scholarly journals An Effective Technique for Enhancing Direction Finding Performance of Virtual Arrays

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Wenxing Li ◽  
Xiaojun Mao ◽  
Wenhua Yu ◽  
Chongyi Yue
Keyword(s):  
Antenna Array ◽  
Interpolation Method ◽  
Doa Estimation ◽  
Direction Finding ◽  
Estimation Accuracy ◽  
Signal Subspace ◽  
Effective Technique ◽  
Resolution Capability ◽  
Significant Bias ◽  
Virtual Array

The array interpolation technology that is used to establish a virtual array from a real antenna array is widely used in direction finding. The traditional interpolation transformation technology causes significant bias in the directional-of-arrival (DOA) estimation due to its transform errors. In this paper, we proposed a modified interpolation method that significantly reduces bias in the DOA estimation of a virtual antenna array and improves the resolution capability. Using the projection concept, this paper projects the transformation matrix into the real array data covariance matrix; the operation not only enhances the signal subspace but also improves the orthogonality between the signal and noise subspace. Numerical results demonstrate the effectiveness of the proposed method. The proposed method can achieve better DOA estimation accuracy of virtual arrays and has a high resolution performance compared to the traditional interpolation method.

scholarly journals Transmit and Receive Array Structure Design of Two-Dimensional hybrid Phased-MIMO Radar based on Nested Array

2018 ◽  
Vol 232 ◽  
pp. 02052
Author(s):  
Tianhao Cheng ◽  
Buhong Wang ◽  
Qiaoge Liu ◽  
Jiwei Tian
Keyword(s):  
Design Method ◽  
Doa Estimation ◽  
Mimo Radar ◽  
Structure Design ◽  
Estimation Accuracy ◽  
Two Dimensional ◽  
Simulation Experiments ◽  
Virtual Array ◽  
Array Structure ◽  
Receive Array

In order to reduce the loss of Degree of Freedom (DOF) brought by the transmit subarray splitting of two-dimensional hybrid phased-MIMO radar, this paper presents a design method of transmitting and receiving array based on nested array structure. Firstly, a two-dimensional hybrid phased-MIMO radar transmitting array based on one-dimensional nested array is presented. On this basis, the receiving end is set as a nested array, and finally a virtual array and difference coarray are formed to expand the number of virtual array elements. The expansion increases the DOF of arrays while preserving the advantages of hybrid phased-MIMO radars. Simulation experiments show that compared with the traditional and coprime hybrid phased-MIMO radar, the proposed method can effectively improve the array DOF and Direction-of-Arrival (DOA) estimation accuracy.

scholarly journals Direction-of-Arrival Estimation of Virtual Array Signals Based on Doppler Effect

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Feng Zhao ◽  
Xia Hao ◽  
Hongbin Chen
Keyword(s):  
High Speed ◽  
Estimation Method ◽  
High Mobility ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Estimation Accuracy ◽  
Music Algorithm ◽  
Moving Sources ◽  
Direction Of Departure ◽  
Virtual Array

The estimation accuracy of direction-of-departure (DOD) and direction-of-arrival (DOA) is reduced because of Doppler shifts caused by the high-speed moving sources. In this paper, an improved DOA estimation method which combines the forward-backward spatial smoothing (FBSS) technique with the MUSIC algorithm is proposed for virtual MIMO array signals in high mobility scenarios. Theoretical analysis and experiment results demonstrate that the resolution capability can be significantly improved by using the proposed method compared to the MUSIC algorithm for the moving sources with limited array elements, especially the DOA which can still be accurately estimated when the sources are much closely spaced.

scholarly journals A Novel Designed Sparse Array for Noncircular Sources with High Degree of Freedom

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Yan-kui Zhang ◽  
Hai-yun Xu ◽  
Da-ming Wang ◽  
Bin Ba ◽  
Si-yao Li
Keyword(s):  
Design Method ◽  
Doa Estimation ◽  
Degree Of Freedom ◽  
Estimation Accuracy ◽  
Sparse Array ◽  
Array Configuration ◽  
Virtual Array ◽  
Array Aperture ◽  
Coprime Array ◽  
High Degree

The existing coprime array is mainly applicable to circular sources, while the virtual array degree of freedom (DOF) for noncircular sources is enhanced limitedly. In order to perfect the array DOF and the direction of arrival (DOA) estimation accuracy, a high degree of freedom sparse array design method for noncircular sources is put forward. Firstly, the method takes the advantages of the characteristic of the noncircular sources to expand the array manifold and then explores and solves the location distribution of the physical array sensors on the basis of the virtual array model with the help of the searching approach. The array configuration can obtain the longest continuous virtual array. The comparisons between the proposed array configuration and the common array configurations are advanced. The simulation experiments show that the sparse array presented in this paper can effectively increase the continuous virtual array aperture of noncircular sources, improve the array DOF and DOA estimation accuracy, and achieve the purpose of better estimation of multiple DOAs in underdetermined conditions.

scholarly journals Thinned Virtual Array for Cramer Rao Bound Optimization in MIMO Radar

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Xia Li ◽  
Buhong Wang
Keyword(s):  
Performance Indicator ◽  
Multiple Input Multiple Output ◽  
Doa Estimation ◽  
Direction Finding ◽  
Mimo Radar ◽  
Combinatorial Problems ◽  
Array Configuration ◽  
Virtual Array ◽  
Array Aperture ◽  
Cramer Rao Bound

By transmitting multiple independent waveforms at the transmit side and processing echoes of spatial targets at the receive side, Multiple Input Multiple Output (MIMO) radar enjoys virtual array aperture expansion and more degree of freedom (DOF), both of which favors the application of direction finding or estimation of direction of arrival (DOA). The expanded virtual aperture provides higher angular resolution which also promotes the precision of DOA estimation, and the extra DOF brought by waveform diversity can be leveraged to focus energy in certain spatial region for better direction-finding capacity. However, beamspace methods which match certain beampatterns suffer from deteriorated performance and complexity in implementation, and the advantage of virtual array aperture is limited by its virtual element redundancy. As an important performance indicator of DOA estimation, Cramer–Rao Bound (CRB) is closely connected to the array configuration of the system. To reduce the complexity of the system and improve CRB performance at the same time, in this paper, the virtual array of MIMO radar is designed directly by selecting outputs from matched filters at the receive side. For the sake of fair comparison, both scenarios with and without priori directions are considered to obtain optimized virtual array configuration, respectively. The original combinatorial problems are approximated by sequential convex approximations methods which produce solutions with efficiency. Numerical results demonstrate that the proposed method can provide thinned virtual arrays with excellent CRB performance.

scholarly journals Partial Dictionary Based Off-Grid DOA Estimation Using Combined Coprime and Nested Array

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Jianfeng Li ◽  
Xiong Xu ◽  
Ping Li ◽  
Qiting Zhang
Keyword(s):  
Angular Resolution ◽  
State Of The Art ◽  
Estimation Method ◽  
Doa Estimation ◽  
Estimation Accuracy ◽  
Reconstruction Method ◽  
Phase Ambiguity ◽  
Virtual Array ◽  
Coprime Array ◽  
Cyclic Phase

A partial dictionary based direction of arrival (DOA) estimation method which addresses the off-grid problem and exploits combined coprime and nested array (CCNA) is proposed. Compared to general coprime array, CCNA yields two sparse coprime subarrays in the coarray domain by adding a third subarray in the physical-array domain. To ensure the DOA estimation performance, the subarray with larger aperture is chosen, and the cyclic phase ambiguity caused by the sparse subarray allows partial dictionary covering arbitrary cycle to represent the whole atoms, and then, the off-grid sparse reconstruction method is developed to amend the grid mismatch. After the sparse recovery and off-grid compensation, ambiguous DOA estimations can be eliminated by substituting the estimations into the whole virtual array. Multiple simulations verify that the proposed algorithm outperforms the other state-of-the-art methods in terms of DOA estimation accuracy and angular resolution.

scholarly journals Tensor-Based DOA Estimation for Array Virtual Translation

2021 ◽  
Author(s):  
Jiaqiang Peng ◽  
Guimei Zheng
Keyword(s):  
Tensor Decomposition ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Processing Technique ◽  
Estimation Accuracy ◽  
Signal Subspace ◽  
Spatial Smoothing ◽  
Factor Matrix ◽  
Estimation Algorithms ◽  
Array Aperture

Abstract In order to make up for the problem that the tensor-based spatial smoothing DOA estimation algorithm cannot make good use of the physical aperture of the array, this paper proposes a tensor-based array virtual translation DOA estimation algorithm. Under the framework of the tensor-based DOA estimation algorithm, the algorithm applies the array virtual translation technique to the factor matrix obtained after tensor decomposition, which can be expanded into signal subspace and approximately has a Vandermonde structure. Furthermore, the available array aperture of the algorithm is expanded, the estimation accuracy is improved, and the limitation of the physical array aperture on the algorithm’s multi-target estimation ability is broken. Since the processing technique proposed in this paper has nothing to do with the construction of tensors, this technique is suitable for all DOA estimation algorithms based on tensors. Theoretical analysis and numerical simulation verify the effectiveness of the algorithm proposed in this paper.

scholarly journals Underdetermined DOA Estimation for Wideband Signals via Focused Atomic Norm Minimization

Entropy ◽  
2020 ◽  
Vol 22 (3) ◽  
pp. 359 ◽  
Author(s):  
Juan Shi ◽  
Qunfei Zhang ◽  
Weijie Tan ◽  
Linlin Mao ◽  
Lihuan Huang ◽  
...  
Keyword(s):  
Information Theory ◽  
Signal Processing ◽  
Covariance Matrix ◽  
Estimation Method ◽  
Doa Estimation ◽  
Estimation Methods ◽  
Estimation Accuracy ◽  
Norm Minimization ◽  
Atomic Norm ◽  
Virtual Array

In underwater acoustic signal processing, direction of arrival (DOA) estimation can provide important information for target tracking and localization. To address underdetermined wideband signal processing in underwater passive detection system, this paper proposes a novel underdetermined wideband DOA estimation method equipped with the nested array (NA) using focused atomic norm minimization (ANM), where the signal source number detection is accomplished by information theory criteria. In the proposed DOA estimation method, especially, after vectoring the covariance matrix of each frequency bin, each corresponding obtained vector is focused into the predefined frequency bin by focused matrix. Then, the collected averaged vector is considered as virtual array model, whose steering vector exhibits the Vandermonde structure in terms of the obtained virtual array geometries. Further, the new covariance matrix is recovered based on ANM by semi-definite programming (SDP), which utilizes the information of the Toeplitz structure. Finally, the Root-MUSIC algorithm is applied to estimate the DOAs. Simulation results show that the proposed method outperforms other underdetermined DOA estimation methods based on information theory in term of higher estimation accuracy.

scholarly journals DOA Estimation Performance Analysis and Verification of Dual Crossed-Loop/Monopole Antenna Array

2019 ◽  
Vol 2019 ◽  
pp. 1-8
Author(s):  
Sijie Wang ◽  
Biyang Wen ◽  
Yingwei Tian
Keyword(s):  
Antenna Array ◽  
Estimation Error ◽  
Doa Estimation ◽  
Hf Radar ◽  
Estimation Accuracy ◽  
Dominant Factor ◽  
Application Range ◽  
Estimation Performance ◽  
Wave Radar ◽  
Target Monitoring

The compact high-frequency surface wave radar using a crossed-loop/monopole (CLM) antenna as the receiving sensor has been widely used in ocean remote sensing and target monitoring. However, the direction of arrival (DOA) estimation accuracy of a single CLM antenna is the dominant factor that restricts the target monitoring performance of the compact HF radar. Besides, the single CLM antenna can estimate two signals simultaneously at most, but its effectiveness is challenged by the pattern distortion and the existence of coherent sources, which limits the application range of the compact HF radar. In this study, a compact array combining two CLM antennas is proposed to improve the DOA estimation accuracy and solve the multisource DOA estimation problem. The estimation error and multisource DOA estimation performance of a dual CLM antenna array are analyzed by formula derivation and simulation. Furthermore, the field experiment results are given to demonstrate the performance improvement of the dual CLM antenna array.

scholarly journals Spectral Domain Sparse Representation for DOA Estimation of Signals with Large Dynamic Range

Sensors ◽  
2021 ◽  
Vol 21 (15) ◽  
pp. 5164
Author(s):  
Jacob Compaleo ◽  
Inder J. Gupta
Keyword(s):  
Sparse Representation ◽  
Antenna Array ◽  
Dynamic Range ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Single Step ◽  
Window Function ◽  
Spectral Domain ◽  
Low Sidelobe ◽  
Weighting Window

Recently, we proposed a Spectral Domain Sparse Representation (SDSR) approach for the direction-of-arrival estimation of signals incident to an antenna array. In the approach, sparse representation is applied to the conventional Bartlett spectra obtained from snapshots of the signals received by the antenna array to increase the direction-of-arrival (DOA) estimation resolution and accuracy. The conventional Bartlett spectra has limited dynamic range, meaning that one may not be able to identify the presence of weak signals in the presence of strong signals. This is because, in the conventional Bartlett spectra, uniform weighting (window) is applied to signals received by various antenna elements. Apodization can be used in the generation of Bartlett spectra to increase the dynamic range of the spectra. In Apodization, more than one window function is used to generate different portions of the spectra. In this paper, we extend the SDSR approach to include Bartlett spectra obtained with Apodization and to evaluate the performance of the extended SDSR approach. We compare its performance with a two-step SDSR approach and with an approach where Bartlett spectra is obtained using a low sidelobe window function. We show that an Apodization Bartlett-based SDSR approach leads to better performance with just single-step processing.

Sign in / Sign up

Export Citation Format

Share Document