An approach to direction finding based on a subspace perturbation expansion
Document Type
Conference Proceeding
Date of Original Version
12-1-2003
Abstract
This paper describes a method for estimating directions of arrival from sensor-array data. The estimates are obtained from minimizing a subspace-fitting cost function. This cost function is optimally weighted using statistical information provided by a subspace perturbation expansion. The calculations for scenarios involving very closely spaced sources suffers from the need to invert ill conditioned matrices. This problem is overcome by a reparameterization of both the cost function and its Jacobian based on the concept of a limiting subspace. The paper includes a challenging simulation example involving multiple moving sources.
Publication Title, e.g., Journal
Conference Record of the Asilomar Conference on Signals, Systems and Computers
Volume
1
Citation/Publisher Attribution
Vaccaro, Richard J., Pranab Majumdar, and Norman L. Owsley. "An approach to direction finding based on a subspace perturbation expansion." Conference Record of the Asilomar Conference on Signals, Systems and Computers 1, (2003): 817-821. https://digitalcommons.uri.edu/ele_facpubs/1146