Session A2: GNSS Security: Interference, Jamming, and Spoofing 1

A New Method for AOA Estimation and TDOA/AOA Joint Localization of GNSS Spoofer
Mingxiu Chen, Yanhong Kou, Yiwei Wang, and Chun Wang, Beihang University
Location: Beacon A

Abstract: One of the key issues in GNSS anti-spoofing processing is the direction-finding and localization of spoofer sources. Unlike other cases of interference source localization, the power of the GNSS spoofing signal is usually comparable to that of the authentic satellite signal, which is far below the noise level. Moreover, the GNSS spoofing signal shares the same signal structure as the authentic signal, which causes the conventional radiogoniometry and interference monitoring system ineffective for GNSS spoofing detection, estimation, and separation. This brings difficulties in accurately locating the GNSS spoofer.
To address this issue, we propose an AOA (Angle of Arrival) estimation method based on spatial cross-correlation power spectrum peak search as well as a spoofer localization method that integrates TDOA (Time Difference of Arrival) and AOA measurements, taking into account the characteristics of GNSS spoofing signals.
First, a spatial cross-correlation power spectrum estimation method based on array antennas is proposed considering the high correlation between spoofing and authentic signals. Through cross-correlation between the signals from different array elements, the power spectrum peaks are searched within the angular range of interest, and the signal power and AOA measurements from different incoming directions are extracted. In this way, the detection of spoofing interferences and the estimation of their parameters in the spatial and energy domains can also be achieved.
Second, TDOA measurements of different signals arriving at each monitoring station are extracted by baseband signal processing inside monitoring receivers. Combining the aforementioned AOA and TDOA measurements, the consistency between the measurements and their corresponding PVT solutions is examined to classify and identify the spoofing and authentic signals. In this way, the authentic GNSS signals can be separated from the spoofing signals and then used for localization and timing synchronization between monitoring stations, thus solving the problem for monitoring stations to obtain their true PVT positions by the GNSS common view method under spoofing attack conditions.
Finally, the AOA and TDOA measurements of the separated spoofing signals are combined to estimate the position of the spoofer. With both theoretical model and simulation analysis, the proposed method is proven to be capable of detecting and identifying spoofing signals, and further accurately locating the spoofer in complicated GNSS interference situations.