scholarly journals BLIND JOINT DOA AND DOD ESTIMATION AND IDENTIFIABILITY RESULTS FOR MIMO RADAR WITH DIFFERENT TRANSMIT / RECEIVE ARRAY MANIFOLDS

2009 ◽  
Vol 18 ◽  
pp. 101-119 ◽  
Author(s):  
Xiaofei Zhang ◽  
Xin Gao ◽  
Gaopeng Feng ◽  
Dazhuan Xu
Keyword(s):  
Mimo Radar ◽  
Receive Array

scholarly journals Transmit and Receive Array Structure Design of Two-Dimensional hybrid Phased-MIMO Radar based on Nested Array

2018 ◽  
Vol 232 ◽  
pp. 02052
Author(s):  
Tianhao Cheng ◽  
Buhong Wang ◽  
Qiaoge Liu ◽  
Jiwei Tian
Keyword(s):  
Design Method ◽  
Doa Estimation ◽  
Mimo Radar ◽  
Structure Design ◽  
Estimation Accuracy ◽  
Two Dimensional ◽  
Simulation Experiments ◽  
Virtual Array ◽  
Array Structure ◽  
Receive Array

In order to reduce the loss of Degree of Freedom (DOF) brought by the transmit subarray splitting of two-dimensional hybrid phased-MIMO radar, this paper presents a design method of transmitting and receiving array based on nested array structure. Firstly, a two-dimensional hybrid phased-MIMO radar transmitting array based on one-dimensional nested array is presented. On this basis, the receiving end is set as a nested array, and finally a virtual array and difference coarray are formed to expand the number of virtual array elements. The expansion increases the DOF of arrays while preserving the advantages of hybrid phased-MIMO radars. Simulation experiments show that compared with the traditional and coprime hybrid phased-MIMO radar, the proposed method can effectively improve the array DOF and Direction-of-Arrival (DOA) estimation accuracy.

Transmit and Receive Array Gain-Phase Error Estimation in Bistatic MIMO Radar

2015 ◽  
Vol 14 ◽  
pp. 32-35 ◽  
Author(s):  
Jun Li ◽  
Ming Jin ◽  
Yu Zheng ◽  
Guisheng Liao ◽  
Li Lv
Keyword(s):  
Error Estimation ◽  
Phase Error ◽  
Mimo Radar ◽  
Bistatic Mimo Radar ◽  
Array Gain ◽  
Receive Array

scholarly journals Sparse Array Angle Estimation Using Reduced-Dimension ESPRIT-MUSIC in MIMO Radar

2013 ◽  
Vol 2013 ◽  
pp. 1-6 ◽  
Author(s):  
Chaozhu Zhang ◽  
Yucai Pang
Keyword(s):  
Low Cost ◽  
Direction Cosine ◽  
Mimo Radar ◽  
Angle Estimation ◽  
Linear Arrays ◽  
Reduced Dimension ◽  
Esprit Algorithm ◽  
Receive Array ◽  
True Direction ◽  
High Computational Complexity

Sparse linear arrays provide better performance than the filled linear arrays in terms of angle estimation and resolution with reduced size and low cost. However, they are subject to manifold ambiguity. In this paper, both the transmit array and receive array are sparse linear arrays in the bistatic MIMO radar. Firstly, we present an ESPRIT-MUSIC method in which ESPRIT algorithm is used to obtain ambiguous angle estimates. The disambiguation algorithm uses MUSIC-based procedure to identify the true direction cosine estimate from a set of ambiguous candidate estimates. The paired transmit angle and receive angle can be estimated and the manifold ambiguity can be solved. However, the proposed algorithm has high computational complexity due to the requirement of two-dimension search. Further, the Reduced-Dimension ESPRIT-MUSIC (RD-ESPRIT-MUSIC) is proposed to reduce the complexity of the algorithm. And the RD-ESPRIT-MUSIC only demands one-dimension search. Simulation results demonstrate the effectiveness of the method.

Array Grating Lobe Elimination of F-MIMO HF Radar with Colocated Antennas

2014 ◽  
Vol 556-562 ◽  
pp. 4510-4513
Author(s):  
Qiang Yang ◽  
Xian Mei Hou
Keyword(s):  
Multiple Input Multiple Output ◽  
Pso Algorithm ◽  
Mimo Radar ◽  
Hf Radar ◽  
Frequency Diversity ◽  
Grating Lobe ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Array Structure ◽  
Receive Array

Multiple-input multiple-output (MIMO) radar with frequency diversity (f-MIMO) is applied to HF radar. An array processing model of f-MIMO HF radar is developed. To eliminate the grating lobe of f-MIMO radar beamforming, two approaches are proposed. One is to apply particle swarm optimization (PSO) algorithm to select the optimal carrier frequency combination. Another is to extract array elements from the virtual receive array to get the optimal sparse array structure, and the simplified physical receive array structure is proposed. Simulation results demonstrate the effectiveness of the method proposed.

scholarly journals Sparse Recovery for Bistatic MIMO Radar Imaging in the Presence of Array Gain Uncertainties

2014 ◽  
Vol 2014 ◽  
pp. 1-6 ◽  
Author(s):  
Jun Li ◽  
Shengqi Zhu ◽  
Xixi Chen ◽  
Li Lv ◽  
Guisheng Liao ◽  
...  
Keyword(s):  
Optimization Problem ◽  
Multiple Input Multiple Output ◽  
Sparse Recovery ◽  
Mimo Radar ◽  
Range Cell ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Gain Errors ◽  
Array Gain ◽  
Receive Array

A sparse recovery based transmit-receive angle imaging scheme is proposed for bistatic multiple-input multiple-output (MIMO) radar. The redundancy of the transmit and receive angles in the same range cell is exploited to construct the sparse model. The imaging is then performed by compressive sensing method with consideration of both the transmit and receive array gain uncertainties. An additional constraint is imposed on the inverse of the transmit and receive array gain errors matrices to make the optimization problem of the CS solvable. The image of the targets can be reconstructed using small number of snapshots in the case of large array gain uncertainties. Simulation results confirm the effectiveness of the proposed scheme.

New Transmit-Receive Array Configurations for the MIMO Radar With Enhanced Degrees of Freedom

2020 ◽  
Vol 24 (7) ◽  
pp. 1534-1538
Author(s):  
Abdul Hayee Shaikh ◽  
Xiaoyu Dang ◽  
Tanveer Ahmed ◽  
Daqing Huang
Keyword(s):  
Degrees Of Freedom ◽  
Mimo Radar ◽  
Receive Array
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