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 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 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. 

Mutual Coupling Compensation in Receiving Arrays and Its Implementation on Software Defined Radios

2021 ◽  
Vol 35 (11) ◽  
pp. 1433-1434
Author(s):  
Sana Khan ◽  
Hassan Sajjad ◽  
Mehmet Ozdemir ◽  
Ercument Arvas
Keyword(s):  
Real Time ◽  
Mutual Coupling ◽  
Linear Array ◽  
Incident Angle ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Substantial Improvement ◽  
Uniform Linear Array ◽  
Low Snr ◽  
Software Defined Radios

Mutual coupling is compensated in a four element uniform linear receiving array using software defined radios. Direction of arrival (DoA) is estimated in real-time for the array with spacing d=lambda/4. The decoupling matrix was measured using a VNA for only one incident angle. After compensation the error in DoA estimation was reduced to 5%. Comparing the DoA results with d=lambda/2 spaced Uniform Linear Array (ULA), 1.2% error was observed. Although, the experiment was performed indoors with a low SNR, the results show a substantial improvement in the estimated DoA after compensation.

scholarly journals Cramér-Rao Bound of Direction Finding Using a Uniform Hexagonal Array

2019 ◽  
pp. 1-14
Author(s):  
Grace Wakarima Ndiritu ◽  
Dominic Makaa Kitavi ◽  
Cyrus Gitonga Ngari
Keyword(s):  
Sensor Array ◽  
Graphical Representation ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Direction Finding ◽  
Direction Of Arrival Estimation ◽  
Circular Array ◽  
Hexagonal Array ◽  
Sensor Array Processing ◽  
Cramer Rao Bound

Direction-of-arrival (DOA) estimation is a key area of sensor array processing which is encountered  in many important engineering applications. Although various studies have focused on the uniform hexagonal array for direction finding, there is a scanty use of the uniform hexagonal array in conjunction with Cramer-Rao bound for direction finding estimation. The advantage of Cramér- Rao bound based on the uniform hexagonal array: overcome the problem of unwanted radiation in undesired directions. In this paper, the direction-of-arrival estimation of Cramér-Rao bound based on the uniform hexagonal array was studied. The proposed approach concentrated on deriving the array manifold vector for the uniform hexagonal array and Cramer-Rao bound of the uniform hexagonal array. The Cramér-Rao bound based on the uniform hexagonal array was compared with Cramer-Rao bound based on the uniform circular array. The conclusions are as follows. The Cramer-Rao bound of uniform hexagonal array decreases with an increase in the number of sensors. The comparison between the uniform hexagonal array and uniform circular array shows that the Cramér-Rao bound of the uniform hexagonal array was slightly higher as compared to the Cramér-Rao bound of the uniform circular array. The analytical results are supported by graphical representation.

scholarly journals Blind Direction-of-Arrival Estimation with Uniform Circular Array in Presence of Mutual Coupling

2016 ◽  
Vol 2016 ◽  
pp. 1-7 ◽  
Author(s):  
Song Liu ◽  
Lisheng Yang ◽  
Shizhong Yang ◽  
Qingping Jiang ◽  
Haowei Wu
Keyword(s):  
Mutual Coupling ◽  
Coupling Parameter ◽  
Direction Of Arrival ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Estimation Methods ◽  
Circular Array ◽  
Signal Parameters ◽  
Simulation Results ◽  
Parameter Estimation Methods

A blind direction-of-arrival (DOA) estimation algorithm based on the estimation of signal parameters via rotational invariance techniques (ESPRIT) is proposed for a uniform circular array (UCA) when strong electromagnetic mutual coupling is present. First, an updated UCA model with mutual coupling in a discrete Fourier transform (DFT) beam space is deduced, and the new manifold matrix is equal to the product of a centrosymmetric diagonal matrix and a Vandermonde-structure matrix. Then we carry out blind DOA estimation through a modified ESPRIT method, thus avoiding the need for spatial angular searching. In addition, two mutual coupling parameter estimation methods are presented after the DOAs have been estimated. Simulation results show that the new algorithm is reliable and effective especially for closely spaced signals.

Battlefield Acoustic Target Localization in Electronic Sentinel System

2012 ◽  
Vol 490-495 ◽  
pp. 1348-1352
Author(s):  
Guang Yu Liu ◽  
Cheng Zhang ◽  
Tie Lin Liu
Keyword(s):  
High Resolution ◽  
Direction Of Arrival ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Target Localization ◽  
Circular Array ◽  
Rigid Cylinder ◽  
Localization Algorithms ◽  
Acoustic Target

The problem of battlefield acoustic target localization is studied based on an array model of a uniform circular array (UCA) mounted on a rigid cylinder including beamforming technology and high resolution direction of arrival (DOA) estimation algorithm. The influence of various facts to the discussed localization algorithms is analyzed. It is concluded that the direction of the battlefield acoustic target can be achieved by the proposed high resolution DOA estimation algorithm. The performance of the eigen-beam beamforming array and the high resolution DOA estimation algorithm can be improved by the rigid cylinder.

scholarly journals Performance Analysis of Two-Dimensional Maximum Likelihood Direction-of-Arrival Estimation Algorithm Using the UCA

2017 ◽  
Vol 2017 ◽  
pp. 1-28 ◽  
Author(s):  
Yun-Seong Cho ◽  
Jeong-Min Seo ◽  
Joon-Ho Lee
Keyword(s):  
Maximum Likelihood ◽  
Performance Analysis ◽  
Taylor Series Expansion ◽  
Direction Of Arrival ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Mean Square ◽  
Circular Array ◽  
Simulation Results ◽  
Mean Square Errors

We address the performance analysis of the maximum likelihood (ML) direction-of-arrival (DOA) estimation algorithm in the case of azimuth/elevation estimation of two incident signals using the uniform circular array (UCA). Based on the Taylor series expansion and approximation, we get explicit expressions of the root mean square errors (RMSEs) of the azimuths and elevations. The validity of the derived expressions is shown by comparing the analytic results with the simulation results. The derivation in this paper is further verified by illustrating the consistency of the analytic results with the Cramer-Rao lower bound (CRLB).

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