This paper addresses the two-dimensional (2D) direction-of-arrival (DOA) estimation problem with two novel methods for mixed noncircular and circular signals. The first proposed method is named the two-stage direction-of-arrival matrix (TSDOAM) method, and the other is called the two-stage rank reduction (TSRARE) method. The proposed methods utilize both the circularity and the direction-of-arr...

This paper addresses subspace-based direction of arrival (DOA) estimation and its purpose is to complement previously available theoretical results generally obtained for specific algorithms. We focus on asymptotically (in the number of measurements) minimum variance (AMV) estimators based on estimates of orthogonal projectors obtained from singular value decompositions of sample covariance mat...

The main motivation of using an acoustic vector-sensor in direction-of-arrival (DOA) estimation applications has been its unambiguous two-dimensional directivity, insensitivity to the range of sources, and independence of signal frequency. The main objection lies in its lack of geometry-redundancy and limited degree of freedom. Four thus emerged challenging tasks and the corresponding solutions...

Functional dependencies (FDs) and inclusion dependencies (INDs) are the most fundamental integrity constraints that arise in practice in relational databases. We introduce null inclusion dependencies (NINDs) to cater for the situation when a database is incomplete and contains null values. We show that the implication problem for NINDs is the same as that for INDs. We then present a sound and c...

In this paper, a novel sparsity-aware direction of arrival (DOA) estimation scheme for a noncircular source is proposed in multiple-input multiple-output (MIMO) radar. In the proposed method, the reduced-dimensional transformation technique is adopted to eliminate the redundant elements. Then, exploiting the noncircularity of signals, a joint sparsity-aware scheme based on the reweighted l1 nor...