scholarly journals MIMO Radar Using a Vector Network Analyzer

Electronics ◽  
2019 ◽  
Vol 8 (12) ◽  
pp. 1447
Author(s):  
Mostafa Hefnawi ◽  
Joey Bray ◽  
Jonathan Bathurst ◽  
Yahia Antar
Keyword(s):  
Continuous Wave ◽  
Multiple Input Multiple Output ◽  
Mimo Radar ◽  
Radar Signal ◽  
Network Analyzer ◽  
Range Resolution ◽  
Simulink Model ◽  
Input Multiple Output ◽  
Virtual Array ◽  
Critical Requirement

In this paper, a multiple-input multiple-output (MIMO) radar system was developed using a Keysight’s N5244A 4-port PNA-X network analyzer and Simulink. The system can transmit and receive TDM stepped-frequency continuous wave signals with a total sweep bandwidth of 450 MHz. The system also provides a reliable, self-contained phase-coherent RF front-end across four RF channels, which is a critical requirement for MIMO Radar signal processing algorithms. A Simulink model was built to organize the collected S-parameters into a virtual array and to perform IFFT processing so that range and angle information from targets could be extracted. The experimental results show the ability of the MIMO radar to distinguish between multiple closely spaced targets with a 33 cm range resolution and a 19o angle resolution.

scholarly journals SPARX, a MIMO Array for Ground-Based Radar Interferometry

Sensors ◽  
2019 ◽  
Vol 19 (2) ◽  
pp. 252 ◽  
Author(s):  
Alberto Michelini ◽  
Francesco Coppi ◽  
Alberto Bicci ◽  
Giovanni Alli
Keyword(s):  
Multiple Input Multiple Output ◽  
Mimo Radar ◽  
Sar Interferometry ◽  
Open Pit ◽  
Acquisition Time ◽  
Atmospheric Effects ◽  
Mechanical Assembly ◽  
Input Multiple Output ◽  
Virtual Array ◽  
Interferometric Sar

Ground-Based SAR Interferometry (GB-InSAR) is nowadays a proven technique widely used for slope monitoring in open pit mines and landslide control. Traditional GB-InSAR techniques involve transmitting and receiving antennas moving on a scanner to achieve the desired synthetic aperture. Mechanical movement limits the acquisition speed of the SAR image. There is a need for faster acquisition time as it plays an important role in correcting rapidly varying atmospheric effects. Also, a fast imaging radar can extend the applications to the measurement of vibrations of large structures. Furthermore, the mechanical assembly put constraints on the transportability and weight of the system. To overcome these limitations an electronically switched array would be preferable, which however faces enormous technological and cost difficulties associated to the large number of array elements needed. Imaging Multiple-Input Multiple Output (MIMO) radars can be used as a significant alternative to usual mechanical SAR and full array systems. This paper describes the ground-based X-band MIMO radar SPARX recently developed by IDS GeoRadar in order to overcome the limits of IDS GeoRadar’s well-established ground based interferometric SAR systems. The SPARX array consists of 16 transmit and 16 receive antennas, organized in independent sub-modules and geometrically arranged in order to synthesize an equally spaced virtual array of 256 elements.

Oil-Spills Detection in MIMO-SAR Radar Images by High Order Statistics

2013 ◽  
Vol 443 ◽  
pp. 649-652
Author(s):  
Yan Ling Luo
Keyword(s):  
Oil Spills ◽  
Multiple Input Multiple Output ◽  
Mimo Radar ◽  
Radar Signal ◽  
Future Research ◽  
Signal Model ◽  
Radar Images ◽  
Multiple Input ◽  
Input Multiple Output ◽  
High Order Statistics

MIMO radar (Multiple input multiple output radar) is a hot topic which gets lots of attention from researchers all around the world recently. It can achieve better detection performance than conventional phased radar. In this paper, the MIMO radar signal model is studied, and then the concept of MIMO radar is applied into SAR. The technique is employed to detect the oil spill in sea. At last, some conclusion is drawn. And some item for future research in presented also.

Multi-Target Direction Measurement of Bistatic MIMO Radar

2014 ◽  
Vol 556-562 ◽  
pp. 2797-2801
Author(s):  
Jing Fang Wang
Keyword(s):  
Multiple Input Multiple Output ◽  
Mimo Radar ◽  
Radar Signal ◽  
Great Success ◽  
Two Dimensional ◽  
Signal Model ◽  
Bistatic Mimo Radar ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Mimo Technology

Multiple-input multiple output (MIMO) radar has been widespread concern in the domestic and foreign researchers. Bistatic radar draws on the great success of MIMO technology in the communications field, and it has many advantages over conventional radar. The direction angles estimations of bistatic MIMO radar are researched. To contrast traditional radar DOA estimates, the direction vector of the bistatic MIMO radar is the Knonecker plot of the emission vector and reception vector, that two-dimensional direction angles is estimated. To solve this problem, the principle of bistatic MIMO radar signal model is in-depthly researched.By proposing Capon dimensionality reduction method, the two-dimensional directions of the dual-based MIMO radar are estimated, and computer simulation is to verify the effectiveness of the method.

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.

scholarly journals 2D-DOD and 2D-DOA Estimation for a Mixture of Circular and Strictly Noncircular Sources Based on L-Shaped MIMO Radar

Sensors ◽  
2020 ◽  
Vol 20 (8) ◽  
pp. 2177
Author(s):  
Jiaxiong Fang ◽  
Yonghong Liu ◽  
Yifang Jiang ◽  
Yang Lu ◽  
Zehao Zhang ◽  
...  
Keyword(s):  
Multiple Input Multiple Output ◽  
Estimation Method ◽  
Doa Estimation ◽  
Mimo Radar ◽  
Joint Diagonalization ◽  
Data Vector ◽  
Direction Of Departure ◽  
Input Multiple Output ◽  
Virtual Array ◽  
Cramer Rao Bound

In this paper, a joint diagonalization based two dimensional (2D) direction of departure (DOD) and 2D direction of arrival (DOA) estimation method for a mixture of circular and strictly noncircular (NC) sources is proposed based on an L-shaped bistatic multiple input multiple output (MIMO) radar. By making full use of the L-shaped MIMO array structure to obtain an extended virtual array at the receive array, we first combine the received data vector and its conjugated counterpart to construct a new data vector, and then an estimating signal parameter via rotational invariance techniques (ESPRIT)-like method is adopted to estimate the DODs and DOAs by joint diagonalization of the NC-based direction matrices, which can automatically pair the four dimensional (4D) angle parameters and solve the angle ambiguity problem with common one-dimensional (1D) DODs and DOAs. In addition, the asymptotic performance of the proposed algorithm is analyzed and the closed-form stochastic Cramer–Rao bound (CRB) expression is derived. As demonstrated by simulation results, the proposed algorithm has outperformed the existing one, with a result close to the theoretical benchmark.

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.

A Simulation System for MIMO Radar

2010 ◽  
Vol 121-122 ◽  
pp. 633-639
Author(s):  
Jian Kui Zeng ◽  
Zi Ming Dong
Keyword(s):  
Signal Processing ◽  
Multiple Input Multiple Output ◽  
Mimo Radar ◽  
Simulation System ◽  
Radar Signal ◽  
Signal Model ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Conventional Counterpart ◽  
Radar Technique

MIMO radar (Multiple input multiple output radar) is a novel radar technique developed recently. It can achieve better detection performance than conventional phased radar. In this paper, the MIMO radar signal model is studied, and then the signal processing flow of the MIMO radar is researched. At last, a simulation platform with the Matlab is established to testify the advantage of MIMO radar over its conventional counterpart.

scholarly journals A MIMO FMCW radar approach to HFSWR

2011 ◽  
Vol 9 ◽  
pp. 159-163 ◽  
Author(s):  
J. O. Hinz ◽  
U. Zölzer
Keyword(s):  
Continuous Wave ◽  
Multiple Input Multiple Output ◽  
Hf Radar ◽  
Limiting Factor ◽  
State Monitoring ◽  
Available Bandwidth ◽  
Range Resolution ◽  
Ship Detection ◽  
Wave Radar ◽  
Input Multiple Output

Abstract. In this paper we propose one possible approach how to apply the concept of multiple-input multiple-output (MIMO) to monostatic Frequency Modulated Continuous Wave (FMCW) High-Frequency Surface Wave Radar (HFSWR) in a maritime environment. Common tasks for a HFSWR are sea-state monitoring and ship detection, where our focus is on ship detection. A limiting factor in HFSWR is the available bandwidth, which is inversely proportional to the range resolution capability of the radar and typical below 100 kHz. The question is how to extend or combine a conventional single-input multiple-output (SIMO) FMCW phased-array type radar with stretch processing and the colocated MIMO concept to "reuse" the very limited HF radar band resources. Another important question to answer is how MIMO FMCW waveforms can be separated at the receiver.

scholarly journals MIMO High Frequency Surface Wave Radar Using Sparse Frequency FMCW Signals

2017 ◽  
Vol 2017 ◽  
pp. 1-16 ◽  
Author(s):  
Mengguan Pan ◽  
Baixiao Chen
Keyword(s):  
Surface Wave ◽  
High Frequency ◽  
Continuous Wave ◽  
Multiple Input Multiple Output ◽  
Mimo Radar ◽  
Large Bandwidth ◽  
Wave Radar ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Processing Framework

The heavily congested radio frequency environment severely limits the signal bandwidth of the high frequency surface wave radar (HFSWR). Based on the concept of multiple-input multiple-output (MIMO) radar, we propose a MIMO sparse frequency HFSWR system to synthesize an equivalent large bandwidth waveform in the congested HF band. The utilized spectrum of the proposed system is discontinuous and irregularly distributed between different transmitting sensors. We investigate the sparse frequency modulated continuous wave (FMCW) signal and the corresponding deramping based receiver and signal processor specially. A general processing framework is presented for the proposed system. The crucial step is the range-azimuth processing and the sparsity of the carrier frequency causes the two-dimensional periodogram to fail when applied here. Therefore, we introduce the iterative adaptive approach (IAA) in the range-azimuth imaging. Based on the initial 1D IAA algorithm, we propose a modified 2D IAA which particularly fits the deramping processing based range-azimuth model. The proposed processing framework for MIMO sparse frequency FMCW HFSWR with the modified 2D IAA applied is shown to have a high resolution and be able to provide an accurate and clear range-azimuth image which benefits the following detection process.

scholarly journals OFDM Chirp Waveform Design Based on Subchirp Bandwidth Overlap and Segmented Transmitting for Low Correlation Interference in MIMO Radar

Sensors ◽  
2019 ◽  
Vol 19 (12) ◽  
pp. 2696
Author(s):  
Xiang Lan ◽  
Min Zhang ◽  
Jin-Xing Li
Keyword(s):  
Orthogonal Frequency Division Multiplexing ◽  
Multiple Input Multiple Output ◽  
Mimo Radar ◽  
Detection Performance ◽  
Range Image ◽  
Range Resolution ◽  
Multiple Input ◽  
Chirp Signals ◽  
Input Multiple Output ◽  
Correlation Performance

There are some special merits for the orthogonal frequency division multiplexing (OFDM) chirp waveform as multiple input multiple output (MIMO) signals. This signal has high range resolution, good Doppler tolerance, and constant modulus superiority since it exploits a full bandwidth and is based on chirp signals. The correlation sidelobe peaks level are critical for the detection requirement of MIMO radar signals, however conventional OFDM chirp signals produce high autocorrelation sidelobe peaks (ASP) and cross-correlation peaks (CP), which reduces detection performance. In this paper, we explore the structure of OFDM chirp signals’ autocorrelation function and proposed a scheme to reduce the designed signal’s ASP by a designing suitable range of subchirp bandwidth and a segmented transmit-receive mode. Next, we explore a suitable range of interval between the chirp rates of each two signals to reduce the CP. The simulation of designed signals verifies the effectiveness of the proposed methods in the reduction of ASP and CP, with the correlation performance being compared with recent relate studies. In addition, the multiple signals detection and one-dimensional range image simulation show the good detection performance of a designed signal in MIMO radar detection.

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