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Calibration nested arrays for Underdetermined DOA Estimation Using Fourth-Order Cumulant

IEEE COMMUNICATIONS LETTERS 2020年第9期24卷 1949-1952页

作者： Tian, Ye Xu, He Yanshan Univ Sch Informat Sci & Engn Qinhuangdao 066004 Hebei Peoples R China

The application of a nonuniform nested array provides a simple way for underdetermined direction of arrival (DOA) estimation, enabling us to develop a suited self-calibration algorithm for perturbed nested array. The key points of this algorithm contain two steps: a first step is to obtain gain-phase errors estimation by utilizing partly calibrated array and properly choosing the elements of fourth-order cumulant matrix;a second step to form a small perturbed model after compensating the gain-phase errors as well as obtain DOA estimation using the sparse total east squares (STLS) technique. The proposed algorithm is very suited for underdetermined DOA estimation in the presence of gain-phase errors. Numerical simulations validate the effectiveness of the proposed algorithm.

关键词： Direction-of-arrival estimation Estimation Sensor arrays Phased arrays Perturbation methods Calibration Gain-phase calibration direction of arrival (DOA) estimation nested array sparse total least squares (STLS)

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Tracking a Plane Wave Direction using Sparse arrays with an Extended Kalman Filter 76

Tracking a Plane Wave Direction using Sparse Arrays with an ...

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76th Annual IEEE National Aerospace and Electronics Conference (NAECON)

作者： Rahman, Showrov Adhikari, Kaushallya Univ Rhode Isl Kingston RI 02881 USA

ISBN: (纸本)9798350367638;9798350367621

This work focuses on estimating the direction of arrival of a plane wave from a moving source using time domain snapshots captured by a linear array. We employ an extended Kalman filter by linearizing the time domain measurement model. We consider the performance of a full array, which serves as a benchmark for comparison with three popular sparse arrays: coprime, nested, and shift-invariant sparse arrays. The motivation for using such sparse arrays is to reduce overall cost, sensor count, and computation burden. The simulation results demonstrate that sparse arrays achieve comparable accuracy to full arrays of equivalent aperture. Among the sparse arrays studied, the coprime array exhibits the highest performance, with a mean squared error closest to that of the full array.

关键词： Coprime array direction of arrival (DOA) extended Kalman filter(EKF) nested array shift-invariant sparse array (SISA) sparse arrays

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Near-Field Source Localization With Two-Level nested arrays

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IEEE COMMUNICATIONS LETTERS 2020年第11期24卷 2488-2492页

作者： Shu, Ting Li, Linna He, Jin Shanghai Jiao Tong Univ Shanghai Key Lab Intelligent Sensing & Recognit Sch Elect Informat & Elect Engn Shanghai 200240 Peoples R China Shanghai Aerosp Elect Commun Equipment Res Inst Shanghai 201109 Peoples R China

The concept of the nested array has been used widely for underdetermined far-field source localization. In this case, the enhanced degrees-of-freedom (DOFs) is often achieved by using spatial smoothing because the difference co-array of a two-level nested array behaves like a uniformly-spaced linear array (ULA). This ingenious operation cannot be used for near-field localization because the ULA behavior of the co-array is violated by the near-field's curved wavefronts and range-dependent attenuation. Thus, the application of nested arrays for near-field localization becomes challenging. In this letter, we propose to concatenate the vectorization of multiple fourth-order cumulant matrices to increase the DOFs offered by the nested arrays. We also show that when the sources are in the near-field, the maximum DOFs provided by a two-level nested array with L physical sensors can mathematically be up to exactly L-2. The well-posed identification conditions are discussed as well. Numerical examples are conducted to verify our analysis. Comparisons with existing ULA-based methods are also provided.

关键词： Sensor arrays Smoothing methods array signal processing Estimation Phased arrays array signal processing near-field source localization nested array

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2-D DOA estimation via correlation matrix reconstruction for nested L-shaped array

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DIGITAL SIGNAL PROCESSING 2020年第0期98卷 102623-000页

作者： Yang, Yunlong Mao, Xingpeng Hou, Yuguan Jiang, Guojun Harbin Inst Technol Sch Elect & Informat Engn Harbin Peoples R China Minist Ind & Informat Technol Key Lab Marine Environm Monitoring & Informat Pro Harbin Peoples R China

For a nested L-shaped array (N-LsA) composed of two orthogonal nested subarrays, the self-difference co-array of each nested subarray is hole-free, whereas cross-difference co-arrays between subarrays have holes. Due to the existence of holes, virtual cross-correlation matrices with increased degree of freedoms (DOFs) can not be constructed from cross-difference co-arrays, which will degrade the performance of direction of arrival (DOA) estimation. To overcome this problem, a high resolution two-dimensional (2-D) DOA estimation algorithm is exploited for N-LsA in this paper. Specifically, by using oblique projection operators, filled cross-difference co-arrays can be achieved by filling the holes, and virtual cross-correlation matrix will be obtained. Then the virtual correlation matrix of the N-LsA, which consists of virtual cross-correlation matrices and virtual autocorrelation matrices given by filled self-difference co-arrays, is reconstructed for 2-D DOA estimation. Additionally, the proposed algorithm contains an automatic angle-pairing procedure and can handle underdetermined DOA estimation. The estimation error, Cramer-Rao bound and computational complexity are derived. Simulation results show that the proposed algorithm offers substantial performance improvement over the existing algorithms. (C) 2019 Elsevier Inc. All rights reserved.

关键词： 2-D DOA estimation Matrix reconstruction nested array L-shaped array Oblique projection operator

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Maximizing the Number of Spatial Nulls with Minimum Sensors

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DEFENCE SCIENCE JOURNAL 2022年第4期72卷 638-646页

作者： Remadevi, M. Anjana, S. Sureshkumar, N. Rajesh, R. DRDO Naval Phys & Oceanog Lab Kochi 682021 Kerala India Rajagiri Sch Engn & Technol Kochi 682039 Kerala India

In this paper, we attempt to unify two array processing frameworks viz, Acoustic Vector Sensor (AVS) and two level nested array to enhance the Degrees of Freedom (DoF) significantly beyond the limit that is attained by a Uniform Linear Hydrophone array (ULA) with specified number of sensors. The major focus is to design a line array architecture which provides high resolution unambiguous bearing estimation with increased number of spatial nulls to mitigate the multiple interferences in a deep ocean scenario. AVS can provide more information about the propagating acoustic field intensity vector by simultaneously measuring the acoustic pressure along with tri-axial particle velocity components. In this work, we have developed nested AVS array (NAVS) ocean data model to demonstrate the performance enhancement. Conventional and MVDR spatial filters are used as the response function to evaluate the performance of the proposed architecture. Simulation results show significant improvement in performance viz, increase of DoF, and localization of more number of acoustic sources and high resolution bearing estimation with reduced side lobe level.

关键词： Uniform line array Acoustic vector sensor nested array Spatial nulls Conventional and MVDR beamformer

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Probability Density Functions of the Subspace-Based Direction of Arrival Estimators 13

Probability Density Functions of the Subspace-Based Directio...

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IEEE 13th Annual Computing and Communication Workshop and Conference (CCWC)

作者： Al Kinani, Ridhab Adhikari, Kaushallya Univ Rhode Isl Kingston RI 02881 USA

ISBN: (纸本)9798350332865

MUSIC, MNM, and ESPRIT algorithms are commonly used subspace-based estimators for estimating directions of arrival of plane waves using the data received by a passive sensor array. The estimators perform differently in three different SNR ranges, namely no information region, low information region, and high information region. We evaluate and analyze the PDFs of the subspace-based estimators for fully populated and sparse linear arrays and uniform circular arrays in the three SNR ranges. The simulations demonstrate that in the high information region, the PDFs of the subspacebased estimators resemble Gaussian distributions whose expected values are equal to the true parameter values and variances are small. The PDFs are non-uniform and asymmetric in the low information region.

关键词： Direction of arrival coprime array ESPRIT MNM MUSIC nested array probability density function

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A New Sparse Linear array With Three-Level nested Structure 8

A New Sparse Linear Array With Three-Level Nested Structure

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8th Sensor Signal Processing for Defence Conference (SSPD)

作者： Chen, Mingyang Gan, Lu Wang, Wenwu Univ Surrey Dept Elect & Elect Engn Surrey England Brunel Univ Dept Elect & Comp Engn Uxbridge Middx England

ISBN: (纸本)9781728105031

Mutual coupling, which is caused by a tight inter-sensor spacing in uniform linear arrays (ULAs), will, to a certain extent, affect the estimation result for source localisation. To address the problem, sparse arrays such as coprime array and nested array are considered to achieve less mutual coupling and more uniform degrees-of-freedom (DoFs) than ULAs. However, there are holes in coprime arrays leading to a decrease of uniform DoFs and in a nested array, some sensors may still be located so closely that the influence of mutual coupling between sensors remains significant. This paper proposes a new Loosely Distributed nested array (LoDiNA), which is designed in a three-level nested configuration and the three layers are linked end-to-end with a longer inter-element separation. It is proved that LoDiNA can generate a higher number of uniform DoFs with greater robustness against mutual coupling interference and simpler configurations, as compared to existing nested arrays. The feasibility of the proposed LoDiNA structure is demonstrated for Direction-of-Arrival (DoA) estimation for multiple stationary sources with noise.

关键词： Mutual coupling sparse arrays nested array uniform DoFs LoDiNA DoA estimation

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A DOA Estimation Method Based on Low-Complexity Hybrid Analog and Digital Architecture Design 23

A DOA Estimation Method Based on Low-Complexity Hybrid Analo...

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23rd IEEE International Conference on Communication Technology, ICCT 2023

作者： Wang, Shuxin Sun, Ji Wu, Xiaohuan School of Telecommunication and Information Engineering Nanjing University of Posts and Telecommunications Nanjing China

ISBN: (纸本)9798350325959

The sub-connected (SC) hybrid analog and digital (HAD) structure is attractive in large-scale arrays due to its lower complexity and cost. However, due to antenna grouping, it suffers from angular ambiguity and cannot directly obtain the spatial covariance matrix required by subspace-based methods, such as MUSIC/root-MUSIC. In this paper, we investigate a direction-of-arrival (DOA) estimation method based on the design of low-complexity HAD architectures. We propose a two-layer sub-connected (TL-SC) HAD structure that can directly obtain the spatial covariance matrix of the received signal, avoiding angular ambiguity by exploiting the structural properties of its virtual array, i.e., the nested array structure. Simulation results show that our proposed method can achieve its Cramer-Rao lower bound (CRLB) and has higher estimation accuracy for the same RF chain number. © 2023 IEEE.

关键词： direction-of-arrival estimation hybrid analog and digital large antenna array nested array

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Joint Angle and Range Estimation with Two-Level nested FDA-MIMO Radar 6

Joint Angle and Range Estimation with Two-Level Nested FDA-M...

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6th International Conference on Information Communication and Signal Processing, ICICSP 2023

作者： Wang, Zhengxi Zhu, Shengqi Li, Ximin Wei, Fa Liu, Congfeng Lan, Lan Xidian University National Key Lab of Radar Signal Processing Shannxi Xi'an China Xidian University Key Lab of Electronic Information Countermeasure of the Ministry of Education Shannxi Xi'an China

ISBN: (纸本)9798350339994

The parameter estimation accuracy and the estimated sources number of multiple-input-multiple-output (MIMO) radar with frequency diversity array (FDA) are limited by the number of array elements. In this paper, combining the advantages of nested arrays to expand the array aperture, the signal model of the monostatic two-level nested FDA-MIMO radar is derived. A modified MUSIC algorithm is proposed to solve the rank deficit problem in parameter estimation and realize the joint estimation of angle and range. The effectiveness of the proposed algorithm is verified by simulation results. © 2023 IEEE.

关键词： frequency diversity array modified MUSIC algorithm nested array parameter estimation

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A novel DOA estimation algorithm using directional antennas in cylindrical conformal arrays

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Defence Technology（防务技术） 2021年第3期17卷 1042-1051页

作者： Xiao-feng Gao Ping Li Xin-hong Hao Guo-lin Li Zhi-jie Kong Science and Technology on Electromechanical Dynamic Control Laboratory School of Mechatronical EngineeringBeijing Institute of TechnologyBeijing100081China China Academy of Launch Vehicle Technology Beijing100076China

In this paper, a novel direction of arrival(DOA) estimation algorithm using directional antennas in cylindrical conformal arrays(CCAs) is proposed. To eliminate the shadow effect, we divide the CCAs into several subarrays to obtain the complete output vector. Considering the anisotropic radiation pattern of a CCA, which cannot be separated from the manifold matrix, an improved interpolation method is investigated to transform the directional subarray into omnidirectional virtual nested arrays without non-orthogonal perturbation on the noise vector. Then, the cross-correlation matrix(CCM) of the subarrays is used to generate the consecutive co-arrays without redundant elements and eliminate the noise vector. Finally, the full-rank equivalent covariance matrix is constructed using the output of co-arrays,and the unitary estimation of the signal parameters via rotational invariance techniques(ESPRIT) is performed on the equivalent covariance matrix to estimate the DOAs with low computational complexity. Numerical simulations verify the superior performance of the proposed algorithm, especially under a low signal-to-noise ratio(SNR) environment.

关键词： Direction of arrival(DOA) Conformal antenna array Interpolation technique nested array

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