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Related Experiment Video

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Simulating Imaging of Large Scale Radio Arrays on the Lunar Surface

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A Quad-Constellation GNSS Navigation Algorithm with Colored Noise Mitigation.

Xianqiang Cui¹, Tianhang Gao¹, Changsheng Cai¹

¹School of Geosciences and Info-Physics, Central South University, Changsha 410083, China.

Sensors (Basel, Switzerland)

|January 1, 2020

Summary

Colored noise in kinematic Global Navigation Satellite System (GNSS) positioning degrades accuracy. A new Kalman filter algorithm effectively mitigates this noise, improving 3D positioning accuracy by up to 25.1% in quad-constellation navigation.

Keywords:

colored noise functional model fitting filter navigation quad-constellation GNSS single point positioning

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Area of Science:

Geomatics Engineering
Navigation Systems
Signal Processing

Background:

Kinematic positioning accuracy is significantly degraded by colored noise.
Existing methods struggle to effectively mitigate colored noise in multi-constellation GNSS.

Purpose of the Study:

To propose and evaluate a Kalman filter-based algorithm for colored noise mitigation in quad-constellation GNSS kinematic positioning.
To assess the impact of colored noise on positioning accuracy under varying satellite visibility and road conditions.

Main Methods:

Developed observation and state colored noise models using past epoch residuals.
Implemented a Kalman filter for predicting and mitigating colored noise in real-time.
Conducted kinematic single point positioning (SPP) experiments using integrated GPS, GLONASS, BDS, and Galileo.

Main Results:

The proposed colored noise model effectively mitigates noise, especially with good satellite visibility.
Three-dimensional positioning accuracy improved by up to 25.1% after colored noise handling.
Accuracy improvements ranged from 16.6% to 27.3% depending on satellite elevation cut-off angles and road patterns.

Conclusions:

The Kalman filter-based approach successfully models and mitigates colored noise in quad-constellation GNSS.
The algorithm enhances kinematic positioning accuracy across diverse operational scenarios.
Effective colored noise mitigation is crucial for high-accuracy GNSS applications.