ArticleSensors (Basel, Switzerland)2017
Direction-of-Arrival Estimation with Coarray ESPRIT for Coprime Array.
Article in Sensors (Basel, Switzerland), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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17 citing papers in PubMed.
- Hole-Free Nested Array with Three Sub-ULAs for Direction of Arrival Estimation.Sensors (Basel, Switzerland) · 2023Article
- Joint Estimation Method of DOD and DOA of Bistatic Coprime Array MIMO Radar for Coherent Targets Based on Low-Rank Matrix Reconstruction.Sensors (Basel, Switzerland) · 2022Article
- Parameter Estimation for Two-Dimensional Incoherently Distributed Source with Double Cross Arrays.Sensors (Basel, Switzerland) · 2020Article
- A Deep Learning Model for Fault Diagnosis with a Deep Neural Network and Feature Fusion on Multi-Channel Sensory Signals.Sensors (Basel, Switzerland) · 2020Article
- Gain-Phase Errors Calibration for a Linear Array Based on Blind Signal Separation.Sensors (Basel, Switzerland) · 2020Article
- 2D-DOD and 2D-DOA Estimation for a Mixture of Circular and Strictly Noncircular Sources Based on L-Shaped MIMO Radar.Sensors (Basel, Switzerland) · 2020Article
- An Array Switching Strategy for Direction of Arrival Estimation with Coprime Linear Array in the Presence of Mutual Coupling.Sensors (Basel, Switzerland) · 2020Article
- Robust Sparse Bayesian Learning-Based Off-Grid DOA Estimation Method for Vehicle Localization.Sensors (Basel, Switzerland) · 2020Article
- A High-Resolution and Low-Complexity DOA Estimation Method with Unfolded Coprime Linear Arrays.Sensors (Basel, Switzerland) · 2019Article
- Joint Angle and Frequency Estimation Using One-Bit Measurements.Sensors (Basel, Switzerland) · 2019Article
- DOA Estimation for Coprime Linear Array Based on MI-ESPRIT and Lookup Table.Sensors (Basel, Switzerland) · 2018Article
- A Sparse-Based Off-Grid DOA Estimation Method for Coprime Arrays.Sensors (Basel, Switzerland) · 2018Article
- Two-Dimensional Direction-of-Arrival Fast Estimation of Multiple Signals with Matrix Completion Theory in Coprime Planar Array.Sensors (Basel, Switzerland) · 2018Article
- Parameter Estimation of Multiple Frequency-Hopping Signals with Two Sensors.Sensors (Basel, Switzerland) · 2018Article
- An Improved Adaptive Received Beamforming for Nested Frequency Offset and Nested Array FDA-MIMO Radar.Sensors (Basel, Switzerland) · 2018Article
- Improved Coarray Interpolation Algorithms with Additional Orthogonal Constraint for Cyclostationary Signals.Sensors (Basel, Switzerland) · 2018Article
- A Direct Coarray Interpolation Approach for Direction Finding.Sensors (Basel, Switzerland) · 2017Article
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2 authors.
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Abstract
A coprime array is capable of achieving more degrees-of-freedom for direction-of-arrival (DOA) estimation than a uniform linear array when utilizing the same number of sensors. However, existing algorithms exploiting coprime array usually adopt predefined spatial sampling grids for optimization problem design or include spectrum peak search process for DOA estimation, resulting in the contradiction between estimation performance and computational complexity. To address this problem, we introduce the Estimation of Signal Parameters via Rotational Invariance Techniques (ESPRIT) to the coprime coarray domain, and propose a novel coarray ESPRIT-based DOA estimation algorithm to efficiently retrieve the off-grid DOAs. Specifically, the coprime coarray statistics are derived according to the received signals from a coprime array to ensure the degrees-of-freedom (DOF) superiority, where a pair of shift invariant uniform linear subarrays is extracted. The rotational invariance of the signal subspaces corresponding to the underlying subarrays is then investigated based on the coprime coarray covariance matrix, and the incorporation of ESPRIT in the coarray domain makes it feasible to formulate the closed-form solution for DOA estimation. Theoretical analyses and simulation results verify the efficiency and the effectiveness of the proposed DOA estimation algorithm.
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