The root-MUSIC algorithm for direction finding with interpolated arrays
Signal Processing
An Efficient Adaptive Minor Subspace Extraction Using Exact Nested Orthogonal Complement Structure
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Array interpolation and bias reduction
IEEE Transactions on Signal Processing - Part I
Array interpolation and DOA MSE reduction
IEEE Transactions on Signal Processing
Two-dimensional wideband interpolated root-MUSIC applied tomeasured seismic data
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
DoA Estimation Via Manifold Separation for Arbitrary Array Structures
IEEE Transactions on Signal Processing
Adaptive minor component extraction with modular structure
IEEE Transactions on Signal Processing
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We present nontrivial utilization methods of a pair of symbolic algebraic algorithms (Yamada et al. in IEEE Trans Signal Process 46:1639---1664, 1998; Yamada and Bose in IEEE Trans Circuits Syst 1 Fundam Theory Appl 49:298---304, 2002) which were developed originally for multidimensional phase unwrapping and zero-distribution problems. Given the minor subspace of the covariance matrix of the data measured at a uniform linear array of sensors, the proposed methods provide estimates of the Directions-of-Arrival (DOA) distribution of multiple narrowband signals, i.e., the number of DOA in an arbitrarily specified range, without using any numerical search for each direction of arrival. The proposed methods can serve as powerful mathematical tools to extract global information in the high-resolution DOA estimation problems.