Title

Performance Degradation of DOA Estimators Due to Unknown Noise Fields

Document Type

Article

Date of Original Version

1-1-1992

Abstract

This correspondence presents a statistical performance analysis of subspace-based directions-of-arrival (DOA) estimation algorithms in the presence of correlated observation noise with unknown covariance. Our analysis of five different estimation algorithms is unified by a single expression for the mean-squared DOA estimation error which is derived using a subspace perturbation expansion. The analysis assumes that only a finite amount of array data is available. © 1992 IEEE

Publication Title

IEEE Transactions on Signal Processing

Volume

40

Issue

3

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