Nested sensor array extension factors required to match the peak sidelobe height of a uniform linear array

2019 ◽  
Vol 145 (3) ◽  
pp. 1733-1733
Author(s):  
Hossam Elsaadawy ◽  
Kayla M. Houte ◽  
Camille LeBlanc ◽  
James M. Slezak ◽  
Kaushallya Adhikari
Keyword(s):  
Sensor Array ◽  
Linear Array ◽  
Uniform Linear Array ◽  
Array Extension

Sensor Array Self-Calibration for Two-Dimensional Direction of Arrival Estimation

2012 ◽  
Vol 490-495 ◽  
pp. 534-537
Author(s):  
Da Wei Xiao ◽  
Jin Fang Cheng ◽  
Yi Liu
Keyword(s):  
Sensor Array ◽  
Linear Array ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Calibration Method ◽  
Estimation Accuracy ◽  
Two Dimensional ◽  
Uniform Linear Array ◽  
Actual Measurement ◽  
Self Calibration

In recent years, high-resolution Direction of Arrival (DOA) estimation with a sensor array has become indispensable for various applications. In actual measurement, however, DOA estimation accuracy is deteriorated by many error factors. For a uniform linear array (ULA), there exist algorithms for self-calibration for single-dimensional (1-D) DOA estimation. In this paper, we develop a simple self-calibration method for two-dimensional (2-D) DOA estimation with an L-shaped array.

scholarly journals Efficient AM Algorithms for Stochastic ML Estimation of DOA

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Haihua Chen ◽  
Shibao Li ◽  
Jianhang Liu ◽  
Yiqing Zhou ◽  
Masakiyo Suzuki
Keyword(s):  
Computational Complexity ◽  
Optimization Problem ◽  
Sensor Array ◽  
Array Signal Processing ◽  
Linear Array ◽  
Variable Parameter ◽  
Numerical Instability ◽  
Uniform Linear Array ◽  
Ml Estimation ◽  
Irreducible Form

The estimation of direction-of-arrival (DOA) of signals is a basic and important problem in sensor array signal processing. To solve this problem, many algorithms have been proposed, among which the Stochastic Maximum Likelihood (SML) is one of the most concerned algorithms because of its high accuracy of DOA. However, the estimation of SML generally involves the multidimensional nonlinear optimization problem. As a result, its computational complexity is rather high. This paper addresses the issue of reducing computational complexity of SML estimation of DOA based on the Alternating Minimization (AM) algorithm. We have the following two contributions. First using transformation of matrix and properties of spatial projection, we propose an efficient AM (EAM) algorithm by dividing the SML criterion into two components. One depends on a single variable parameter while the other does not. Second when the array is a uniform linear array, we get the irreducible form of the EAM criterion (IAM) using polynomial forms. Simulation results show that both EAM and IAM can reduce the computational complexity of SML estimation greatly, while IAM is the best. Another advantage of IAM is that this algorithm can avoid the numerical instability problem which may happen in AM and EAM algorithms when more than one parameter converges to an identical value.

Comparison between DOA Estimation Subspace methods for incoherent and coherent signals

2015 ◽  
Vol 1 ◽  
pp. 18
Author(s):  
Ahmed Abdalla ◽  
Suhad Mohammed ◽  
Tang Bin ◽  
Jumma Mary Atieno ◽  
Abdelazeim Abdalla
Keyword(s):  
Linear Array ◽  
Doa Estimation ◽  
Far Field ◽  
Matlab Simulation ◽  
Subspace Methods ◽  
Coherent Signals ◽  
Uniform Linear Array ◽  
Pros And Cons ◽  
Basic Concepts ◽  
And Performance

This paper considers the problem of estimating the direction of arrival (DOA) for the both incoherent and coherent signals from narrowband sources, located in the far field in the case of uniform linear array sensors. Three different methods are analyzed. Specifically, these methods are Music, Root-Music and ESPRIT. The pros and cons of these methods are identified and compared in light of different viewpoints. The performance of the three methods is evaluated, analytically, when possible, and by Matlab simulation. This paper can be a roadmap for beginners in understanding the basic concepts of DOA estimation issues, properties and performance.

scholarly journals Micro Non-Uniform Linear Array (MNULA) for Ultrasound Plane Wave Imaging

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 640
Author(s):  
Yujia Tang ◽  
Zhangjian Li ◽  
Yaoyao Cui ◽  
Chen Yang ◽  
Jiabing Lv ◽  
...  
Keyword(s):  
Plane Wave ◽  
Linear Array ◽  
Near Field ◽  
Uniform Linear Array ◽  
Imaging Technology ◽  
Linear Arrays ◽  
Imaging Quality ◽  
Imaging Results ◽  
Wave Imaging ◽  
Laboratory Technology

Ultrasound plane wave imaging technology has been applied to more clinical situations than ever before because of its rapid imaging speed and stable imaging quality. Most transducers used in plane wave imaging are linear arrays, but their structures limit the application of plane wave imaging technology in some special clinical situations, especially in the endoscopic environment. In the endoscopic environment, the size of the linear array transducer is strictly miniaturized, and the imaging range is also limited to the near field. Meanwhile, the near field of a micro linear array has serious mutual interferences between elements, which is against the imaging quality of near field. Therefore, we propose a new structure of a micro ultrasound linear array for plane wave imaging. In this paper, a theoretical comparison is given through sound field and imaging simulations. On the basis of primary work and laboratory technology, micro uniform and non-uniform linear arrays were made and experimented with the phantom setting. We selected appropriate evaluation parameters to verify the imaging results. Finally, we concluded that the micro non-uniform linear array eliminated the artifacts better than the micro uniform linear array without the additional use of signal processing methods, especially for target points in the near-field. We believe this study provides a possible solution for plane wave imaging in cramped environments like endoscopy.

scholarly journals Compressed Sensing-Based DOA Estimation with Unknown Mutual Coupling Effect

Electronics ◽  
2018 ◽  
Vol 7 (12) ◽  
pp. 424 ◽  
Author(s):  
Peng Chen ◽  
Zhenxin Cao ◽  
Zhimin Chen ◽  
Linxi Liu ◽  
Man Feng
Keyword(s):  
Compressed Sensing ◽  
Mutual Coupling ◽  
Linear Array ◽  
State Of The Art ◽  
Coupling Effect ◽  
Estimation Method ◽  
Doa Estimation ◽  
System Model ◽  
Reconstruction Problem ◽  
Uniform Linear Array

The performance of a direction-finding system is significantly degraded by the imperfection of an array. In this paper, the direction-of-arrival (DOA) estimation problem is investigated in the uniform linear array (ULA) system with the unknown mutual coupling (MC) effect. The system model with MC effect is formulated. Then, by exploiting the signal sparsity in the spatial domain, a compressed-sensing (CS)-based system model is proposed with the MC coefficients, and the problem of DOA estimation is converted into that of a sparse reconstruction. To solve the reconstruction problem efficiently, a novel DOA estimation method, named sparse-based DOA estimation with unknown MC effect (SDMC), is proposed, where both the sparse signal and the MC coefficients are estimated iteratively. Simulation results show that the proposed method can achieve better performance of DOA estimation in the scenario with MC effect than the state-of-the-art methods, and improve the DOA estimation performance about 31.64 % by reducing the MC effect by about 4 dB.

An Improved Clutter Suppression Method for Non-Sidelooking Uniform Linear Array Antennas Airborne Radar

2013 ◽  
Vol 681 ◽  
pp. 175-180
Author(s):  
Jun Zhao ◽  
Xu Hang
Keyword(s):  
Linear Array ◽  
Compensation Method ◽  
Airborne Radar ◽  
Clutter Suppression ◽  
Uniform Linear Array ◽  
Array Antennas ◽  
Compensation Methods ◽  
Suppression Method ◽  
Simulation Results ◽  
Independent Identically Distributed

The clutter distribution of airborne radar with non-sidelooking uniform linear array antennas varies with ranges and samples in different range gates are not independent identically distributed vectors, so that the statistical STAP methods degrade greatly. In this paper, an improved clutter range dependence compensation method for airborne radar with uniform linear array is proposed. This method involves in a preprocessing with ADC method to align the mainlobe of clutter spectrum in different range gates and subsequently clutter suppression in other azimuths with EDBU technology. Simulation results show the proposed method can reduce the clutter spectrum dispersion significantly and outperform conventional local compensation methods.

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