Instantaneous frequency estimation and localization for ENF signals

Abstract

Forensic analysis based on Electric Network Frequency (ENF) fluctuations is an emerging technology for authenticat-ing multimedia recordings. This class of techniques requires extracting frequency fluctuations from multimedia recordings and comparing them with the ground truth frequencies, ob-tained from the power mains, at the corresponding time. Most current guidelines for frequency estimation from the ENF signal use non-parametric approaches. Such approaches have limited temporal-frequency resolution due to the tradeoffs of the time-frequency resolutions as well as computational power. To facilitate robust high-resolution matching, it is important to estimate instantaneous frequency using as few samples as possible. The use of subspace-based methods for high resolution frequency estimation is fairly new for ENF analysis. In this paper, a systematic study of several high resolution low-complexity frequency estimation algorithms is conducted, focusing on estimating the frequencies in short time-frames. After establishing the performance of several frequency estimation algorithms, a study towards using the ENF signal for estimating the location-of-recording is carried out. Experiments conducted on ENF data collected in several cities indicate the presence of location-specific signatures that can be exploited for future forensic applications.