Optimal GNSS Signal Tracking Loop Design Based on Plant Modeling

Conventional research for signal tracking of the Global Navigation Satellite System (GNSS) uses a loop filter to minimize the effect of measurement noise. Although for a few decades, research into the optimal GNSS tracking loop has been based on similarity between signal tracking and general control loop theory, it has mainly focused on optimal estimator, or shown vulnerability for high dynamic signal tracking. To enhance the performance of the optimal signal tracking loop, this paper proposes new plant modeling for optimal GNSS signal tracking that consists of both optimal estimator and controller. The proposed plant modeling is able to maximize the performance of the optimal signal tracking loop due to the relationships between code and carrier tracking, and between the frequency and phase of the carrier. In addition, the plant clearly defines a relationship between the general control loop and GNSS tracking loop, so that the plant is ready to be applied to various control theories for GNSS signal tracking. To assess the performance of the proposed plant modeling, we implement a linear quadratic Gaussian (LQG) tracking loop based on the new proposed plant and process simulation data. Comparison of the processing results to those of conventional research shows improved performance of the proposed plant modeling.