ArticleSensors (Basel, Switzerland)2018
Two-Dimensional DOA Estimation for Three-Parallel Nested Subarrays via Sparse Representation.
Article in Sensors (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- Two-Stage Fast DOA Estimation Based on Directional Antennas in Conformal Uniform Circular Array.Sensors (Basel, Switzerland) · 2021Article
- Two-Dimensional Angle Estimation of Two-Parallel Nested Arrays Based on Sparse Bayesian Estimation.Sensors (Basel, Switzerland) · 2018Article
- A Sparse-Based Off-Grid DOA Estimation Method for Coprime Arrays.Sensors (Basel, Switzerland) · 2018Article
- A Novel Nested Configuration Based on the Difference and Sum Co-Array Concept.Sensors (Basel, Switzerland) · 2018Article
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4 authors.
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Abstract
Nested arrays are considered attractive due to their hole-free performance, and have the ability to resolve O ( N 2 ) sources with O ( N ) physical sensors. Inspired by nested arrays, two kinds of three-parallel nested subarrays (TPNAs), which are composed of three parallel sparse linear subarrays with different inter-element spacings, are proposed for two-dimensional (2-D) direction-of-arrival (DOA) estimation in this paper. We construct two cross-correlation matrices and combine them as one augmented matrix in the first step. Then, by vectorizing the augmented matrix, a hole-free difference coarray with larger degrees of freedom (DOFs) is achieved. Meanwhile, sparse representation and the total least squares technique are presented to transform the problem of 2-D DOA searching into 1-D searching. Accordingly, we can obtain the paired 2-D angles automatically and improve the 2-D DOA estimation performance. In addition, we derive closed form expressions of sensor positions, as well as number of sensors for different subarrays of two kinds of TPNA to maximize the DOFs. In the end, the simulation results verify the superiority of the proposed TPNAs and 2-D DOA estimation method.
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