scholarly journals High-Resolution Direction-of-Arrival Estimation via Concentric Circular Arrays

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Serdar Ozgur Ata ◽  
Cevdet Isik
Keyword(s):  
Antenna Arrays ◽  
Linear Array ◽  
Signal To Noise Ratio ◽  
Sensor Arrays ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Circular Array ◽  
Multiple Signal Classification ◽  
Circular Arrays ◽  
Source Signals

Estimating the direction of arrival (DOA) of source signals is an important research interest in application areas including radar, sonar, and wireless communications. In this paper, the problem of DOA estimation is addressed on concentric circular antenna arrays (CCA) in detail as an alternative to the well-known geometries of the uniform linear array (ULA) and uniform circular array (UCA). We define the steering matrix of the CCA geometry and investigate the performance analysis of the array in the DOA-estimation problem by simulations that are realized through varying the parameters of signal-to-noise ratio, number of sensors, and resolution angle of sensor arrays by using the MUSIC (Multiple Signal Classification) algorithm. The results present that CCA geometries provide higher angle resolutions compared to UCA geometries and require less physical area for the same number of sensor elements. However, as a cost-increasing effect, higher computational power is needed to estimate the DOA of source signals in CCAs compared to ULAs.

scholarly journals Direction of Arrival Estimation of Uncorrelated Signals Using Root-MUSIC Algorithm for ULAs and UCAs

2018 ◽  
Vol 7 (4.36) ◽  
pp. 398
Author(s):  
S. Venkata Rama Rao ◽  
A. Mallikarjuna Prasad ◽  
Ch. Santhi Rani
Keyword(s):  
Basic Problem ◽  
Signal To Noise Ratio ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Circular Array ◽  
Music Algorithm ◽  
Linear Arrays ◽  
Circular Arrays ◽  
Symmetric Structure ◽  
The Individual

In this paper, Root-MUSIC algorithm for direction of arrival (DOA) estimation of uncorrelated signals is explored both for uniform linear and uniform circular arrays. The basic problem in Uniform Linear Arrays (ULAs) is Mutual coupling between the individual elements of the antenna array. This problem is reduced in Uniform Circular Arrays (UCAs) because of its symmetric structure. The DOA estimation of uncorrelated signals that have different power levels is simulated on a MATLAB environment. And the noise consider is white across all the array elements. The factors considered for simulation are number of number of snapshots, array elements, radius of circular array, array length, and signal to noise ratio. 

scholarly journals A Robust Direction of Arrival Estimation Method for Uniform Circular Array

Sensors ◽  
2019 ◽  
Vol 19 (20) ◽  
pp. 4427
Author(s):  
Xu ◽  
Wu ◽  
Yu ◽  
Guang
Keyword(s):  
Array Signal Processing ◽  
Linear Array ◽  
Estimation Method ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Circular Array ◽  
Source Signal ◽  
Random Sample Consensus ◽  
Esprit Algorithm ◽  
Source Signals

Estimating the Direction of Arrival (DOA) is a basic and crucial problem in array signal processing. The existing DOA methods fail to obtain reliable and accurate results when noise and reverberation occur in real applications. In this paper, an accurate and robust estimation method for estimating the DOA of sources signal is proposed. Incorporating the Estimating Signal Parameters via Rotational Invariance Techniques (ESPRIT) algorithm with the RANdom SAmple Consensus (RANSAC) algorithm gives rise to the RAN-ESPRIT method, which removes outliers automatically in noise-corrupted environments. In this work, a uniform circular array (UCA) is converted into a virtual uniform linear array (ULA) to begin with. Then, the covariance matrix of the received signals of the virtual linear array is reconstructed, and the ESPRIT algorithm is deployed to estimate initial DOA of the source signal. Finally, the modified RANSAC method with automatically selected thresholds is used to fit the source signal to obtain accurate DOA. The proposed method can remove the unreliable DOA feature data and leads to more accuracy of DOA estimation of source signals in reverberation environments. Experimental results demonstrate that the proposed method is more robust and efficient compared to the traditional methods (i.e., ESPRIT, TLS-ESPRIT).

scholarly journals DOA Estimation for UCAs Based on Virtual Subarray Beamforming Technique

2018 ◽  
Vol 232 ◽  
pp. 01012
Author(s):  
Bo Xu ◽  
Zhigang Huang
Keyword(s):  
Signal To Noise Ratio ◽  
Estimation Method ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Signal To Noise ◽  
Circular Arrays ◽  
Noise Ratio ◽  
Subarray Beamforming ◽  
Beamforming Technique

Direction-of-arrival (DOA) estimation is always a hotspot research in the fields of radar, sonar, communication and so on. And uniform circular arrays (UCAs) are more attractive in the context of DOA estimation since their symmetrical structures have potential to provide two directions coverage. This paper proposed a new DOA estimation method for UCAs via virtual subarray beamforming technique. The method would provide an acceptable DOA estimate even if the number of sources is great than the number of array elements. Also, the performance of the proposed method would hold good when the snapshot length or the signal-to-noise ratio (SNR) is small. Simulations show that the proposed technique offers significantly improved estimation resolution, capacity, and accuracy relative to the existing techniques.

scholarly journals Direction of Arrival Estimation of GPS Narrowband Jammers Using High-Resolution Techniques

Sensors ◽  
2019 ◽  
Vol 19 (24) ◽  
pp. 5532 ◽  
Author(s):  
Mohamed Moussa ◽  
Abdalla Osman ◽  
Mohamed Tamazin ◽  
Michael J. Korenberg ◽  
Aboelmagd Noureldin
Keyword(s):  
Linear Array ◽  
Classical Method ◽  
Spatial Separation ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Circular Array ◽  
Gps Receivers ◽  
Fast Orthogonal Search ◽  
Jamming Detection ◽  
Ultimate Objective

GPS jamming is a considerable threat to applications that rely on GPS position, velocity, and time. Jamming detection is the first step in the mitigation process. The direction of arrival (DOA) estimation of jamming signals is affected by resolution. In the presence of multiple jamming sources whose spatial separation is very narrow, an incorrect number of jammers can be detected. Consequently, mitigation will be affected. The ultimate objective of this research is to enhance GPS receivers’ anti-jamming abilities. This research proposes an enhancement to the anti-jamming detection ability of GPS receivers that are equipped with a uniform linear array (ULA) and uniform circular array (UCA). The proposed array processing method utilizes fast orthogonal search (FOS) to target the accurate detection of the DOA of both single and multiple in-band CW jammers. Its performance is compared to the classical method and MUSIC. GPS signals obtained from a Spirent GSS6700 simulator and CW jamming signals were used. The proposed method produces a threefold advantage, higher accuracy DOA estimates, amplitudes, and a correct number of jammers. Therefore, the anti-jamming process can be significantly improved by limiting the erroneous spatial attenuation of GPS signals arriving from an angle close to the jammer.

scholarly journals Direction of Arrival Using Uniform Circular Array based on 2-D MUSIC Algorithm

2018 ◽  
Vol 12 (1) ◽  
pp. 30
Author(s):  
Mohammed Amine Ihedrane ◽  
Seddik Bri
Keyword(s):  
Dielectric Permittivity ◽  
Patch Antenna ◽  
Direction Of Arrival ◽  
Dielectric Substrate ◽  
Signal Classification ◽  
Circular Array ◽  
Music Algorithm ◽  
Multiple Signal Classification ◽  
Linear Arrays ◽  
Circular Arrays

<p>This study presents the conception, simulation, realisation and characterisation of a patch antenna for Wi-Fi. The antenna is designed at the frequency of 2.45 GHz; the dielectric substrate used is FR4_epoxy which has a dielectric permittivity of 4.4.this patch antenna is used to estimate the direction of arrival (DOA) using 2-D Multiple Signal Classification (2-D MUSIC) the case of the proposed  uniform circular arrays (UCA). The comparison between Uniform circular arrays and Uniform Linear arrays (ULA) demonstrate that the proposed structure give better angles resolutions compared to ULAs.</p>

scholarly journals DOA Estimation in Low SNR Environment through Coprime Antenna Arrays: An Innovative Approach by Applying Flower Pollination Algorithm

2021 ◽  
Vol 11 (17) ◽  
pp. 7985
Author(s):  
Khurram Hameed ◽  
Shanshan Tu ◽  
Nauman Ahmed ◽  
Wasim Khan ◽  
Ammar Armghan ◽  
...  
Keyword(s):  
Antenna Arrays ◽  
Signal To Noise Ratio ◽  
Sensor Arrays ◽  
Doa Estimation ◽  
Cumulative Distribution ◽  
Estimation Accuracy ◽  
Noise Robustness ◽  
Flower Pollination Algorithm ◽  
Flower Pollination ◽  
Highly Nonlinear

The design of the modern computing paradigm of heuristics is an innovative development for parameter estimation of direction of arrival (DOA) using sparse antenna arrays. In this study, the optimization strength of the flower pollination algorithm (FPA) is exploited for the DOA estimation in a low signal to noise ratio (SNR) regime by applying coprime sensor arrays (CSA). The enhanced degree of freedom (DOF) is achieved with FPA by investigating the global minima of highly nonlinear cost function with multiple local minimas. The sparse structure of CSA demonstrates that the DOF up to O(MN) is achieved by employing M+N CSA elements, where M and N are the numbers of antenna elements used to construct the CSA . Performance analysis is conducted for estimation accuracy, robustness against noise, robustness against snapshots, frequency distribution of root mean square error (RMSE), variability analysis of RMSE, cumulative distribution function (CDF) of RMSE over Monte Carlo runs and the comparative studies of particle swarm optimization (PSO). These reveal the worth of the proposed methodology for estimating DOA.

scholarly journals Direction of Arrival Estimation Using Augmentation of Coprime Arrays

Information ◽  
2018 ◽  
Vol 9 (11) ◽  
pp. 277 ◽  
Author(s):  
Tehseen Hassan ◽  
Fei Gao ◽  
Babur Jalal ◽  
Sheeraz Arif
Keyword(s):  
Covariance Matrix ◽  
Degrees Of Freedom ◽  
Direction Of Arrival ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Spatial Smoothing ◽  
Multiple Signal Classification ◽  
Coprime Arrays ◽  
The Difference ◽  
Source Signals

Recently, direction of arrival (DOA) estimation premised on the sparse arrays interpolation approaches, such as co-prime arrays (CPA) and nested array, have attained extensive attention because of the effectiveness and capability of providing higher degrees of freedom (DOFs). The co-prime array interpolation approach can detect O(MN) paths with O(M + N) sensors in the array. However, the presence of missing elements (holes) in the difference coarray has limited the number of DOFs. To implement co-prime coarray on subspace based DOA estimation algorithm namely multiple signal classification (MUSIC), a reshaping operation followed by the spatial smoothing technique have been presented in the literature. In this paper, an active coarray interpolation (ACI) is proposed to efficiently recovering the covariance matrix of the augmented coarray from the original covariance matrix of source signals with no vectorizing and spatial smoothing operation; thus, the computational complexity reduces significantly. Moreover, the numerical simulations of the proposed ACI approach offers better performance compared to its counterparts.

scholarly journals Low Complexity Sparse Beamspace DOA Estimation Via Single Measurement Vectors for Uniform Circular Array

2021 ◽  
Author(s):  
Di Zhao ◽  
Weijie Tan ◽  
Zhongliang Deng ◽  
Gang Li
Keyword(s):  
Optimization Problem ◽  
Signal To Noise Ratio ◽  
Estimation Method ◽  
Doa Estimation ◽  
Low Complexity ◽  
Estimation Methods ◽  
Circular Array ◽  
Single Measurement ◽  
Signal Model ◽  
Convex Optimization Problem

Abstract In this paper, we present a low complexity beamspace direction-of-arrival (DOA) estimation method for uniform circular array (UCA), which is based on the single measurement vectors (SMVs) via vectorization of sparse covariance matrix. In the proposed method, we rstly transform the signal model of UCA to that of virtual uniform linear array (ULA) in beamspace domain using the beamspace transformation (BT). Subsequently, by applying the vectorization operator on the virtual ULA-like array signal model, a new dimension-reduction array signal model consists of SMVs based on Khatri-Rao (KR) product is derived. And then, the DOA estimation is converted to the convex optimization problem. Finally, simulations are carried out to verify the eectiveness of the proposed method, the results show that without knowledge of the signal number, the proposed method not only has higher DOA resolution than subspace-based methods in low signal-to-noise ratio (SNR), but also has much lower computational complexity comparing other sparse-like DOA estimation methods.

scholarly journals Minimum Array Elements for Resolution of Several Direction of Arrival Estimation Methods in Various Noise-Level Environments

2018 ◽  
Vol 2 ◽  
pp. 87-94
Author(s):  
Ismail El Ouargui ◽  
Said Safi ◽  
Miloud Frikel
Keyword(s):  
Gaussian Noise ◽  
Noise Level ◽  
Signal To Noise Ratio ◽  
Additive White Gaussian Noise ◽  
Direction Of Arrival ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Estimation Methods ◽  
Minimum Number ◽  
Informative Signals

The resolution of a Direction of Arrival (DOA) estimation algorithm is determined based on its capability to resolve two closely spaced signals. In this paper, authors present and discuss the minimum number of array elements needed for the resolution of nearby sources in several DOA estimation methods. In the real world, the informative signals are corrupted by Additive White Gaussian Noise (AWGN). Thus, a higher signal-to-noise ratio (SNR) offers a better resolution. Therefore, we show the performance of each method by applying the algorithms in different noise level environments.

Direction of Arrival Estimation with Compact Array Antennas

2009 ◽  
pp. 201-216
Author(s):  
Eddy Taillefer ◽  
Jun Cheng ◽  
Takashi Ohira
Keyword(s):  
Single Port ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Signal Classification ◽  
Direction Of Arrival Estimation ◽  
Multiple Signal Classification ◽  
Array Antennas ◽  
Power Pattern ◽  
Parasitic Array ◽  
Compact Array

This chapter presents direction of arrival (DoA) estimation with a compact array antenna using methods based on reactance switching. The compact array is the single-port electronically steerable parasitic array radiator (Espar) antenna. The antenna beam pattern is controlled though parasitic elements loaded with reactances. DoA estimation using an Espar antenna is proposed with the power pattern cross correlation (PPCC), reactance-domain (RD) multiple signal classification (MUSIC), and, RD estimation of signal parameters via rotational invariance techniques (ESPRIT) algorithms. The three methods exploit the reactance diversity provided by an Espar antenna to correlate different antenna output signals measured at different times and for different reactance values. The authors hope that this chapter allows the researchers to appreciate the issues that may be encountered in the implementation of direction-finding application with a single-port compact array like the Espar antenna.

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