An ARS-Aided GNSS Scheme for Jamming-Resistant Direct Yaw Tracking

Chuanrui Wang, Xiaowei Cui, Gang Liu, Mingquan Lu

Peer Reviewed

Abstract:	Reliable attitude determination using GNSS antenna arrays is vulnerable to jamming, while existing anti-jamming algorithms typically suffer from high computational complexity due to multi-dimensional parameter searches. To address this, we propose a computationally efficient and robust attitude determination scheme aided by an Attitude Reference System (ARS). By leveraging the reliable roll and pitch angles provided by the ARS, the complex three-dimensional attitude estimation problem is reduced to a one-dimensional yaw tracking task. We theoretically prove that the yaw angle variation is locally equivalent to a 1-D Direction-of-Arrival (DOA) shift, allowing for direct yaw measurement using the Constrained Adaptive Monopulse (CAMP) technique without iterative searching. To enhance robustness in multi-jammer scenarios, a multi-satellite fusion strategy based on inverse-variance weighting is developed. This mechanism automatically evaluates the reliability of each satellite’s monopulse measurement, effectively suppressing outliers caused by jamming or poor geometry. Simulation results demonstrate that the proposed method maintains high attitude accuracy even in the presence of four jammers. Furthermore, runtime comparisons reveal that the proposed scheme reduces computational time by approximately 18 times compared to a highly optimized 1-D Maximum Likelihood search baseline, validating its suitability for real-time implementation on resource-constrained platforms.
Published in:	Proceedings of the ION 2026 Pacific PNT Meeting April 13 - 16, 2026 Hilton Waikiki Beach Honolulu, Hawaii
Pages:	833 - 844
Cite this article:	Wang, Chuanrui, Cui, Xiaowei, Liu, Gang, Lu, Mingquan, "An ARS-Aided GNSS Scheme for Jamming-Resistant Direct Yaw Tracking," Proceedings of the ION 2026 Pacific PNT Meeting, Honolulu, Hawaii, April 2026, pp. 833-844. https://doi.org/10.33012/2026.20624
Full Paper:	ION Members/Non-Members: 1 Download Credit Sign In