Direction-of-arrival (DOA) is a pivotal measurement in Global Navigation Satellite System antispoofing, which provides key information for spoofing discrimination and orienting. Notably, even sophisticated spoofing attacks employing multiple transmitting antennas can be effectively addressed using DOA measurements, due to the inherent challenge for spoofers to align signal directions with authentic satellites. Nevertheless, traditional DOA estimation methods using antenna arrays are costly and computationally complex. The methods that use the synthetic aperture or dual-polarization antenna (DPA) offer a promising avenue for reducing system complexity. However, synthetic aperture techniques demand precise knowledge of antenna movement trajectories, while DPA methods rely on dedicated hardware structures. To overcome such limitations, this article proposes a space–time-ambiguity decomposition method for DOA estimation to boost antispoofing with rotating dual antennas. By jointly leveraging the measurements across both spatial and temporal dimensions, the signal DOA is estimated with dual antennas when absenting the information of the antenna moving trace. A maximum clique search method is employed for spoofing discrimination, which synthesizes DOA estimations from multiple signals to enhance discrimination performance. Monte Carlo simulations are conducted compared with the Cramer–Rao low bound. Field experiments in a multiantenna spoofing scene indicate the validity of the proposed method.
A Space–Time-Ambiguity Decomposition Method for DOA Estimation Enhancing Antispoofing via Rotating Dual Antennas
IEEE Transactions on Aerospace and Electronic Systems ; 60 , 6 ; 7643-7662
01.12.2024
3239315 byte
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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