Version 1
: Received: 25 December 2023 / Approved: 26 December 2023 / Online: 28 December 2023 (02:15:44 CET)
How to cite:
Gao, N.; Chen, X.; Yan, Z.; Jiao, Z. Performance Enhancement and Evaluation of a Vector Tracking Receiver using Adaptive Tracking Loops. Preprints2023, 2023121948. https://doi.org/10.20944/preprints202312.1948.v1
Gao, N.; Chen, X.; Yan, Z.; Jiao, Z. Performance Enhancement and Evaluation of a Vector Tracking Receiver using Adaptive Tracking Loops. Preprints 2023, 2023121948. https://doi.org/10.20944/preprints202312.1948.v1
Gao, N.; Chen, X.; Yan, Z.; Jiao, Z. Performance Enhancement and Evaluation of a Vector Tracking Receiver using Adaptive Tracking Loops. Preprints2023, 2023121948. https://doi.org/10.20944/preprints202312.1948.v1
APA Style
Gao, N., Chen, X., Yan, Z., & Jiao, Z. (2023). Performance Enhancement and Evaluation of a Vector Tracking Receiver using Adaptive Tracking Loops. Preprints. https://doi.org/10.20944/preprints202312.1948.v1
Chicago/Turabian Style
Gao, N., Zhe Yan and Zhiyuan Jiao. 2023 "Performance Enhancement and Evaluation of a Vector Tracking Receiver using Adaptive Tracking Loops" Preprints. https://doi.org/10.20944/preprints202312.1948.v1
Abstract
The traditional receiver employs scalar tracking loops, resulting in degraded navigation performance in weak signal and high dynamic scenarios. An innovative design of a vector tracking receiver based on nonlinear Kalman filter (KF) tracking loops is proposed in this paper, which combines the strengths of both vector tracking and KF tracking loops. Firstly, a comprehensive description of the vector tracking receiver model is presented, and unscented Kalman filter (UKF) is applied to nonlinear tracking loop. Secondly, to enhance the stability and robustness of the KF tracking loop, we introduce square root filtering and an adaptive mechanism. The tracking loop based on square root UKF (SRUKF) can dynamically adjust its filtering parameters based on signal noise and feedback Doppler error. Finally, the proposed method is implemented on a software-defined receiver (SDR), and the field vehicle experiment demonstrates the superiority of this method over other receivers in complex dynamic environments.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
