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DOA Estimation Exploiting Sparse array Motions

IEEE TRANSACTIONS ON SIGNAL PROCESSING 2019年第11期67卷 3013-3027页

作者： Qin, Guodong Amin, Moeness G. Zhang, Yimin D. Xidian Univ Sch Elect Engn Xian 710071 Shaanxi Peoples R China Villanova Univ Coll Engn Ctr Adv Commun Villanova PA 19085 USA Temple Univ Dept Elect & Comp Engn Philadelphia PA 19122 USA

This paper utilizes sparse array motion to increase the numbers of achievable both degrees of freedom (DOFs) and consecutive lags in direction-of-arrival (DOA) estimation problems. We use commonly employed environment-independent sparse array configurations. The design of these arrays is not dependent on the sources in the field of view, but rather aims at achieving desirable difference co-arrays. They include structured coprime and nested arrays, minimum redundancy array (MRA), minimum hole array (MHA), and sparse uniform linear array (SULA). array motion can fill the holes in the spatial autocorrelation lags associated with a fixed platform and, therefore, increases the number of sources detectable by the same number of array sensors. Quasi-stationarity of the environment is assumed where the source locations and waveforms are considered invariant over array motion of half wavelength. Closed-form expressions of the number of DOFs and consecutive spatial correlation lags for coprime and nested arrays as well as SULA, due to array translation motion, are derived. The number of DOFs and consecutive lags for the specific cases of MRA an 5 avaluated. We show the respective DOA estimation performance based on sparse reconstruction techniques.

关键词： Sparse arrays DOA estimation difference coarray coprime array nested array minimum redundancy array array motion synthetic aperture

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Calibrating nested Sensor arrays with Model Errors 48

Calibrating Nested Sensor Arrays with Model Errors

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48h Asilomar Conference on Signals, Systems and Computers

作者： Han, Keyong Yang, Peng Nehorai, Arye Washington Univ Preston M Green Dept Elect & Syst Engn One Brookings Dr St Louis MO 63130 USA

ISBN: (纸本)9781479982974

We consider the problem of direction of arrival (DOA) estimation based on a nonuniform linear nested array which can provide O(N-2) degrees of freedom using only N sensors. Both subspace-based and sparsity-based algorithms require certain modeling assumptions, for example, exact known array geometry, including sensor gain and phase. In practice, however, the actual sensor gain and phase are often perturbed from their nominal values, which results in failure of the existing DOA estimation algorithms. In this paper, we investigate the self-calibration problem for perturbed nested arrays, proposing corresponding robust algorithms to estimate both the model errors and the DOAs. The partial Toeplitz structure of the covariance matrix is employed to estimate the gain errors, and the sparse total least squares is used to deal with the phase error issue. Additionally, for the first time, we extend the proposed approaches to calibrate general non-uniform linear arrays. Numerical examples are provided to verify the effectiveness of the proposed strategies.

关键词： Calibration model error nested array Toeplitz sparse total least squares direction of arrival estimation

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An Efficient Compressed Sensing-based DOA Estimation Method in nested MIMO Sonar

An Efficient Compressed Sensing-based DOA Estimation Method ...

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Oceans Aberdeen Conference

作者： Yang, Jie Yang, Yixin Lei, Bo Northwestern Polytech Univ Key Lab Ocean Acoust & Sensing Minist Ind & Informat Technol Xian 710072 Shaanxi Peoples R China Northwestern Polytech Univ Sch Marine Sci & Technol Xian 710072 Shaanxi Peoples R China

ISBN: (纸本)9781509052783

The maximum number of targets that can be uniquely identified by the traditional MIMO sonar is limited by the number of virtual sensors. To alleviate this problem, we extend the idea of nested array to the case of MIMO sonar. To utilize the enhanced degrees of freedom (DOF) provided by the nested MIMO sonar, an efficient direction of arrival (DOA) estimation method is proposed based on compressed sensing (CS), in which we exploit weighted l(1) minimization algorithm to achieve high resolution and suppress spurious peaks. Simulation results verify the usefulness of the proposed method under various situations.

关键词： MIMO sonar nested array degrees of freedom direction of arrival compressed sensing

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A Novel DOA Estimation Error Reduction Preprocessing Scheme of Correlated Waves for Khatri-Rao Product Extended-array

A Novel DOA Estimation Error Reduction Preprocessing Scheme ...

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17th International Symposium on Antennas and Propagation (ISAP)

作者： Shirai, Satoshi Yamada, Hiroyoshi Yamaguchi, Yoshio Niigata Univ Grad Sch Sci & Technol Niigata 9502181 Japan

In this paper, we study on direction-of-arrival (DOA) estimation error reduction by Khatri-Rao (KR) product extended array in the presence of correlated waves. Recently, a simple array signal processing technique called KR product extended array has been proposed. By using the technique, degrees-of-freedom of an array can be easily increased. However, DOA estimation accuracy deteriorates when correlated or coherent waves arrive. Such highly correlated waves often arrive for radar application, hence error reduction technique has been desired. Therefore, in this paper, we propose a new method for error reduction preprocessing scheme by using N-th root of matrix. The N-th root of matrix has a similar effect to the spatial smoothing preprocessing for highly correlated signals. As a result, DOA estimation error due to signal correlation will be reduced. The optimal order of N depends on the data itself. In this paper, a simple iterative method to obtain adaptive N is also proposed. Computer simulation results are provided to show performance of the proposed method.

关键词： DOA estimation Khatri-Rao product nested array degrees of freedom

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Underdetermined DOA Estimation With Unknown Source Number in Nonuniform Noise

Underdetermined DOA Estimation With Unknown Source Number in...

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IEEE Radar Conference

作者： Jiang, Guojun Mao, Xingpeng Wang, Mianzhi Liu, Yongtan Nehorai, Arye Harbin Inst Technol Sch Elect & Informat Engn Harbin 150001 Heilongjiang Peoples R China Washington Univ Preston M Green Dept Elect & Syst Engn St Louis MO 63130 USA

ISBN: (纸本)9781538641675

We present a new direction-of-arrival (DOA) estimator for nested arrays, which does not require source number knowledge and works in the presence of nonuniform noise. We first give the number of unique elements and the number of elements which appear more than once in the difference coarray obtained from the nested arrays. Then we construct 2N - 5 Toeplitz matrices based on the elements appearing more than once. Finally, we introduce a method for DOA estimation which does not require the source number information. Numerical examples are provided to demonstrate the effectiveness of the proposed algorithm.

关键词： DOA estimation nested array source number knowledge nonuniform noise

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A NEW COPRIME-array-BASED CONFIGURATION WITH AUGMENTED DEGREES OF FREEDOM AND REDUCED MUTUAL COUPLING 47

A NEW COPRIME-ARRAY-BASED CONFIGURATION WITH AUGMENTED DEGRE...

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47th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

作者： Mohsen, Nabil Hawbani, Ammar Agrawal, Monika Alsamhi, Saeed Zhao, Liang Univ Sci & Technol China Hefei Peoples R China Indian Inst Technol Delhi New Delhi India AthloneInst Technol Software Res Inst Athlone Ireland Shenyang Aerosp Univ Shenyang Peoples R China

ISBN: (纸本)9781665405409

In this paper, a new type of coprime-array-based structure, named AtCADiS, is proposed to achieve increased degrees of freedom (DoFs) and reduced mutual coupling. The closed-form expressions for the sensor positions and the number of uniform DoFs (uDoFs) of AtCADiS are provided. Specifically, AtCADiS is constructed via two steps. First, we shift the leftmost sensor of tailored coprime array with displaced subarrays (tCADiS) to the right by N. Second, we increase the number of sensors of tCADiS by left perpendicularM/2right perpendicular. that are appropriately placed to connect the positive and negative lags of difference coarray of tCADiS and further improved its uDoFs remarkably. Finally, simulations show that AtCADiS can achieve higher number of uDoFs than the existing coprimearray-based structures by using the same number of physical sensors, which leads to stronger resolution capability and higher direction of arrival (DoA) estimation accuracy. In the presence of mutual coupling, AtCADiS can achieve comparable mutual coupling leakage compared with the existing array structures.

关键词： sparse array coprime array nested array difference coarray direction-of-arrival estimation mutual coupling

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To Achieve Massive MIMO with Much Less Antennas By nested Placement 35

To Achieve Massive MIMO with Much Less Antennas By Nested Pl...

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IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)

作者： Yuan, Shitong Liang, Qilian Univ Texas Arlington Dept Elect Engn Arlington TX 76019 USA

ISBN: (纸本)9781467399555

nested array-A new type of two dimensional arrays with sensors(antennas) on lattice was proposed these years. This paper designs a novel antenna placement scheme at base station based on 2-D nested array. We utilize the difference co-array, which is an important characteristic of nested array, to model and generate all antennas(virtual antennas) in the covariance matrix of channel(virtual channel) coefficients. Based on this fact and inferences, we also model a Massive MIMO antenna system with nested configuration and list all mathematics procedures to calculate its performance with achievable rate. A zero forcing detector is applied to this Massive MIMO system and the spectral efficiency is given at the end. The numeric result proves our mathematics derivation and also the feasibility in real world. What's more, given the same number of antennas, the proposed method could achieve higher sum-rate capacity and better spectral efficiency.

关键词： Massive MIMO nested array Difference Co-array Spectral Efficiency

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Tracking More Targets with Less Antenna: An Investigation into the Co-array Concept 9

Tracking More Targets with Less Antenna: An Investigation in...

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9th European Conference on Antennas and Propagation EuCAP

作者： Wang, Jiachen Xu, Hantao Zheng, Xuezhi Vandenbosch, Guy A. E. Katholieke Univ Leuven TELEMIC ESAT Kasteelpk Arenberg 10 B-3001 Leuven Belgium

ISBN: (纸本)9788890701856

In this paper, two compressive DoA estimation algorithms are investigated, namely the sparse ruler, and the coprime sampling array. These algorithms explore the eigen matrix structure of a non uniform linear array in order to artificially synthesize a larger uniform linear array, in this way boosting the capability of a DoA tracking system beyond the theoretical limit of the number of sources that can be detected with a certain number of antenna elements. In other words, we can detect the Direction of Arrival ( DoA) of more sources with less antenna elements. Crucial is that the study is based on real measurements conducted on a real demonstrator platform. The key parameters that affect the DoA estimation are investigated. The results show clearly that the sparse ruler algorithm has a better performance.

关键词： Direction of Arrival (DoA) estimation Sparse Ruler MUSIC algorithm Coprime Sampling nested array Spatial Smoothing

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DOA Estimation of Non-Circular Signals using Fourth Order Cumulant in Underdetermined Cases

DOA Estimation of Non-Circular Signals using Fourth Order Cu...

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IEEE International Workshop on Signal Processing Systems (IEEE SiPS)

作者： Gupta, Payal Agrawal, Monika Indian Inst Technol Ctr Appl Res Elect New Delhi 110016 India

ISBN: (纸本)9781538663189

In this paper, we estimate the Direction of Arrival (DoA) of the non-circular signals impinging on the Non-Uniform Linear array (NULA). A new methodology based on the fourth order cumulant is proposed where the NULA output signal is transformed into the virtual array output signal by utilizing the non-circularity properties. Next, we focused on the enhancing the degrees of freedom by designing the NULA. The proposed NULA design yields the virtual array which offers the significant increase the degrees of freedom as compared to others existing NULAs. The effectiveness of proposed array is verified through the numerical example, and simulation results proved the outperformance of proposed array.

关键词： DoA estimation array signal processing nested array Sparse array Fourth order cumulant Non-circular signals Underdetermined cases

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DIRECTION FINDING USING SPARSE LINEAR arrayS WITH MISSING DATA

DIRECTION FINDING USING SPARSE LINEAR ARRAYS WITH MISSING DA...

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IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Wang, Mianzhi Zhang, Zhen Nehorai, Arye Washington Univ Preston M Dept Elect & Syst Engn St Louis MO 63130 USA

ISBN: (纸本)9781509041176

We investigate the problem of direction of arrival (DOA) estimation using sparse linear arrays, such as co-prime and nested arrays, in the case of missing data resulting from sensor failures. We introduce a signal model where sensor failures occur after taking certain number of snapshots. We formulate a structured covariance estimation problem by exploiting the special geometry of sparse linear arrays, which also provides enhanced degrees of freedom. Numerical examples show that, by utilizing the information in both complete measurements and incomplete measurements, our method achieves better estimation accuracy than the traditional method using only complete measurements.

关键词： DOA estimation missing data maximum likelihood coprime array nested array

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