Real-time through-wall imaging using an ultrawideband multiple-input multiple-output (MIMO) phased array radar system

2010 ◽  
Author(s):  
T S Ralston ◽  
G L Charvat ◽  
J E Peabody
Keyword(s):  
Real Time ◽  
Phased Array ◽  
Multiple Input Multiple Output ◽  
Radar System ◽  
Phased Array Radar ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Wall Imaging

scholarly journals Performance Characteristics: The Phase Mimo Radar Technique

2020 ◽  
Vol 8 (6) ◽  
pp. 379-382
Keyword(s):  
Phased Array ◽  
Multiple Input Multiple Output ◽  
Weight Vector ◽  
Mimo Radar ◽  
Phased Array Radar ◽  
Processing Gain ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Beam Patterns ◽  
Radar Technique

The phased-MIMO radar technology is the combination of the phased array and the MIMO (Multiple Input Multiple Output) radar technique. This proposed new technique gives the benefits of MIMO radar without sacrificing the main benefits of phased-array radar, which is the gain in coherent processing on the emission side. The intention of the proposed technique is to divide the transmission network into a number of overlapping subnets. This means that each subnet is used to consistently transmit a waveform that is orthogonal to the waveforms transmitted by the other subnets. The MIMO technique applied to traditional phased array radar has been investigated and has yielded many advantages over the phased array radar system and the MIMO radar. A Coherent processing gain can be obtained by designing a weight vector for each subnet to form a beam in a particular direction in space. The proposed technique compared to the previous techniques, which was a phased array and a MIMO radar, is analytically demonstrated and simulated by MATLAB analysis of the corresponding beam patterns and of the overall beam patterns.

Estimation of clutter degrees of freedom for airborne multiple‐input multiple‐output‐phased array radar

2013 ◽  
Vol 7 (6) ◽  
pp. 652-657 ◽  
Author(s):  
Wenchong Xie ◽  
Xichuan Zhang ◽  
Yongliang Wang ◽  
Yong Zhu
Keyword(s):  
Degrees Of Freedom ◽  
Phased Array ◽  
Multiple Input Multiple Output ◽  
Phased Array Radar ◽  
Multiple Input ◽  
Input Multiple Output

scholarly journals Real-Time Estimation in a Turbulent Jet Using Multiple-Input-Multiple-Output Transfer Functions

2019 ◽  
Author(s):  
Igor Maia ◽  
Peter Jordan ◽  
Eduardo Martini ◽  
André V. Cavalieri ◽  
Aaron Towne ◽  
...  
Keyword(s):  
Real Time ◽  
Transfer Functions ◽  
Multiple Input Multiple Output ◽  
Time Estimation ◽  
Turbulent Jet ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Real Time Estimation

scholarly journals Design and Analysis of Multiple-Input Multiple-Output Radar System Based on RF Single-Link Technology

Symmetry ◽  
2018 ◽  
Vol 10 (5) ◽  
pp. 130 ◽  
Author(s):  
He Yu ◽  
Guohui Yang ◽  
Yingsong Li ◽  
Fanyi Meng
Keyword(s):  
Multiple Input Multiple Output ◽  
Radar System ◽  
Multiple Input ◽  
Single Link ◽  
Input Multiple Output

scholarly journals An Implementation Scheme of Range and Angular Measurements for FMCW MIMO Radar via Sparse Spectrum Fitting

Electronics ◽  
2020 ◽  
Vol 9 (3) ◽  
pp. 389
Author(s):  
Lidong Huang ◽  
Xianpeng Wang ◽  
Mengxing Huang ◽  
Liangtian Wan ◽  
Zhiguang Han ◽  
...  
Keyword(s):  
Continuous Wave ◽  
Multiple Input Multiple Output ◽  
Mimo Radar ◽  
Radar System ◽  
Superior Performance ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Angular Measurements ◽  
Implementation Scheme ◽  
Spectrum Fitting

The work presented in this paper is about implementing a frequency-modulated continuous wave (FMCW) multiple-input multiple-output (MIMO) positioning radar and a sparse spectrum fitting (SpSF) algorithm for range and angular measurements. First, we designed a coherent FMCW MIMO radar system working in the S-band with low power consumption that consists of four transmitter and four receiver antennas and has the ability to extend its virtual aperture; thus, this system can achieve a higher resolution than conventional phased array radars. Then, the SpSF algorithm was designed for estimating the distance and angle of the targets in the FMCW MIMO radar. Due to the fact that the SpSF algorithm can exploit the spatial sparsity diversity of a signal, the SpSF algorithm that is applied in the designed MIMO radar system can achieve a better estimation performance than the multiple signal classification (MUSIC) and Capon algorithms, especially in the context of small snapshots and low signal-to-noise ratios (SNRs). The simulated and experimental results are used to prove the effectiveness of the designed MIMO radar and the superior performance of the algorithm.

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