scholarly journals A Propagator Method for Bistatic Coprime EMVS-MIMO Radar

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Yongqiang Yang ◽  
Ningjun Ruan ◽  
Guanjun Huang ◽  
Junpeng Shi ◽  
Fangqing Wen
Keyword(s):  
Multiple Input Multiple Output ◽  
Cross Product ◽  
Mimo Radar ◽  
Signal Subspace ◽  
Direction Of Departure ◽  
Vector Sensors ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Array Aperture ◽  
Coprime Array

In this paper, a novel two-dimensional (2D) direction-of-departure (DOD) and 2D direction-of-arrival (DOA) estimate algorithm is proposed for bistatic multiple-input multiple-output (MIMO) radar system equipped with coprime electromagnetic vector sensors (EMVS) arrays. Firstly, we construct the propagator to obtain the signal subspace. Then, the ambiguous angles are estimated by using rotation invariant technique. Based on the characteristic of coprime array, the unambiguous angles estimation is achieved. Finally, all azimuth angles estimation is followed via vector cross product. Compared to the existing uniform linear array, coprime MIMO radar is occupying large array aperture, and the proposed algorithm does not need to obtain signal subspace by eigendecomposition. In contrast to the state-of-the-art algorithms, the proposed algorithm shows better estimation performance and simpler computation performance. The proposed algorithm’s effectiveness is proved by simulation results.

scholarly journals A PE-MUSIC Algorithm for Sparse Array in MIMO Radar

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Yucai Pang ◽  
Song Liu ◽  
Yun He
Keyword(s):  
Multiple Input Multiple Output ◽  
Mimo Radar ◽  
Music Algorithm ◽  
Sparse Arrays ◽  
Sparse Array ◽  
Direction Of Departure ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Array Aperture ◽  
The Cost

Larger array aperture is provided by sparse arrays than uniform ones, which can improve the angle estimation resolution and reduce the cost of system evidently. However, manifold ambiguity is introduced due to the array sparsity. In this paper, a Power Estimation Multiple-Signal Classification (PE-MUSIC) algorithm is proposed to solve the manifold ambiguity of arbitrary sparse arrays for uncorrelated sources in Multiple-Input Multiple-Output (MIMO) radar. First, the paired direction of departure (DOD) and direction of arrival (DOA) are obtained for all targets by MUSIC algorithm, including the true and spurious ones; then, the well-known Davidon–Fletcher–Powell (DFP) algorithm is applied to estimate all targets’ power values, among which the value of a spurious target trends to zero. Therefore, the ambiguity of sparse array in MIMO radar can be cleared. Simulation results verify the effectiveness and feasibility of the method.

scholarly journals Angle Estimation for MIMO Radar in the Presence of Gain-Phase Errors with One Instrumental Tx/Rx Sensor: A Theoretical and Numerical Study

2021 ◽  
Vol 13 (15) ◽  
pp. 2964
Author(s):  
Fangqing Wen ◽  
Junpeng Shi ◽  
Xinhai Wang ◽  
Lin Wang
Keyword(s):  
Numerical Study ◽  
Multiple Input Multiple Output ◽  
Mimo Radar ◽  
Phase Errors ◽  
Direction Of Departure ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Angle Pair ◽  
Parallel Factor ◽  
Parafac Decomposition

Ideal transmitting and receiving (Tx/Rx) array response is always desirable in multiple-input multiple-output (MIMO) radar. In practice, nevertheless, Tx/Rx arrays may be susceptible to unknown gain-phase errors (GPE) and yield seriously decreased positioning accuracy. This paper focuses on the direction-of-departure (DOD) and direction-of-arrival (DOA) problem in bistatic MIMO radar with unknown gain-phase errors (GPE). A novel parallel factor (PARAFAC) estimator is proposed. The factor matrices containing DOD and DOA are firstly obtained via PARAFAC decomposition. One DOD-DOA pair estimation is then accomplished from the spectrum searching. Thereafter, the remainder DOD and DOA are achieved by the least squares technique with the previous estimated angle pair. The proposed estimator is analyzed in detail. It only requires one instrumental Tx/Rx sensor, and it outperforms the state-of-the-art algorithms. Numerical simulations verify the theoretical advantages.

scholarly journals Beamspace Unitary ESPRIT Algorithm for Angle Estimation in Bistatic MIMO Radar

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Dang Xiaofang ◽  
Chen Baixiao ◽  
Yang Minglei ◽  
Zheng Guimei
Keyword(s):  
Multiple Input Multiple Output ◽  
Low Complexity ◽  
Mimo Radar ◽  
Element Space ◽  
Bistatic Mimo Radar ◽  
Direction Of Departure ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Joint Direction ◽  
Esprit Algorithm

The beamspace unitary ESPRIT (B-UESPRIT) algorithm for estimating the joint direction of arrival (DOA) and the direction of departure (DOD) in bistatic multiple-input multiple-output (MIMO) radar is proposed. The conjugate centrosymmetrized DFT matrix is utilized to retain the rotational invariance structure in the beamspace transformation for both the receiving array and the transmitting array. Then the real-valued unitary ESPRIT algorithm is used to estimate DODs and DOAs which have been paired automatically. The proposed algorithm does not require peak searching, presents low complexity, and provides a significant better performance compared to some existing methods, such as the element-space ESPRIT (E-ESPRIT) algorithm and the beamspace ESPRIT (B-ESPRIT) algorithm for bistatic MIMO radar. Simulation results are conducted to show these conclusions.

Conjugate ESPRIT for MIMO Radar without Using Non-Circular Signals

2014 ◽  
Vol 513-517 ◽  
pp. 3850-3854
Author(s):  
Jian Feng Li ◽  
Wei Yang Chen ◽  
Xiao Fei Zhang
Keyword(s):  
Data Model ◽  
Multiple Input Multiple Output ◽  
Mimo Radar ◽  
Rotational Invariance ◽  
Joint Estimation ◽  
Signal Parameters ◽  
Direction Of Departure ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Virtual Array

Without using non-circular signals, conjugate estimation of signal parameters via rotational invariance technique (ESPRIT) for joint estimation of direction of departure (DOD) and direction of arrival (DOA) in bistatic multiple-input multiple-output (MIMO) radar is proposed. The characteristics of the Vandermonde-like matrix are employed to expand the virtual array of MIMO radar. Then the rotational invariance in the signal subspace is exploited to get the automatically paired estimations of angles. The proposed algorithm works with the same data model as that of ESPRIT, and has better angle estimation performance and can detect more targets than ESPRIT. Simulation results verify the usefulness of our approach.

scholarly journals Direction Finding for Bistatic MIMO Radar with Uniform Circular Array

2013 ◽  
Vol 2013 ◽  
pp. 1-6 ◽  
Author(s):  
Cao Yunhe ◽  
Zhang Zijing ◽  
Wang Shenghua ◽  
Dai Fengzhou
Keyword(s):  
Multiple Input Multiple Output ◽  
Mimo Radar ◽  
Search Method ◽  
Circular Array ◽  
Angle Estimation ◽  
Steering Vector ◽  
Direction Of Departure ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Polynomial Rooting

A method of direction of arrival (DOA) and direction of departure (DOD) angle estimation based on polynomial rooting for bistatic multiple-input multiple-output (MIMO) radar with uniform circular array (UCA) configuration is proposed in this paper. The steering vector of the UCA is firstly transformed into a steering vector with a Vandermonde structure by using the Jacobi-Anger expansion. Then the null-spectrum function of the MIMO radar can be written as an expression in which the transmit and receive steering vectors are decoupled. Finally, a two-step polynomial rooting is used to estimate DOA and DOD of targets instead of two-dimensional multiple signal classification (MUSIC) search method for bistatic UCA MIMO radar. The angle estimation performance of the proposed method is similar to that of the MUSIC spectral search method, but the computation burden of the proposed polynomial rooting algorithm is much lower than that of the conventional MUSIC method. The simulation results of the proposed algorithm are presented and the performances are investigated and analyzed.

Parameter Estimation and Cramer-Rao Bound in Wideband Bistatic MIMO Radar System

2015 ◽  
Vol 713-715 ◽  
pp. 651-655 ◽  
Author(s):  
Li Li
Keyword(s):  
Parameter Estimation ◽  
Fractional Fourier Transform ◽  
Multiple Input Multiple Output ◽  
Mimo Radar ◽  
Radar System ◽  
Novel Approach ◽  
Direction Of Departure ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Cramer Rao Bound

The problem of target localization and parameter estimation in wideband bistatic Multiple-Input Multiple-Output (MIMO) radar system is considered. In this paper, we use a novel approach to estimate Doppler stretch and time delay in fractional Fourier transform (FRFT) domain. We also develop two sub-array models to accurately estimate the direction-of-departure (DOD) and the direction-of-arrival (DOA). Furthermore, the Cramér-Rao bound for target parameter estimation is derived and computed in closed form. Parameter estimation performances are evaluated and studied theoretically and via simulations

scholarly journals DOA Estimation of a Novel Generalized Nested MIMO Radar with High Degrees of Freedom and Hole-Free Difference Coarray

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Yule Zhang ◽  
Guoping Hu ◽  
Hao Zhou ◽  
Mingming Zhu ◽  
Fei Zhang
Keyword(s):  
Degrees Of Freedom ◽  
Multiple Input Multiple Output ◽  
Doa Estimation ◽  
Mimo Radar ◽  
Music Algorithm ◽  
Array Configuration ◽  
Matrix Reconstruction ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Array Aperture

A novel generalized nested multiple-input multiple-output (MIMO) radar for direction of arrival (DOA) estimation is proposed in this paper. The proposed structure utilizes the extended two-level nested array (ENA) as transmitter and receiver and adjusts the interelement spacing of the receiver with an expanding factor. By optimizing the array element configuration, we can obtain the best number of elements of the transmitter and receiver and the attainable degrees of freedom (DOF). Compared with the existing nested MIMO radar, the proposed MIMO array configuration not only has closed-form expressions for sensors’ positions and the number of maximum DOF, but also significantly improves the array aperture. It is verified that the sum-difference coarray (SDCA) of the proposed nested MIMO radar can get higher DOF without holes. MUSIC algorithm based on Toeplitz matrix reconstruction is employed to prove the rationality and superiority of the proposed MIMO structure.

scholarly journals Position Estimation of Automatic-Guided Vehicle Based on MIMO Antenna Array

Electronics ◽  
2018 ◽  
Vol 7 (9) ◽  
pp. 193 ◽  
Author(s):  
Zhimin Chen ◽  
Xinyi He ◽  
Zhenxin Cao ◽  
Yi Jin ◽  
Jingchao Li
Keyword(s):  
Multiple Input Multiple Output ◽  
Mimo Radar ◽  
Position Estimation ◽  
Radar System ◽  
Joint Estimation ◽  
Mimo Antenna ◽  
Direction Of Departure ◽  
Multiple Input ◽  
Automatic Guided Vehicle ◽  
Input Multiple Output

The existing positioning methods for the automatic guided vehicle (AGV) in the port can not achieve high location precision, Therefore, a novel multiple input multiple output (MIMO) antenna radar positioning scheme is proposed in this paper. The positioning problem for AGV is considered, and the joint estimation problem for direction of departure (DoD) and direction of arrival (DoA) is addressed in the multiple-input multiple-output (MIMO) radar system. With the radar detect the transponder and estimate the DoA/DoD, the relative location between the transponder and the AGV can be obtained. The corresponding Cramér–Rao lower bounds (CRLBs) for the target parameters are also derived theoretically. Finally, we compare the positioning accuracy of the traditional global position system (GPS) with the proposed MIMO radar system. Simulation results show that the proposed method can achieve better performance than the traditional GPS.

scholarly journals A Barrage Jamming Strategy Based on CRB Maximization against Distributed MIMO Radar

Sensors ◽  
2019 ◽  
Vol 19 (11) ◽  
pp. 2453 ◽  
Author(s):  
Guangyong Zheng ◽  
Siqi Na ◽  
Tianyao Huang ◽  
Lulu Wang
Keyword(s):  
Particle Swarm Optimization ◽  
Multiple Input Multiple Output ◽  
Mimo Radar ◽  
Parameters Estimation ◽  
Swarm Optimization ◽  
Counter Measures ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Simulation Results ◽  
Cramer Rao Bound

Distributed multiple input multiple output (MIMO) radar has attracted much attention for its improved detection and estimation performance as well as enhanced electronic counter-counter measures (ECCM) ability. To protect the target from being detected and tracked by such radar, we consider a barrage jamming strategy towards a distributed MIMO. We first derive the Cramer–Rao bound (CRB) of target parameters estimation using a distributed MIMO under barrage jamming environments. We then set maximizing the CRB as the criterion for jamming resource allocation, aiming at degrading the accuracy of target parameters estimation. Due to the non-convexity of the CRB maximizing problem, particle swarm optimization is used to solve the problem. Simulation results demonstrate the advantages of the proposed strategy over traditional jamming methods.

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