Blind high resolution localization and tracking of multiple frequency hopped signals

This paper considers the problem of blind localization and tracking of multiple frequency-hopped spread-spectrum (FHSS) signals using an antenna array, without knowledge of hopping patterns. We first identify a hop free subset of data by discarding high-entropy spectral slices from the spectrogram, then perform low-rank decomposition of four-way data generated by capitalizing on both spatial and temporal shift invariance for high resolution direction of arrival (DOA) recovery. After MMSE beamforming, a dynamic programming approach is developed for joint ML estimation of signal frequencies and hopping instants for signal user tracking.