A. L. Swindlehurst

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We consider in this paper the problem of extending the ESPRIT algorithm for multiple source, co-channel direction nding to the two-dimensional case (e.g., azimuth and elevation angle estimation). Two algorithms are presented, one based on the optimal (minimum variance) subspace tting formulation of ESPRIT, and the other based on an approximation to it. The(More)
This is the second of a two-part paper dealing with the performance of subspace-based algorithms for narrowband direction-of-arrival (DOA) estimation when the array manifold and noise covariance are not correctly modeled. In Part I, the performance of the MUSIC algorithm was investigated. In Part II, we extend this analysis to mul-tidimensional (MD)(More)
We compare the performance of several algorithms for signal separation based on actual mobile cellular radio data. The data were collected by base stations in two different environments: using an eight element linear array on a hillside overlooking a suburban area, and using a four element square array at the top of a ten story building in a dense urban(More)
A new method is presented for the identiication of systems parameterized by linear state space models. The method relies on the concept of subspace tting, wherein an input/output data model parameterized by the state matrices is found that best ts, in the least-squares sense, the dominant subspace of the measured data. Some empirical results are included to(More)
Signal parameter estimation and specifically direction of arrival (DOA) estimation for sensor array data is encountered in a number of applications ranging from electronic surveillance to wireless communications. Subspace based methods have shown to provide computationally as well as statistically efficient algorithms for DOA estimation. Estimator(More)
Abatracf-T h e recently introduced class of stlbspace fit-ling algorithms for sensor array signal processing (e.g., direction-of-arrival (DOA) estimation) includes determin-istic maximum likelihood, ESPRIT, weighted subspace flt-ting, and both one-and multi-dimensional MUSIC as special cases. In this paper, the performance of this class of algorithms is(More)
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