elevation and signal-to-noise ratio (SNR) as weights in the GNSS processing algorithm. The combination of these weights enhances the precision of the positioning solution.
  8. Implementation and Test Results: The methodology is tested on real-time receiver trials, and the results are compared to an idealized post-processing scenario. The real-time solutions show less accuracy compared to the post-processed ideal case due to the challenges and limitations of smartphone environments. The SFDF model and SNR weighting show improvements in vertical accuracy.

Conclusion

The article presents a novel methodology to achieve sub-meter GNSS accuracies in consumer devices like smartphones. While the ideal case demonstrates high accuracy in post-processing, real-time implementation faces challenges due to the complex and noisy environment of smartphones. Nevertheless, the methodology shows promise for improving vertical accuracy and provides valuable insights for future GNSS research and development in consumer applications. Achieving sub-meter accurate PPP in real-time remains a goal with significant potential benefits.

Suggestion for Citation:
Amerudin, S. (2023). A Review: Accuracy for the Masses: Real-Time Sub-Meter in a Consumer Receiver? [Online] Available at: https://people.utm.my/shahabuddin/?p=6586 (Accessed: 31 July 2023).