MUSIC is a popular algorithm for estimating the direction of arrival (DOA) in array signal processing applications.In this paper, we analyze the performance of the MUSIC algorithm for a single source system, in the presence of noisy and missing data (when only a random subset of the entries in the data matrix are observed). We prove consistency of the DOA estimate when signal from a single source is impinging on low coherence arrays, and derive an analytic expression for the mean-squared-error (MSE) performance of MUSIC for the case of uniform linear arrays, in the large array and relatively large sample setting. Our analysis is mathematically justified in both the sample rich and deficient regimes. The expression for the MSE is a simple function of array geometry, signal-to-noise ratio (SNR), the fraction of entries observed, and the ratio of the number of sensors to number of snapshots. We derive a phase transition threshold which separates a regime where MUSIC is consistent from a regime where MUSIC is inconsistent. This threshold depends upon the SNR, the probability of observing entries in the data matrix, and number of sensors and snapshots in a simple manner which we make explicit.
Index Terms-Direction of Arrival (DOA), Multiple Signal Classification (MUSIC), random matrix theory.1053-587X
We consider the problem of estimating the singular vectors of lowrank signal matrices buried in noise in the setting where the singular vectors are assumed to be Kronecker products of unknown vectors. We propose four algorithms for estimating such singular vectors, analyze their performance and show that they asymptotically fail to estimate to latent singular vector below the same critical SNR. We corroborate our theoretical findings with numerical simulations and illustrate the improved performance on a STAP beamforming application.
Abstract-In this work, using 3D device simulation, we perform an extensive gate to source/drain underlap optimization for the recently proposed hybrid transistor, HFinFET, to show that the underlap lengths can be suitably tuned to improve the on-off ratio as well as the subthreshold characteristics in an ultrashort channel n-type device without significant on performance degradation. We also show that the underlap knob can be tuned to mitigate the device quality degradation in presence of interface traps. The obtained results are shown to be very promising when compared against ITRS 2009 performance projections as well as published state of the art planar and non-planar Silicon MOSFET data of comparable gate lengths using standard benchmarking techniques.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.