Biblio

Global Navigation Satellite System (GNSS) jamming is an evolving technology where new modulations are progressively introduced in order to reduce the impact of interference mitigation techniques such as Adaptive Notch Filters (ANFs). The Standardisation of GNSS Threat reporting and Receiver testing through International Knowledge Exchange, Experimentation and Exploitation (STRIKE3) project recently described a new class of jamming signals, called tick signals, where a basic frequency tick is hopped over a large frequency range. In this way, discontinuities are introduced in the instantaneous frequency of the jamming signals. These discontinuities reduce the effectiveness of ANFs, which unable to track the jamming signal. This paper analyses the effectiveness of interference mitigation techniques with respect to frequency-hopped tick jamming signals. ANFs and Robust Interference Mitigation (RIM) techniques are analysed. From the analysis, it emerges that, despite the presence of frequency discontinuities, ANFs provide some margin against tick signals. However, frequency discontinuities prevent ANFs to remove all the jamming components and receiver operations are denied for moderate Jamming to Noise power ratio (J/N) values, RIM techniques are not affected by the presence of frequency discontinuities and significantly higher jamming power are sustained by the receiver when this type of techniques is adopted.

In this paper, an edit detection method for forensic audio analysis is proposed. It develops and improves a previous method through changes in the signal processing chain and a novel detection criterion. As with the original method, electrical network frequency (ENF) analysis is central to the novel edit detector, for it allows monitoring anomalous variations of the ENF related to audio edit events. Working in unsupervised manner, the edit detector compares the extent of ENF variations, centered at its nominal frequency, with a variable threshold that defines the upper limit for normal variations observed in unedited signals. The ENF variations caused by edits in the signal are likely to exceed the threshold providing a mechanism for their detection. The proposed method is evaluated in both qualitative and quantitative terms via two distinct annotated databases. Results are reported for originally noisy database signals as well as versions of them further degraded under controlled conditions. A comparative performance evaluation, in terms of equal error rate (EER) detection, reveals that, for one of the tested databases, an improvement from 7% to 4% EER is achieved, respectively, from the original to the new edit detection method. When the signals are amplitude clipped or corrupted by broadband background noise, the performance figures of the novel method follow the same profile of those of the original method.