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).

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 Interferometer Algorithm under Phase Measurement Error

2021 ◽  
Vol 11 (2) ◽  
pp. 467
Author(s):  
Chan-Bin Ko ◽  
Joon-Ho Lee
Keyword(s):  
Measurement Error ◽  
Performance Analysis ◽  
Phase Measurement ◽  
Fundamental Problem ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Direction Finding ◽  
Circular Array ◽  
Angle Of Arrival ◽  
The Past

Direction finding has been extensively studied over the past decades and a number of algorithms have been developed. In direction finding, theoretic performance prediction is a fundamental problem. This paper addresses the performance analysis issue of interferometer-based 2D angle of arrival estimation using uniform circular array (UCA). We propose an analytic method for performance analysis of interferometer in the presence of Gaussian or uniform error in phase measurement of incident signal on each sensor. The analytic mean square error (MSE), which is approximately equal to the MSE of actual interferometer-based DOA estimation, is derived via Taylor expansion and approximation. The derived analytic MSE is useful for predicting how the MSE of the interferometer-based DOA estimation algorithm is dependent on the phase measurement error.

scholarly journals Super-Resolution-Based DOA Estimation with Wide Array Distance and Extrapolation for Vital FMCW Radar

2021 ◽  
Vol 21 (1) ◽  
pp. 23-34
Author(s):  
Sangdong Kim ◽  
Bongseok Kim ◽  
Youngseok Jin ◽  
Jonghun Lee
Keyword(s):  
Continuous Wave ◽  
Super Resolution ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Low Complexity ◽  
Field Of View ◽  
Mean Square ◽  
Fmcw Radar ◽  
Simulation Results ◽  
Resolution Algorithm

This paper proposes a super-resolution-based direction-of-arrivals (DOA) estimation with wide array distance and extrapolation for vital frequency-modulated continuous-wave (FMCW) radar. Most super-resolution algorithms employ the distance between adjacent arrays of half a wavelength, i.e., λ/2. Meanwhile, in the case of narrow field of view of FMCW radar, the resolution of the angle is maintained by increasing the spacing between the arrays even if the number of arrays decreases. In order to employ these characteristics of array spacing and resolution, the proposed algorithm confirms whether or not to use the case where the distance between the adjacent arrays is greater than λ/2. In the case of an array distance >λ/2, a super-resolution algorithm is performed to obtain the enhanced DOA resolution. Moreover, the proposed algorithm virtually generates data between antennae by using extrapolation in order to further improve the performance of the resolution. The simulation results show that the proposed algorithm achieves the results of root-mean-square error similar to conventional super-resolution algorithms while maintaining low complexity. In order to further verify the performance of the proposed estimation algorithm, we demonstrate its employment in practice: experiments in a chamber room and an indoor room were conducted.

scholarly journals Performance Analysis of Amplitude Comparison Monopulse Direction-of-Arrival Estimation

2020 ◽  
Vol 10 (4) ◽  
pp. 1246 ◽  
Author(s):  
Do-Jin An ◽  
Joon-Ho Lee
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Taylor Series Expansion ◽  
Direction Of Arrival ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Estimation Accuracy ◽  
Simulation Based ◽  
The Mean ◽  
Computationally Intensive

Amplitude-comparison monopulse radar in tracking radar uses the tracking scheme of a monopulse radar to estimate the angle components of a target. The performance of the amplitude comparison monopulse radar under measurement uncertainty is analysed. Measurement noises are modelled as Gaussian random variables. Taylor series expansion is adopted to get analytic expression of the mean square error (MSE). Estimation accuracy, in terms of the MSEs for estimate the direction-of-arrival (DOA) estimation algorithm, is usually obtained from the Monte Carlo simulation, which can be computationally intensive especially for large number of repetitions in the Monte Carlo simulation. To get reliable MSE in the Monte Carlo simulation, the number of repetitions should be very large, which implies that there is a trade-off between reliability of the MSE and computational burden in the Monte Carlo simulation. This paper shows the performance of amplitude comparison monopulse radar by linear approximation of nonlinear equations to estimate the DOA. The performance of amplitude comparison monopulse radar is quantitatively analysed via the MSEs, and the derived expression is validated by comparing the analytic MSEs with the simulation based MSEs. In addition, it is shown in the numerical results that analytically derived MSE is much less computationally intensive in comparison with the Monte Carlo simulation-based MSE, which implies that the proposed scheme in this paper results in drastic reduction in computational complexity for evaluation of the MSE.

Direction of Arrival Estimation Under Near-Field Interference Using Matrix Filter

2015 ◽  
Vol 23 (04) ◽  
pp. 1540007 ◽  
Author(s):  
Guolong Liang ◽  
Wenbin Zhao ◽  
Zhan Fan
Keyword(s):  
Near Field ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Direction Of Arrival Estimation ◽  
Far Field ◽  
Data Simulation ◽  
Estimation Algorithms ◽  
Simulation Results

Direction of arrival (DOA) estimation is of great interest due to its wide applications in sonar, radar and many other areas. However, the near-field interference is always presented in the received data, which may result in degradation of DOA estimation. An approach which can suppress the near-field interference and preserve the far-field signal desired by using a spatial matrix filter is proposed in this paper and some typical DOA estimation algorithms are adjusted to match the filtered data. Simulation results show that the approach can improve capability of DOA estimation under near-field inference efficiently.

scholarly journals An Enhanced Smoothed L0-Norm Direction of Arrival Estimation Method Using Covariance Matrix

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4403
Author(s):  
Ji Woong Paik ◽  
Joon-Ho Lee ◽  
Wooyoung Hong
Keyword(s):  
Covariance Matrix ◽  
Phased Array ◽  
Null Space ◽  
Estimation Method ◽  
Direction Of Arrival ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Direction Of Arrival Estimation ◽  
Improve Performance ◽  
Space Projection

An enhanced smoothed l0-norm algorithm for the passive phased array system, which uses the covariance matrix of the received signal, is proposed in this paper. The SL0 (smoothed l0-norm) algorithm is a fast compressive-sensing-based DOA (direction-of-arrival) estimation algorithm that uses a single snapshot from the received signal. In the conventional SL0 algorithm, there are limitations in the resolution and the DOA estimation performance, since a single sample is used. If multiple snapshots are used, the conventional SL0 algorithm can improve performance in terms of the DOA estimation. In this paper, a covariance-fitting-based SL0 algorithm is proposed to further reduce the number of optimization variables when using multiple snapshots of the received signal. A cost function and a new null-space projection term of the sparse recovery for the proposed scheme are presented. In order to verify the performance of the proposed algorithm, we present the simulation results and the experimental results based on the measured data.

scholarly journals A Direction-of-Arrival Estimation Algorithm Based on Compressed Sensing and Density-Based Spatial Clustering and Its Application in Signal Processing of MEMS Vector Hydrophone

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2191
Author(s):  
Huichao Yan ◽  
Ting Chen ◽  
Peng Wang ◽  
Linmei Zhang ◽  
Rong Cheng ◽  
...  
Keyword(s):  
Compressed Sensing ◽  
Spatial Clustering ◽  
Direction Of Arrival ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Cluster Center ◽  
Direction Of Arrival Estimation ◽  
Vector Hydrophone ◽  
Regularization Parameters ◽  
Selection Of

Direction of arrival (DOA) estimation has always been a hot topic for researchers. The complex and changeable environment makes it very challenging to estimate the DOA in a small snapshot and strong noise environment. The direction-of-arrival estimation method based on compressed sensing (CS) is a new method proposed in recent years. It has received widespread attention because it can realize the direction-of-arrival estimation under small snapshots. However, this method will cause serious distortion in a strong noise environment. To solve this problem, this paper proposes a DOA estimation algorithm based on the principle of CS and density-based spatial clustering (DBSCAN). First of all, in order to make the estimation accuracy higher, this paper selects a signal reconstruction strategy based on the basis pursuit de-noising (BPDN). In response to the challenge of the selection of regularization parameters in this strategy, the power spectrum entropy is proposed to characterize the noise intensity of the signal, so as to provide reasonable suggestions for the selection of regularization parameters; Then, this paper finds out that the DOA estimation based on the principle of CS will get a denser estimation near the real angle under the condition of small snapshots through analysis, so it is proposed to use a DBSCAN method to process the above data to obtain the final DOA estimate; Finally, calculate the cluster center value of each cluster, the number of clusters is the number of signal sources, and the cluster center value is the final DOA estimate. The proposed method is applied to the simulation experiment and the micro electro mechanical system (MEMS) vector hydrophone lake test experiment, and they are proved that the proposed method can obtain good results of DOA estimation under the conditions of small snapshots and low signal-to-noise ratio (SNR).

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