# A Survey on Satellite Communication System Security
## 5 Defense in Satellite Communication Systems
### Solutions for Integrity
#### 5.3.2 Hardware-Dependent Parameter Analysis Methods
[110] highlights a significant enhancement in subspace projection for GNSS spoofing and jamming mitigation. Traditional subspace projection methods, while effective, face challenges regarding inaccuracies in instantaneous frequency estimates, particularly when facing attackers with rapidly changing frequency characteristics. To counter this, this paper introduces an adaptive-partitioned subspace projection technique. This approach divides the received data vector into adaptive block sizes based on the attacker's chirp rate estimates, accommodating the varying IF characteristics. The signal isthen projected onto the attacker's orthogonal subspace constructed from these IF estimates. This technique's adaptability to the jammer's sweep rate, by adjusting the time-frequency observation window length, is key. This adaptability ensures consistent instantaneous phase estimation errors, providing an effective solution against frequency-varied jamming. Similarly, ref. [111] presents a robust spoofing mitigation algorithm using subspace projection tailored for single-antenna GNSS receivers. This approach uses the subspace projection method to effectively eliminate spoofing signals from the received signal by projecting them onto the orthogonal null space of the spoofing signals. This process involves approximating the subspace of spoofing signals and subtracting this estimation from the input signals to isolate the authentic signals and ambient noise. This method is particularly valuable for its independence from the number of antennas, making it a versatile solution for a wide range of GNSS receivers. (iiii) Signal Quality Monitoring: Signal quality monitoring (SQM) techniques detect anomalies or distortions in the received GNSS signals using specific algorithms to specify interference, jamming, or spoofing attacks. Ref. [112] introduces an evolved version of signal quality monitoring for spoofing detection that assesses the quality of the correlation function using two metrics. This includes a ratio test and extra correlators for detecting asymmetries in the correlation function, effectively differentiating between multipath and spoofing interference. The algorithm's capability to detect spoofers with varying code delays is emphasized, necessitating the joint detection of both metrics to distinguish between multipath interference and spoofer attacks. Another study [113] presents the SQM technique, a low-complexity algorithm designed for anti-spoofing. The SQM technique employs ratio test metrics to detect anomalies in the correlation peak and the presence of vestigial signals, using pairs of correlators and extra-correlators to monitor distortions. This technique includes a calibration phase for establishing baseline values and a detection window for computing thresholds to declare the presence of a spoofer. Its effectiveness is validated in the Texas spoofing test battery, known as TEXBAT scenarios, showing notable success in identifying matched-power spoofing attacks under static and dynamic conditions. Similar to both these studies, ref. [114] focuses on Galileo signals and seeks to detect abnormally shaped or asymmetric correlation peaks caused by the interaction between authentic and counterfeit signals. It underlines the severe risks posed by spoofing attacks, which can mislead GNSS receivers, potentially leading to adverse outcomes. This paper utilizes additional correlator branches for spoofing detection, assessing the correlation peak's distortion due to spoofing attacks. Various spoofing scenarios, including changes in signal parameters like delays, Doppler shifts, and amplitudes, are analyzed, with different SQM metrics evaluated for their effectiveness in detecting spoofing attacks under these diverse conditions.