Identifiability Issues for Rot at ionally Invariant Arrays
نویسنده
چکیده
The popular ESPRIT algorithm provides a computationally eficient approach for direction of arrival (DOA) estimation in situations where the sensor array is composed of two identical translated subarrays. One of the key advantages of ESPRIT is that the subarrays need not be calibrated in order to obtain the DOA estimates. In this paper, the problem of DOA estimation using sensor arrays composed of two identical, uncalibrated, and rotated subarrays is considered. It is ahown that, unlike ESPRIT, such rotationally invariant arrays do not provide an identifiable parameterization of the problem; i.e., unique DOA estimates are not possible without additional calibration information when more than one signal is present.
منابع مشابه
Parameter Identifiability Issues in a Latent Ma- rkov Model for Misclassified Binary Responses
Medical researchers may be interested in disease processes that are not directly observable. Imperfect diagnostic tests may be used repeatedly to monitor the condition of a patient in the absence of a gold standard. We consider parameter identifiability and estimability in a Markov model for alternating binary longitudinal responses that may be misclassified. Exactly ...
متن کاملBlind Identifiability Analysis in a Mimo Lti System with Inputs from a Finite-alphabet Set
A blind separation problem in a multiple-input-multiple-output (MIMO) linear time-invariant (LTI) system with finite-alphabet inputs is considered. A discrete-time matrix equation model is used to describe the input-output relation of the system in order to make full use of the advantages of modern digital signal processing techniques. At first, ambiguity problem is investigated. Then, based on...
متن کاملIdentifiability Issues for Parameter - Varying Andmultidimensional Linear Systems
This paper considers the identiiability of state space models for a system that is expressed as a linear fractional transformation (LFT): a constant matrix (containing identiied parameters) in feedback with a nite-dimensional, block-diagonal (\structured") linear operator. This model structure can represent linear time-invariant, linear parameter-varying, uncertain, and multidimensional systems...
متن کاملIdentifiability and manifold ambiguity in DOA estimation for nonuniform linear antenna arrays
This paper considers the direction-of-arrival (DOA) estimation identifiability problem for uncorrelated Gaussian sources and nonuniform antenna arrays. It is now known that sparse arrays always suffer from manifold ambiguity, which arises due to linear dependence amongst the columns of the array manifold matrix (the “steering vectors”). While the standard subspace DOA estimation algorithms such...
متن کامل