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 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.

Rudder/Fin Roll Stabilization of the USCG WMEC 901 Class Vessel

1999 ◽  
Vol 36 (03) ◽  
pp. 157-170
Author(s):  
Jerrold N. Sgobbo ◽  
Michael G. Parsons
Keyword(s):  
Degrees Of Freedom ◽  
Multiple Input Multiple Output ◽  
Cross Coupling ◽  
Degree Of Freedom ◽  
Rolling Motion ◽  
Rolling Moment ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Three Degree Of Freedom ◽  
The U.S

The U.S. Coast Guard's 270-ft Medium Endurance Cutter (WMEC) operates with an active fin stabilization system. This system was designed using a one-degree-of-freedom (1-DOF) model in the roll direction. The controller was designed separate from the heading autopilot. The effects of the rudders and their ability to produce a significant rolling moment were also neglected as well as the cross coupling of roll motions into other degrees of freedom. This paper studies the effects of the rudders on the rolling motion of the ship using a three-degree-of-freedom (3-DOF) model. A simple optimal heading autopilot is designed and combined with the existing fin roll controller to investigate the effects of the rudders on the roll motions of this class of vessel. A rudder roll controller and a multiple input-multiple output (MIMO) rudder/fin controller are designed as well. Significant roll reduction can be achieved using the MIMO rudder/fin controller.

scholarly journals DOA estimation based on sum–difference coarray with virtual array interpolation concept

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Yarong Ding ◽  
Shiwei Ren ◽  
Weijiang Wang ◽  
Chengbo Xue
Keyword(s):  
Numerical Simulation ◽  
Degrees Of Freedom ◽  
Doa Estimation ◽  
Superior Performance ◽  
Norm Minimization ◽  
Atomic Norm ◽  
Virtual Array ◽  
Simulation Results ◽  
The Difference ◽  
Coprime Array

AbstractThe sum–difference coarray is the union of difference coarray and the sum coarray, which is capable to obtain a higher number of degrees of freedom (DOF) than the difference coarray. However, this method fails to use all information provided by the coprime array because of the existence of holes. In this paper, we introduce the virtual array interpolation into the sum–difference coarray domain. After interpolating the virtual array, we estimate the DOA by reconstructing the covariance matrix to resolve an atomic norm minimization problem in a gridless way. The proposed method is gridless and can effectively utilize the DOF of a larger virtual array. Numerical simulation results verify the effectiveness and the superior performance of the proposed algorithm.

scholarly journals A novel method for joint- PAPR mitigation in OFDM-based massive MIMO downlink systems

2018 ◽  
Vol 7 (3) ◽  
pp. 1185 ◽  
Author(s):  
Padarti Vijaya Kumar ◽  
Venkateswara Rao Nandanavanam
Keyword(s):  
Massive Mimo ◽  
High Speed ◽  
Degrees Of Freedom ◽  
Multiple Input Multiple Output ◽  
Average Power ◽  
Data Communication ◽  
Multiple Input ◽  
Input Multiple Output ◽  
High Speed Data ◽  
Mimo Downlink

Massive MIMO has gained much attention with the increase in the high speed data communication. The problem of peak-to-average power ratio (PAPR) is considered, the detrimental aspects in OFDM based massive multiple-input multiple-output (MIMO) downlink systems. The previous works done in reduction of PAPR problem using convex optimization are computationally inefficient. We considered Bayesian approach to mitigate PAPR by utilizing the redundant degrees of freedom (DOF) of the transmit array, which effectively reduced the level of PAPR. The performance or numerical results indicate the applied algorithm achieved a good improvement over the existing techniques in terms of the PAPR reduction.  

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.

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