Title :
Fast recursive subspace adaptive ESPRIT algorithms
Author_Institution :
Fachlochschule Fortwangen, Rohrnbach, Germany
fDate :
9/1/1998 12:00:00 AM
Abstract :
A class of fast recursive ESPRIT algorithms for adaptive (on-line) source localization based on subspace tracking and adaptive rank reduction is introduced. These adaptive ESPRIT algorithms can be used for on-line tracking of r maneuvering sources in space using the output of an N-element sensor array, where N>2r. The fastest of our algorithms requires only O(Nr)+O(r3) complex arithmetic operations to update the estimated directions-of-arrival (DOAs) at each time instant. These highly efficient algorithms are more than only a concatenation of a subspace tracker and a conventional batch ESPRIT algorithm. A special QR-reduction to standard form is the key to the fast recursive algorithms. Detailed computer experiments substantiate the theoretical results
Keywords :
adaptive signal processing; array signal processing; computational complexity; direction-of-arrival estimation; eigenvalues and eigenfunctions; matrix algebra; recursive estimation; tracking; DOA estimation; QR-reduction; adaptive rank reduction; adaptive source localization; complex arithmetic operations; computer experiments; directions-of-arrival; efficient algorithms; eigenvalues; fast recursive ESPRIT algorithms; maneuvering sources; matrix; on-line source localization; sensor array; subspace tracker; subspace tracking; Adaptive algorithm; Adaptive arrays; Arithmetic; Eigenvalues and eigenfunctions; Least squares methods; Narrowband; Sensor arrays; Signal processing algorithms; Smoothing methods; Standards development;
Journal_Title :
Signal Processing, IEEE Transactions on