Single-Channel High-Precision Sparse DOA Estimation of GNSS Signals for Deception Suppression

KANG Weiquan; LU Zunkun; LI Baiyu; SONG Jie; XIAO Wei

doi:10.11999/JEIT250725

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KANG Weiquan, LU Zunkun, LI Baiyu, SONG Jie, XIAO Wei. Single-Channel High-Precision Sparse DOA Estimation of GNSS Signals for Deception Suppression[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT250725

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KANG Weiquan, LU Zunkun, LI Baiyu, SONG Jie, XIAO Wei. Single-Channel High-Precision Sparse DOA Estimation of GNSS Signals for Deception Suppression[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT250725

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Single-Channel High-Precision Sparse DOA Estimation of GNSS Signals for Deception Suppression

doi: 10.11999/JEIT250725 cstr: 32379.14.JEIT250725

Key Laboratory of Satellite Navigation Technology, College of Electronic Science and Technology, National University of Defense Technology, Changsha 410073, China

Funds: National Natural Science Foundation of China (62003354, U20A20193)

Accepted Date: 2025-12-01
Rev Recd Date: 2025-12-01

Available Online: 2025-12-05

Abstract

Abstract

Objective The proliferation of spoofing attacks poses a significant threat to the reliability and security of Global Navigation Satellite Systems (GNSS), which are critical for navigation and positioning across civilian and military applications. Traditional anti-spoofing methods relying on multi-antenna arrays incur high hardware complexity and exhibit limited estimation accuracy under low signal-to-noise ratio (SNR) conditions, compromising their effectiveness in resource-constrained or adverse environments. This research proposes a novel single-channel high-precision sparse direction-of-arrival (DOA) estimation method aimed at suppressing spoofing signals in GNSS receivers. The primary goals are to substantially reduce the hardware complexity associated with spoofing detection and to achieve superior DOA estimation performance even in extremely low SNR scenarios. By exploiting the spatial sparsity of GNSS signals and integrating advanced signal processing techniques, this approach seeks to deliver a cost-effective, robust solution for enhancing GNSS security against deceptive interference. Methods The proposed method leverages a single-channel processing framework to estimate the DOA of GNSS signals with high precision, employing a multi-step strategy tailored for spoofing suppression. The process begins with reconstructing the digital intermediate frequency signal using tracking loop parameters—such as code phase and carrier Doppler—derived from a reference array element. This reconstruction capitalizes on the orthogonality of pseudo-random noise codes inherent to GNSS signals, enabling correlation between the reconstructed signal and the original array data to enhance the SNR prior to despreading. This step isolates a clean steering vector, minimizing noise and interference contributions. The method then harnesses the spatial sparsity of GNSS signals, which arises from the limited number of authentic satellites and potential spoofing sources in the angular domain. An overcomplete dictionary is constructed, comprising steering vectors corresponding to a grid of possible azimuth and elevation angles. The DOA estimation is reformulated as a sparse reconstruction problem, where the steering vector is represented as a sparse combination of dictionary elements. To solve this efficiently, the Alternating Direction Method of Multipliers (ADMM) is employed, iteratively optimizing a regularized objective that balances data fidelity with sparsity. A two-stage grid refinement approach—starting with a coarse search followed by a finer resolution—reduces computational demands while maintaining accuracy. Once DOA estimates are obtained, spoofing signals are identified by their angular proximity to authentic signals, and a Linearly Constrained Minimum Variance (LCMV) beamformer is applied to suppress these interferers while preserving legitimate signals. Results and Discussions Simulations were conducted to assess the proposed method’s performance across various low SNR conditions, using a 4×4 uniform planar array and Beidou B3I signals as a test case. The results reveal that the single-channel sparse DOA estimation method significantly outperforms traditional algorithms like Unitary ESPRIT and Cyclic MUSIC in both accuracy and resolution. In scenarios with an SNR as low as –35 dB, the proposed approach achieves root mean square errors (RMSE) for azimuth and elevation estimates below 1 degree (Fig.2), compared to errors exceeding 30 degrees for the benchmark methods (Fig. 3(a), Fig. 3(b)). It also resolves signals separated by as little as 1 degree (Fig. 4(a), Fig. 4(b)), highlighting its superior resolution capability. Building upon the accurate DOA estimates obtained in the proposed method, LCMV beamforming successfully suppressed spoofing signals. As shown in Fig. 5(b), the proposed method's high-fidelity DOA estimates allowed the beamformer to place deep nulls precisely at the estimated spoofing directions (e.g., (10°, 250°) and (20°, 250°)), effectively attenuating spoofers while preserving genuine signals. In contrast, the lower DOA estimation accuracy of Cyclic MUSIC (Fig. 5(a)) resulted in misaligned nulls and compromised suppression performance. This validates the practical utility of the high-precision DOA estimates for robust spoofing mitigation. Conclusions This study introduces a pioneering single-channel high-precision sparse DOA estimation method for GNSS spoofing suppression, addressing the limitations of traditional multi-antenna approaches in terms of complexity and low-SNR performance. By integrating signal reconstruction, sparse modeling, and ADMM-based optimization, the method achieves exceptional accuracy and resolution under challenging conditions, validated through simulations showing RMSE below 1 degree at -35 dB SNR. Coupled with LCMV beamforming, it effectively mitigates spoofing threats, enhancing GNSS reliability with minimal hardware requirements. This cost-effective solution is particularly valuable for resource-limited applications, reducing dependency on complex arrays while maintaining robust security. Future work could explore its adaptability to dynamic environments, such as moving spoofers or multipath scenarios, and its integration with complementary anti-spoofing techniques. Overall, this research provides a practical, high-performance framework for securing GNSS systems, with significant implications for navigation safety and operational efficiency.
- Satellite navigation,
- Spoofing detection,
- Direction of Arrival (DOA) estimation,
- Sparse reconstruction,
- Alternating Direction Method of Multipliers (ADMM)

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References(17)

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