scholarly journals Spatial Differencing Reconstruction Based Low-Angle DOA Estimation with MIMO Radar

2018 ◽  
Vol 36 (1) ◽  
pp. 182-188
Author(s):  
Qin Zhang ◽  
Linrang Zhang ◽  
Junpeng Shi ◽  
Yannian Zhou ◽  
Yaning Liu
Keyword(s):  
Multiple Input Multiple Output ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Spatial Diversity ◽  
Mimo Radar ◽  
Estimation Accuracy ◽  
Signal Model ◽  
Estimation Performance ◽  
Multiple Input ◽  
Input Multiple Output

Due to the multipath effect, the direction of arrival (DOA) estimation performance for low-angle targets decreases greatly. To overcome this problem, this paper proposes a spatial differencing reconstruction based DOA estimation algorithm by using the received signal model of multiple input multiple output (MIMO) radar. Combining with the spatial diversity of MIMO radar, the proposed method can first use the multipath echo power to select the best signal. Then, a spatial differencing based iterative scheme is developed to reduce the effect of additive noise, resulting in a better estimation performance for low-angle targets. Simulation results show that the proposed method has better advantages in suppressing noise and improving estimation accuracy.

scholarly journals DOA Estimation for Multiple Targets in MIMO Radar with Nonorthogonal Signals

2018 ◽  
Vol 2018 ◽  
pp. 1-7 ◽  
Author(s):  
Zhenxin Cao ◽  
Peng Chen ◽  
Zhimin Chen ◽  
Yi Jin
Keyword(s):  
Correlation Matrix ◽  
Cross Correlation ◽  
Multiple Input Multiple Output ◽  
Doa Estimation ◽  
Mimo Radar ◽  
Signal Classification ◽  
Multiple Signal Classification ◽  
Estimation Performance ◽  
Multiple Input ◽  
Input Multiple Output

This paper addresses the direction of arrival (DOA) estimation problem in the colocated multiple-input multiple-output (MIMO) radar with nonorthogonal signals. The maximum number of targets that can be estimated is theoretically derived as rankRsN, where N denotes the number of receiving antennas and Rs is the cross-correlation matrix of the transmitted signals. Therefore, with the rank-deficient cross-correlation matrix, the maximum number that can be estimated is less than the radar with orthogonal signals. Then, a multiple signal classification- (MUSIC-) based algorithm is given for the nonorthogonal signals. Furthermore, the DOA estimation performance is also theoretically analyzed by the Carmér-Rao lower bound. Simulation results show that the nonorthogonality degrades the DOA estimation performance only in the scenario with the rank-deficient cross-correlation matrix.

scholarly journals A MIMO Radar-Based DOA Estimation Structure Using Compressive Measurements

Sensors ◽  
2019 ◽  
Vol 19 (21) ◽  
pp. 4706 ◽  
Author(s):  
Tao Chen ◽  
Jian Yang ◽  
Muran Guo
Keyword(s):  
Antenna Arrays ◽  
Multiple Input Multiple Output ◽  
Information Criterion ◽  
Doa Estimation ◽  
Mimo Radar ◽  
Optimization Approach ◽  
Measurement Matrix ◽  
Estimation Performance ◽  
Input Multiple Output ◽  
Cramer Rao Bound

In this paper, we propose a novel direction-of-arrival (DOA) estimation structure based on multiple-input multiple-output (MIMO) radar with colocated antennas, referred to as compressive measurement-based MIMO (CM-MIMO) radar, where the compressive sensing (CS) is employed to reduce the number of channels. Therefore, the system complexity and the computational burden are effectively reduced. It is noted that CS is used after the matched filters and that a measurement matrix with less rows than columns is multiplied with the received signals. As a result, the configurations of the transmit and receive antenna arrays are not affected by the CS and can be determined according to the practical requirements. To study the estimation performance, the Cramér–Rao bound (CRB) with respect to the DOAs of the proposed CM-MIMO radar is analyzed in this paper. The derived CRB expression is also suitable for the conventional MIMO radar by setting the measurement matrix as an identity matrix. Moreover, the CRB expression can work in the under-determined case, since the sum-difference coarray structure is considered. However, the random measurement matrix leads to high information loss, thus compromising the estimation performance. To overcome this problem, we consider that the a prior probability distribution of the DOAs associated with the targets can be obtained in many scenarios and an optimization approach for the measurement matrix is proposed in this paper, where the maximum mutual information criterion is adopted. The superiority of the proposed structure is validated by numerical simulations.

Oil-Spills Detection in MIMO-SAR Radar Images by High Order Statistics

2013 ◽  
Vol 443 ◽  
pp. 649-652
Author(s):  
Yan Ling Luo
Keyword(s):  
Oil Spills ◽  
Multiple Input Multiple Output ◽  
Mimo Radar ◽  
Radar Signal ◽  
Future Research ◽  
Signal Model ◽  
Radar Images ◽  
Multiple Input ◽  
Input Multiple Output ◽  
High Order Statistics

MIMO radar (Multiple input multiple output radar) is a hot topic which gets lots of attention from researchers all around the world recently. It can achieve better detection performance than conventional phased radar. In this paper, the MIMO radar signal model is studied, and then the concept of MIMO radar is applied into SAR. The technique is employed to detect the oil spill in sea. At last, some conclusion is drawn. And some item for future research in presented also.

Multi-Target Direction Measurement of Bistatic MIMO Radar

2014 ◽  
Vol 556-562 ◽  
pp. 2797-2801
Author(s):  
Jing Fang Wang
Keyword(s):  
Multiple Input Multiple Output ◽  
Mimo Radar ◽  
Radar Signal ◽  
Great Success ◽  
Two Dimensional ◽  
Signal Model ◽  
Bistatic Mimo Radar ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Mimo Technology

Multiple-input multiple output (MIMO) radar has been widespread concern in the domestic and foreign researchers. Bistatic radar draws on the great success of MIMO technology in the communications field, and it has many advantages over conventional radar. The direction angles estimations of bistatic MIMO radar are researched. To contrast traditional radar DOA estimates, the direction vector of the bistatic MIMO radar is the Knonecker plot of the emission vector and reception vector, that two-dimensional direction angles is estimated. To solve this problem, the principle of bistatic MIMO radar signal model is in-depthly researched.By proposing Capon dimensionality reduction method, the two-dimensional directions of the dual-based MIMO radar are estimated, and computer simulation is to verify the effectiveness of the method.

scholarly journals Root-MUSIC Based Angle Estimation for MIMO Radar with Unknown Mutual Coupling

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Jianfeng Li ◽  
Xiaofei Zhang ◽  
Weiyang Chen
Keyword(s):  
Mutual Coupling ◽  
Estimation Error ◽  
Multiple Input Multiple Output ◽  
Doa Estimation ◽  
Mimo Radar ◽  
Angle Estimation ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Lower Complexity ◽  
Toeplitz Structure

Direction of arrival (DOA) estimation problem for multiple-input multiple-output (MIMO) radar with unknown mutual coupling is studied, and an algorithm for the DOA estimation based on root multiple signal classification (MUSIC) is proposed. Firstly, according to the Toeplitz structure of the mutual coupling matrix, output data of some specified sensors are selected to eliminate the influence of the mutual coupling. Then the reduced-dimension transformation is applied to make the computation burden lower as well as obtain a Vandermonde structure of the direction matrix. Finally, Root-MUSIC can be adopted for the angle estimation. The angle estimation performance of the proposed algorithm is better than that of estimation of signal parameters via rotational invariance techniques (ESPRIT)-like algorithm and MUSIC-like algorithm. Furthermore, the proposed algorithm has lower complexity than them. The simulation results verify the effectiveness of the algorithm, and the theoretical estimation error of the algorithm is also derived.

Cramer-Rao Bound for Parameter Estimation in Bistatic MIMO Radar

2014 ◽  
Vol 513-517 ◽  
pp. 3385-3388
Author(s):  
Li Li
Keyword(s):  
Parameter Estimation ◽  
Target Location ◽  
Multiple Input Multiple Output ◽  
Mimo Radar ◽  
Signal Model ◽  
Wideband Signal ◽  
Wideband Signals ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Cramer Rao Bound

The problem of Cramér-Rao bound for parameter estimation in wideband bistatic Multiple-Input Multiple-Output (MIMO) radar system is considered. In many applications, it is not appropriate to approximate the wideband signal by the narrowband model. In this paper, we propose a new wideband signal model to accurately estimate parameter for wideband signals from a moving target. The Cramér-Rao bound for target parameter estimation is derived and computed in closed form which shows that the optimal performance is achieved. Target location and parameter estimation performances are evaluated and studied theoretically and via simulations.

scholarly journals Computationally Efficient Unitary ESPRIT Algorithm in Bistatic MIMO Radar

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Baobao Liu ◽  
Tao Xue ◽  
Cong Xu ◽  
Yongjun Liu
Keyword(s):  
Multiple Input Multiple Output ◽  
Low Complexity ◽  
Mimo Radar ◽  
Computational Effort ◽  
Estimation Accuracy ◽  
Computationally Efficient ◽  
Angle Estimation ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Esprit Algorithm

A low complexity unitary estimating signal parameter via rotational invariance techniques (ESPRIT) algorithm is presented for angle estimation in bistatic multiple-input-multiple-output (MIMO) radar. The devised algorithm only requires calculating two submatrices covariance matrix, which reduces the computation cost in comparison with subspace methods. Moreover, the signal subspace can be efficiently acquired by exploiting the NystrÖm method, which only needs O M N K 2 flops. Thus, the presented algorithm has an essentially diminished computational effort, especially useful when K ≪ M N , while it can achieve efficient angle estimation accuracy as well as the existing algorithms. Several theoretical analysis and simulation results are provided to demonstrate the usefulness of the proposed scheme.

A Simulation System for MIMO Radar

2010 ◽  
Vol 121-122 ◽  
pp. 633-639
Author(s):  
Jian Kui Zeng ◽  
Zi Ming Dong
Keyword(s):  
Signal Processing ◽  
Multiple Input Multiple Output ◽  
Mimo Radar ◽  
Simulation System ◽  
Radar Signal ◽  
Signal Model ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Conventional Counterpart ◽  
Radar Technique

MIMO radar (Multiple input multiple output radar) is a novel radar technique developed recently. It can achieve better detection performance than conventional phased radar. In this paper, the MIMO radar signal model is studied, and then the signal processing flow of the MIMO radar is researched. At last, a simulation platform with the Matlab is established to testify the advantage of MIMO radar over its conventional counterpart.

Cramer-Rao Bound for Parameter Estimation in Narrowband Bistatic MIMO Radar

2014 ◽  
Vol 556-562 ◽  
pp. 5034-5037 ◽  
Author(s):  
Li Li
Keyword(s):  
Parameter Estimation ◽  
Target Location ◽  
Multiple Input Multiple Output ◽  
Mimo Radar ◽  
Signal Model ◽  
Narrowband Signal ◽  
Multiple Input ◽  
Estimate Parameter ◽  
Input Multiple Output ◽  
Cramer Rao Bound

The problem of Cramer-Rao bound for parameter estimation in norrowband bistatic Multiple-Input Multiple-Output (MIMO) radar system is considered. In this paper, we propose a new narrowband signal model to accurately estimate parameter from a moving target. The Cramer-Rao bound for target parameter estimation is derived and computed in closed form which shows that the optimal performance is achieved. Target location and parameter estimation performances are evaluated and studied theoretically and via simulations.

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