检索结果-内蒙古大学图书馆

Resolving Range Ambiguity via multiple-input multiple-output radar With Element-Pulse Coding

IEEE TRANSACTIONS ON SIGNAL PROCESSING 2020年 68卷 2770-2783页

作者： Xu, Jingwei Zhang, Yuhong Liao, Guisheng So, Hing Cheung Xidian Univ Natl Key Lab Radar Signal Proc Xian 710071 Peoples R China City Univ Hong Kong Dept Elect Engn Hong Kong Peoples R China Xidian Univ Sch Elect Engn Xian 710071 Peoples R China

In this paper, we propose a novel radar framework, referred to as multiple-input multiple-output (MIMO) radar with element-pulse coding (EPC). The EPC employs Fourier basis in joint transmit elements and pulses, which has the advantages of simplicity and convenience for practical realization. It is shown that the EPC-MIMO radar is advantageous in discriminating different pulses and resolving range ambiguity. The discrimination of different pulses is achieved in the transmit spatial frequency domain, and the identifiability of range ambiguity increases with the transmit element number of the radar. Moreover, coherent processing in Doppler domain can be performed after decoding. The coding and decoding procedures are closely related though they are performed in transmitter and receiver, respectively. As the EPC-MIMO radar is capable of resolving range ambiguity, an enhanced parameter estimation approach is developed to obtain the angle and range region number estimates of target. The parameter estimation performance is assessed by the Cramer-Rao bound, which reveals useful and interesting findings. Simulation examples are provided to verify the signal properties in EPC-MIMO radar and to demonstrate its superiority in resolving range ambiguity over existing systems.

关键词： multiple-input multiple-output radar element-pulse coding range ambiguity resolution parameter estimation Cramer-Rao bound

来源：评论

学校读者我要写书评

暂无评论

Design of spectrally compatible waveform with constant modulus for colocated multiple-input multiple-output radar

引用

IET radar SONAR AND NAVIGATION 2019年第8期13卷 1373-1388页

作者： Wang, Xinhai Zhang, Gong Zhang, Yu Wang, Qixia Leung, Henry Nanjing Univ Aeronaut & Astronaut Coll Elect & Informat Engn 29 Jiangjun Ave Nanjing 211100 Jiangsu Peoples R China Minist Educ Key Lab Radar Imaging & Microwave Photon 29 Jiangjun Ave Nanjing 211100 Jiangsu Peoples R China Univ Calgary Dept Elect & Comp Engn Calgary AB Canada

This study investigates the problem of designing unimodular waveform with spectral compatibility for multiple-input multiple-output radar in the presence of multiple targets and the signal-dependent interferences. A new approach is proposed to optimise the spectrally compatible radar waveform subject to not only the constant modulus constraint and the similarity constraint but also the signal-to-interference-plus-noise ratio (SINR) requirements for targets, aiming at suppressing the radar energy in some space-frequency areas occupied by other cooperative communication systems. However, the formulated optimisation problem is NP-hard because of the existence of the non-convex constraints. Based on the dual ascent framework, the authors develop an iterative algorithm to solve this challenging problem. The receive filter is obtained at the beginning of each iteration with the off-the-shelf technique and an innovative method termed phase-only dual ascent method is proposed to get the desired waveform. Additionally, they analyse the performance of the waveforms designed under the global SINR constraint and the local SINR constraint, respectively. Moreover, the convergence of the proposed algorithm is discussed concretely. Finally, the numerical simulations are provided to show the validity of the proposed approach.

关键词： radar signal processing MIMO radar iterative methods concave programming radar interference multiple-input multiple-output radar unimodular waveform spectral compatibility signal-dependent interferences constant modulus constraint signal-to-interference-plus-noise ratio requirements radar energy formulated optimisation problem desired waveform global SINR constraint local SINR constraint spectrally compatible radar waveform cooperative communication systems colocated MIMO radar

来源：评论

学校读者我要写书评

暂无评论

Theoretical analysis and experimental verification of wideband multiple-input multiple-output imaging radar

引用

JOURNAL OF ENGINEERING-JOE 2019年第19期2019卷 5896-5900页

作者： Wang, Jingyang Hu, Cheng Tian, Weiming Wang, Rui Beijing Inst Technol Sch Informat & Elect Radar Res Lab Beijing Peoples R China Beijing Inst Technol Minist Educ Key Lab Elect & Informat Technol Satellite Nav Beijing 100081 Peoples R China

multiple-input multiple-output (MIMO) radar is a novel radar system which can achieve more individual observation echoes than the number of the actual antennas by transmitting orthogonal waveforms. At present, pattern theory is usually utilised to evaluate the azimuth imaging indicator of the MIMO imaging radar system. Although it cannot describe the two-dimensional performance, it is quite effective to analyse the azimuth resolution of far-field targets. However, the pattern based on the far-field condition becomes invalid for targets in the near-field area, thus it cannot explain the appearance of near-field azimuth grating lobes. In this article, spatial spectrums and generalised ambiguity functions (GAFs) of near-field targets are calculated. By describing the near-field GAF (NGAF) approximately, the relationship between the distortions of NGAF and the spatial spectrum is studied qualitatively, which can explain the appearance of azimuth near-field grating lobes. In addition, the calibration method of amplitude and phase errors by an isolated corner reflector is presented in this article. Finally, a simulation and an experiment are carried out to verify the conclusions.

关键词： MIMO radar radar antennas calibration radar imaging MIMO communication radar resolution radar signal processing experimental verification multiple-output imaging radar multiple-input multiple-output radar individual observation echoes actual antennas pattern theory azimuth imaging indicator MIMO imaging radar system azimuth resolution far-field targets far-field condition near-field area near-field azimuth spatial spectrum near-field targets near-field GAF azimuth near-field

来源：评论

学校读者我要写书评

暂无评论

Robust and fast beamforming with magnitude response constraints for multiple-input multiple-output radar

引用

IET radar SONAR AND NAVIGATION 2016年第3期10卷 610-616页

作者： Yu, HongBo Feng, DaZheng Nie, WeiKe Xidian Univ Natl Lab Radar Signal Proc Xian 710071 Peoples R China NW Univ Xian Sch Informat & Technol Xian 710127 Peoples R China

In this study, a new robust and fast beamformer is developed for multiple-input multiple-output radar to improve the robustness against steering vector (SV) mismatches. A convex robust model with magnitude response constraints (MRC) is established by using the conjugate symmetry characteristic of the transmitted-received SV. To reduce the computational complexity and the number of samples required, the full-dimensional weight vector (WV) is expressed as the Kronecker product of the transmitted and received array WVs. Thus, the convex problem is converted into a bi-quadratic cost function and it is solved by combining the bi-iterative algorithm and convex quadratic program. The proposed beamformer can flexibly control the beamwidth of the robust region and achieve high output signal-to-interference-plus-noise ratio. Moreover, the proposed method has lower computational complexity and faster sample convergence rate as compared with the traditional MRC-iterative second-order cone programming and MRC-semi-definite programming beamformers. Finally, numerical simulations are provided to demonstrate the effectiveness and robustness of the proposed beamformer.

关键词： array signal processing MIMO radar iterative methods quadratic programming convex programming robust fast beamforming magnitude response constraints multiple-input multiple-output radar steering vector mismatches MRC full-dimensional weight vector WV Kronecker product bi-quadratic cost function bi-iterative algorithm convex quadratic program numerical simulations

来源：评论

学校读者我要写书评

暂无评论

Robust design of multiple-input multiple-output radar waveform covariance matrix in the presence of clutter

引用

JOURNAL OF APPLIED REMOTE SENSING 2016年第1期10卷 035005-1-035005-15页

作者： Guo, Rongyan Wang, Hongyan Zhoukou Normal Univ Sch Phys & Elect Engn Zhoukou 466001 Henan Province Peoples R China Dalian Univ Coll Informat Engn Dalian 116622 Liaoning Peoples R China

In this work, the issue of robust waveform optimization is addressed in the presence of clutter to improve the worst-case estimation accuracy for collocated multiple-input multiple-output (MIMO) radar. Robust design is necessary due to the fact that waveform design may be sensitive to uncertainties in the initial parameter estimates. Following the min-max approach, the robust waveform covariance matrix design is formulated here on the basis of Cramer-Rao Bound to ease this sensitivity systematically for improving the worst-case accuracy. To tackle the resultant complicated and nonlinear problem, a new diagonal loading (DL)-based iterative approach is developed, in which the inner optimization problem can first be decomposed to some independent subproblems by using the Hadamard's inequality, and then these subproblems can be reformulated into convex issues by using DL method, as well as the outer optimization problem can also be relaxed to a convex issue by translating the nonlinear function into a linear one, and, hence, both of them can be solved very effectively. An optimal solution to the original problem can be obtained via the least-squares fitting of the solution acquired by the iterative approach. Numerical simulations show the efficiency of the proposed method. (C) The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License.

关键词： robust waveform covariance matrix design multiple-input multiple-output radar diagonal loading parameter estimation

来源：评论

学校读者我要写书评

暂无评论

Adaptive Bayesian detection for multiple-input multiple-output radar in compound-Gaussian clutter with random texture

引用

IET radar SONAR AND NAVIGATION 2016年第4期10卷 689-698页

作者： Kong, Lingjiang Li, Na Cui, Guolong Yang, Haining Liu, Qing Huo Univ Elect Sci & Technol China Dept Signal & Informat Proc Chengdu 611731 Peoples R China Duke Univ Dept Elect & Comp Engn Durham NC 27708 USA

In this study, the authors consider the adaptive detection with multiple-input multiple-output radar in compound-Gaussian clutter. The covariance matrices of the primary and the secondary data share a common structure, but different power levels (textures). A Bayesian framework is exploited where both the textures and the structure are assumed to be random. Precisely, the textures follow Gamma distribution or inverse Gamma distribution and the structure is drawn from an inverse complex Wishart distribution. In this framework, two generalised likelihood ratio tests are derived. Finally, they evaluate the capabilities of the proposed detectors against compound-Gaussian clutter as well as their superiority with respect to some existing techniques.

关键词： MIMO radar radar detection Bayes methods radar clutter gamma distribution multiple-input multiple-output radar compound-Gaussian clutter random texture adaptive Bayesian detection Gamma distribution inverse Gamma distribution inverse complex Wishart distribution generalised likelihood ratio tests

来源：评论

学校读者我要写书评

暂无评论

Direction-of-arrival estimation for co-located multiple-input multiple-output radar using structural sparsity Bayesian learning

引用

Chinese Physics B 2015年第11期24卷 70-76页

作者：文方青张弓贲德 College of Electronic and Information Engineering Nanjing University of Aeronautics and Astronautics Key Laboratory of Radar Imaging and Microwave Photonics Ministry of Education Nanjing Research Institute of Electronics Technology

This paper addresses the direction of arrival （DOA） estimation problem for the co-located multiple-input multiple- output （MIMO） radar with random arrays. The spatially distributed sparsity of the targets in the background makes com- pressive sensing （CS） desirable for DOA estimation. A spatial CS framework is presented, which links the DOA estimation problem to support recovery from a known over-complete dictionary. A modified statistical model is developed to ac- curately represent the intra-block correlation of the received signal. A structural sparsity Bayesian learning algorithm is proposed for the sparse recovery problem. The proposed algorithm, which exploits intra-signal correlation, is capable being applied to limited data support and low signal-to-noise ratio （SNR） scene. Furthermore, the proposed algorithm has less computation load compared to the classical Bayesian algorithm. Simulation results show that the proposed algorithm has a more accurate DOA estimation than the traditional multiple signal classification （MUSIC） algorithm and other CS recovery algorithms.

关键词： multiple-input multiple-output radar random arrays direction of arrival estimation sparseBayesian learning

来源：评论

学校读者我要写书评

暂无评论

Performance bounds of direction finding and its applications for multiple-input multiple-output radar

引用

IET radar SONAR AND NAVIGATION 2014年第3期8卷 251-263页

作者： Chen, Haowen Li, Xiang Wang, Hongqiang Zhuang, Zhaowen Natl Univ Def Technol Coll Elect Sci & Engn Changsha 410073 Hunan Peoples R China

In this study, the authors derive an explicit expression for Cramer-Rao lower bound (CRLB) on direction parameters with the antenna locations of a single point target in the far-field scenario for multiple-input multiple-output (MIMO) radar, firstly. Since there are two unknown nuisance parameters (target radar cross section and interference-plus-noise strength), the authors use the concentrated CRLB to simplify the analytical computation. Then, the authors derive two sets of necessary and sufficient geometrical constraints for direction estimation with both bistatic and monostatic MIMO radars. Then, the authors consider the bounds on the asymptotic normalised mean-square angular error (ANMSAE), which are useful measures in three-dimensional bearing estimation problems. The authors derive the expressions for ANMSAE in both bistatic and monostatic MIMO radars, and discuss them in terms of the antenna locations. The authors then show that the uncoupled geometrical conditions are also sufficient to ensure that ANMSAE is independent of azimuth. Finally, the authors extend those conditions to obtain two sets of geometry constraints for bistatic and monostatic MIMO radars, respectively, such as some kinds of symmetry on the geometry, that ensure the optimal performance is isotropic, that is, the ANMSAE bounds are independent of all direction parameters. In numerical examples section, the authors give several representative antenna geometries to illustrate the derived antenna geometry strategy.

关键词： antenna arrays mean square error methods radio direction-finding MIMO radar direction finding multiple-input multiple-output radar Cramer-Rao lower bound CRLB antenna locations far-field scenario unknown nuisance parameters geometrical constraints bistatic MIMO radars monostatic MIMO radars asymptotic normalised mean-square angular error three-dimensional bearing estimation problems ANMSAE bounds derived antenna geometry strategy representative antenna geometries

来源：评论

学校读者我要写书评

暂无评论

Distributed Phased multiple-input multiple-output radars for Early Warning: Observation Area Generation

引用

REMOTE SENSING 2024年第16期16卷 3052页

作者： Luo, Dengsanlang Wen, Gongjian Natl Univ Def Technol Coll Elect Sci Changsha 410073 Peoples R China

This paper introduces a resource management approach for distributed multiple-input multiple-output (MIMO) radar systems equipped with phased array antennas. The approach focuses and adjusts narrow beams from all transmit and receive nodes to generate a regularly shaped observation area for reliable detection. Based on this, a structured early warning framework can be built by evenly arranging sufficient observation areas to cover the surveillance region and periodically scanning these areas for continuous monitoring. Observation area generation, a core technique for this framework, involves the joint optimization of beamforming weights for both transmit and receive nodes, as well as the beam dwell time. Our optimization strategy is designed to achieve two key objectives: minimizing beam dwell time to ensure rapid alerts for defense systems, and minimizing node transmit power to extend operational time while reducing the risk of intercept. To address the problem of observation area generation, we propose a two-stage method. The first stage uses the signal-to-clutter-plus-noise ratio (SCNR) as a new criterion to determine the transmit and receive beamforming weights. The second stage employs a power factor as an additional variable to scale the transmit beamforming weights under various beam dwell times, constructing a Pareto solution set for the problem. Numerical simulations validate the effectiveness of our method, demonstrating improved detection capabilities compared to monostatic phased array radar systems.

关键词： multiple-input multiple-output radar beamforming detection observation area phased array antenna resource management

来源：评论

学校读者我要写书评

暂无评论

Robust minimum variance multiple-input multiple-output radar beamformer

引用

IET SIGNAL PROCESSING 2013年第9期7卷 854-862页

作者： Zhang, Wei Wang, Ju Wu, Siliang Beijing Inst Technol Dept Elect & Informat Beijing 100081 Peoples R China

A robust minimum variance (MV) beamforming approach is proposed for improving the robustness of multiple-input multiple-output (MIMO) radar against the mismatches of the steering vector and the finite sample effects. In contrast to existing robust MV beamformers (RMVBs), the proposed RMVB utilises a specific structured model of virtual steering vector (also named transmit-receive steering vector) of MIMO radar rather than the commonly used unstructured model in phased-array radar. The basic idea of the proposed RMVB is to estimate the desired transmit and receive steering vectors under two quadratic constraints. To solve this problem, an iterative algorithm is developed. Simulations are provided to confirm the effectiveness of the proposed method.

关键词： array signal processing iterative methods radar signal processing MIMO radar robust minimum variance MIMO radar beamformer robust MV beamforming approach multiple-input multiple-output radar finite sample effects virtual steering vector transmit-receive steering vector estimation phased-array radar quadratic constraint iterative algorithm

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：