Samuel Dilshan Somasundaram

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Nuclear quadrupole resonance (NQR) is a radiofrequency technique that can be used to detect the presence of quadrupolar nuclei, such as the N nucleus prevalent in many explosives and narcotics. In a typical application, one observes trains of decaying NQR echoes, in which the decay is governed by the spin echo decay time(s) of the resonant line(s). In most(More)
Recent robust Capon beamformers (RCBs) systematically allow for array steering vector (ASV) errors by exploiting ASV uncertainty ellipsoids, which are typically characterized in element space (ES). Reduced dimension (RD) techniques are often used to reduce computational complexity and speed up algorithm convergence. Here, a general framework is proposed for(More)
Nuclear quadrupole resonance (NQR) is a solid-state radio frequency (RF) spectroscopic technique, allowing the detection of compounds containing quadrupolar nuclei, a requirement fulfilled by many high explosives and narcotics. The practical use of NQR is restricted by the inherently low signal-to-noise ratio (SNR) of the observed signals, a problem that is(More)
Nuclear quadrupole resonance (NQR) is a solid-state radio frequency spectroscopic technique that can be used to detect compounds which contain quadrupolar nuclei, a requirement fulfilled by many high explosives and narcotics. Unfortunately, the low signal-to-noise ratio (SNR) of the observed signals currently inhibits the widespread use of the technique,(More)
Nuclear quadrupole resonance (NQR) is a solid-state radio frequency (RF) spectroscopic technique that allows for the detection of many narcotics and highly explosive substances. Unfortunately, the practical use of NQR is often restricted by the presence of strong RF interference (RFI). In this letter, extending our recent work on stochastic NQR (sNQR), we(More)
The problem of estimating a spectral representation of damped sinusoidal signals from a gapped data set is of considerable interest in several applications. In this paper, we propose a filterbank approach to provide such an estimate, by first reconstructing the missing data samples assuming that the spectral content of the missing data is similar to that of(More)
The robust Capon beamformer has been shown to alleviate the problem of signal cancellation resulting from steering vector errors, caused, e.g., by calibration and/or angleof-arrival errors, which would otherwise seriously deteriorate the performance of an adaptive beamformer. Here, we examine robust Capon beamforming of multi-dimensional arrays, where(More)