Improving Structural Power Content Analysis Robustness for Satellite Navigation Application

With the growing dependency of many critical applications on Global Navigation Satellite Systems (GNSS), the importance of the integrity of GNSS signals has been higher than ever. As the availability of commercial off-the-shelf (COTS) jammers and spoofers rises, there is growing need for real-time interference detection to effectively apply mitigation techniques. Over the years, many interference detection techniques have been developed, verified, and validated. Pre-despreading detection techniques have increased the effectiveness of monitoring systems with limited computational capabilities. For spoofing detection, the Structural Power Content Analysis (SPCA) method, which exploits the periodic nature of the transmitted Pseudo-Random Noise (PRN) codes from the GNSS satellites, has widely been found to be effective in these systems. In this paper results from lab- and field-tests are presented and the real-time applicability of SPCA on spoofing signals is evaluated and found to be an effective and accurate spoofing detection technique. The method, however, was also found to trigger when subjected to several jamming waveforms and scenarios. Through analysis it is demonstrated that this is due to intermodulation products of the jamming signals that are caused by the delay-and-multiply operation performed as part of the SPCA algorithm. Evaluation of these jamming waveforms and events shows that additional signal processing techniques are required to increase the robustness of the SPCA method and the capability of monitoring systems to distinguish between different interference types. Additionally, optimization of the signal and noise filters used in SPCA can increase isolation between the signal and noise energy measurements, and further improve the suppression of intermodulation products due to jamming signals.