Feasibility of Consumer Grade GNSS Receivers for the Integration in Multi-Sensor-Systems

Area of Science:

• Geomatics Engineering
• Signal Processing
• Sensor Technology

Background:

• Global Navigation Satellite System (GNSS) devices are increasingly integrated into various applications, demanding low-cost, compact, and power-efficient solutions.
• High precision is crucial for applications like navigation, geo-monitoring, and multi-sensor systems, necessitating access to raw GNSS data (carrier phase, code ranges, Doppler, signal strength).
• System integration requires a thorough understanding and quantification of the noise characteristics in GNSS observations.

Purpose of the Study:

• To benchmark and quantify the stochastic properties of consumer-grade GNSS receivers.
• To evaluate the performance of consumer-grade GNSS receivers against geodetic-grade receivers.
• To determine the suitability of consumer-grade GNSS receivers for high-precision applications and multi-sensor system integration.

Main Methods:

• A zero-baseline benchmark analysis was employed to quantify the stochastic properties of GNSS observations.
• Performance evaluation involved comparing consumer-grade GNSS receivers with geodetic-grade GNSS receivers.
• Stochastic techniques, including modified Allan standard deviation and code-minus-carrier combinations, were utilized to analyze noise characteristics.

Main Results:

• Consumer-grade GNSS receivers exhibit performance highly similar to geodetic-grade receivers, despite inherent technical limitations.
• Carrier-phase noise was found to be normally distributed with approximately 2 mm of noise.
• Code-range noise was quantified between 0.5-0.8 m, consistent across various stochastic analyses.

Conclusions:

• Consumer-grade GNSS receivers are suitable for high-precision applications, demonstrating comparable performance to geodetic receivers.
• The quantified noise parameters (carrier-phase and code-range) are essential for integrating GNSS receivers into multi-sensor systems.
• Understanding the stochastic properties of GNSS observations is key to unlocking the full potential of consumer-grade devices in advanced applications.