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This paper proposes a fast technique for matching a query image to numerous database images under geometric variations in rotation, scale, and translation. Our proposed method extracts the Fourier-Mellin phase features from the images for invariant matching. The online matching process in our method is fast because it directly determines identification based on the correlation value between those features without the geometric alignment.

Passive bistatic radar (PBR) systems use existing RF broadcast and communication signals in the environment for surveillance and tracking applications. GSM mobile communication signal based PBR systems are suitable for short range surveillance systems, but the low-bandwidth of the signal results in low range resolutions when classical cross-correlation based processing is used for target detection. An alternative and more robust approach based on compressive sensing (CS) is proposed here to achieve high range resolution by performing fine gridding for the target scene.

It transpires that the irregularity in the structure of the ionospheric plasma plays a significant role on the ionospherically-propagated HF signals. In this paper, special attention has been paid to derive a simulator that can explicate the perturbed phase influence imposed by the ionosphere irregularities. This has been achieved by studying the space-time correlation as well as statistics of the perturbed phases so that the problem of perturbed phase simulation is recast as generating particular time series satisfying specific power spectrum and statistical distribution.