Minimum redundancy MIMO array synthesis with a hybrid method based on cyclic difference sets and ACO

2015 ◽  
Vol 9 (1) ◽  
pp. 35-43 ◽  
Author(s):  
Jian Dong ◽  
Ronghua Shi ◽  
Ying Guo
Keyword(s):  
Hybrid Method ◽  
Numerical Experiments ◽  
Multiple Input Multiple Output ◽  
Computational Cost ◽  
Difference Sets ◽  
Cyclic Difference Sets ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Virtual Array ◽  
Array Aperture

As a recently proposed concept, multiple-input multiple-output (MIMO) radars exhibit much higher spatial resolution than traditional transmitter based radars because of the synthesized virtual array. In this paper, the problem of minimum redundancy (MR)-MIMO array synthesis is addressed, which seeks to maximize the virtual array aperture of MIMO radars for a given number of transmitting and receiving elements. A hybrid method combining autocorrelation property of cyclic difference sets (CDSs) and global search characteristics of ant colony optimization (ACO) is proposed for a rapid and numerically-effective exploration of MR-MIMO array configurations. Numerical experiments validate the proposed method, showing improvements in convergence rate and computational cost with respect to bare ACO-based search as well as improvements in the generality and configuration variety with respect to the CDS-based method.

scholarly journals Design and Imaging of Ground-Based Multiple-Input Multiple-Output Synthetic Aperture Radar (MIMO SAR) with Non-Collinear Arrays

2017 ◽  
Author(s):  
Cheng Hu ◽  
Jingyang Wang ◽  
Weiming Tian ◽  
Tao Zeng ◽  
Rui Wang
Keyword(s):  
Coupling Effect ◽  
Near Field ◽  
Multiple Input Multiple Output ◽  
Far Field ◽  
Imaging Result ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Edge Points ◽  
Virtual Array ◽  
Field Edge

MIMO (multiple-input multiple-output) radar provides much more flexibility than the traditional radar for its ability to realize far more observation channels than the actual number of T/R (transmit and receive) elements. Designing the array of MIMO imaging radar, the commonly used virtual array theory generally assumes that all elements are placed on the same line. However, due to the physical size of the antennas and coupling effect between T/R elements, a certain height difference between T/R arrays is essential, resulting in the defocusing of edge points of the scene. On the other hand, the virtual array theory implies far-field approximation, leading to inevitable high grating lobes in the imaging result of near-field edge points of the scene observed by common MIMO array. To tackle these problems, this paper derives the relationship between target’s PSF (point spread function) and pattern of T/R arrays, by which the design criterion of near-field imaging MIMO array is presented. Firstly, the proper height between T/R arrays is designed to focus the near-field edge points well. Secondly, the far-field array is modified to suppress the grating lobes in the near-field area. Finally, the validity of the proposed methods is verified by simulations and an experiment.

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.

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 Joint Phased-MIMO and Nested-Array Beamforming for Increased Degrees-of-Freedom

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Chenglong Zhu ◽  
Hui Chen ◽  
Huaizong Shao
Keyword(s):  
Degrees Of Freedom ◽  
Phased Array ◽  
Multiple Input Multiple Output ◽  
Doa Estimation ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Virtual Array ◽  
The Difference ◽  
Array Beamforming ◽  
Error Simulation

Phased-multiple-input multiple-output (phased-MIMO) enjoys the advantages of MIMO virtual array and phased-array directional gain, but it gets the directional gain at a cost of reduced degrees-of-freedom (DOFs). To compensate the DOF loss, this paper proposes a joint phased-array and nested-array beamforming based on the difference coarray processing and spatial smoothing. The essence is to use a nested-array in the receiver and then fully exploit the second order statistic of the received data. In doing so, the array system offers more DOFs which means more sources can be resolved. The direction-of-arrival (DOA) estimation performance of the proposed method is evaluated by examining the root-mean-square error. Simulation results show the proposed method has significant superiorities to the existing phased-MIMO.

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 Optimizations for robust low sidelobe beamforming of bistatic multiple-input multiple-output virtual array

2014 ◽  
Vol 63 (18) ◽  
pp. 188401
Author(s):  
Huang Cong ◽  
Sun Da-Jun ◽  
Zhang Dian-Lun ◽  
Teng Ting-Ting
Keyword(s):  
Multiple Input Multiple Output ◽  
Low Sidelobe ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Virtual Array

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 Minimum Redundancy MIMO Array Synthesis by means of Cyclic Difference Sets

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Jian Dong ◽  
Ronghua Shi ◽  
Wentai Lei ◽  
Ying Guo
Keyword(s):  
Spatial Resolution ◽  
High Spatial Resolution ◽  
Difference Sets ◽  
Cyclic Difference Sets ◽  
Very High Spatial Resolution ◽  
Virtual Array ◽  
Key Features ◽  
Array Aperture ◽  
Antenna Array Synthesis ◽  
Very High

Antenna array synthesis is an important issue in MIMO radars. By judiciously designing antenna positions, one can create a very long virtual array steering vector with a small number of antennas and therefore achieve very high spatial resolution at a small cost. This paper presents a combinatorial methodology based on cyclic difference sets (CDSs) for minimum redundancy (MR) MIMO array synthesis which seeks to maximize the virtual array aperture for a given number of antennas. First, the key features of CDSs and the CDS-based MR-MIMO layouts are described. Then, the analytical expression of the maximum contiguous virtual array aperture is derived. Further, based on this expression, an enumerative shifting procedure is developed for identifying the optimal CDS-based MR-MIMO layout. Selected examples are analyzed to point out the computational effectiveness of the CDS-based MR-MIMO array synthesis.

scholarly journals Low Complexity Submatrix Divided MMSE Sparse-SQRD Detection for MIMO-OFDM with ESPAR Antenna Receiver

VLSI Design ◽  
2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Diego Javier Reinoso Chisaguano ◽  
Minoru Okada
Keyword(s):  
Orthogonal Frequency Division Multiplexing ◽  
Minimum Mean Square Error ◽  
Multiple Input Multiple Output ◽  
Computational Cost ◽  
Low Complexity ◽  
Detection Process ◽  
Large Size ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Mimo Ofdm

Multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) with an electronically steerable passive array radiator (ESPAR) antenna receiver can improve the bit error rate performance and obtains additional diversity gain without increasing the number of Radio Frequency (RF) front-end circuits. However, due to the large size of the channel matrix, the computational cost required for the detection process using Vertical-Bell Laboratories Layered Space-Time (V-BLAST) detection is too high to be implemented. Using the minimum mean square error sparse-sorted QR decomposition (MMSE sparse-SQRD) algorithm for the detection process the average computational cost can be considerably reduced but is still higher compared with a conventional MIMOOFDM system without ESPAR antenna receiver. In this paper, we propose to use a low complexity submatrix divided MMSE sparse-SQRD algorithm for the detection process of MIMOOFDM with ESPAR antenna receiver. The computational cost analysis and simulation results show that on average the proposed scheme can further reduce the computational cost and achieve a complexity comparable to the conventional MIMO-OFDM detection schemes.

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