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 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 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 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.

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.

MIMO Beamforming

2009 ◽  
pp. 240-263
Author(s):  
Qinghua Li ◽  
Xintian Eddie Lin ◽  
Jianzhong ("Charlie") Zhang
Keyword(s):  
Multiple Input Multiple Output ◽  
Industrial Applications ◽  
Antenna System ◽  
Limiting Factor ◽  
Transmit Beamforming ◽  
Underlying Principle ◽  
Input Multiple Output ◽  
Time Division ◽  
Channel Reciprocity ◽  
Mimo Beamforming

Transmit beamforming improves the performance of multiple-input multiple-output antenna system (MIMO) by exploiting channel state information (CSI) at the transmitter. Numerous MIMO beamforming schemes are proposed in open literature and standard bodies such as 3GPP, IEEE 802.11n and 802.16d/e. This chapter describes the underlying principle, evolving techniques, and corresponding industrial applications of MIMO beamforming. The main limiting factor is the cumbersome overhead to acquire CSI at the transmitter. The solutions are categorized into FDD (Frequency Division Duplex) and TDD (Time Division Duplex) approaches. For all FDD channels and radio calibration absent TDD channels, channel reciprocity is not available and explicit feedback is required. Codebook-based feedback techniques with various quantization complexities and feedback overheads are depicted in this chapter. Furthermore, we discuss transmit/receive (Tx/Rx) radio chain calibration and channel sounding techniques for TDD channels, and show how to achieve channel reciprocity by overcoming the Tx/Rx asymmetry of the RF components

scholarly journals Assessment of Compressive Sensing 2 × 2 MIMO Antenna Design for Millimeter-Wave Radar Image Enhancement

Electronics ◽  
2020 ◽  
Vol 9 (4) ◽  
pp. 624
Author(s):  
Neda Rojhani ◽  
Marco Passafiume ◽  
Matteo Lucarelli ◽  
Giovanni Collodi ◽  
Alessandro Cidronali
Keyword(s):  
Compressive Sensing ◽  
Millimeter Wave ◽  
Multiple Input Multiple Output ◽  
Array Antenna ◽  
Random Pattern ◽  
Mimo Antenna ◽  
Millimeter Wave Radar ◽  
Random Array ◽  
Wave Radar ◽  
Input Multiple Output

This paper presents a microstrip array antenna designed for a 2 × 2 Compressive Sensing Multiple-Input Multiple-Output (CS-MIMO) millimeter-wave radar operating at 37.5 GHz. The CS-MIMO linear array antenna is designed to obtain an optimal aperture by seeking a suitable random pattern for the antenna positions. Applying CS allows a considerable reduction in the number of antennas respect to a dense array based on the Nyquist criterion. In this study, we report all possible configurations of 2 × 2 CS-MIMO by placing antennas in random positions, plus their compression ratio. Finally, by selecting the proper design, we examine the experimental validation of the CS-MIMO antenna prototype by comparing measurements and simulations with a Standard MIMO (Std-MIMO) antenna prototype as a benchmark. The experimental results show that the angular resolution can be increased through a random array CS-MIMO by a factor of at least 2.9 respect to Std-MIMO while preserving the radar field of view.

The Application of a Kind of New LFM Signal in Quasi-Continuous Wave Radar

2013 ◽  
Vol 347-350 ◽  
pp. 1087-1090
Author(s):  
Zhi Kuan Zheng ◽  
Qiang He ◽  
Zhuang Zhi Han
Keyword(s):  
Short Range ◽  
Continuous Wave ◽  
Short Pulse ◽  
Blind Spot ◽  
Detection Range ◽  
Range Resolution ◽  
Pulse Radar ◽  
Time Bandwidth Product ◽  
Wave Radar ◽  
Close Range

In order to solve the contradiction of pulse radar detection range and range resolution, the LFM signal which has a large time-bandwidth product is chosen to be modulated on the transmitter pulse. So that the radar has larger width and higher range resolution. Since the conversion of the transceiver switches, wide LFM signal may cause close range blind spots. Timeshare launching one long and one short signals is traditional solution, but it will cause a lower data rate. A kind of dual-LFM signal based on frequency division multiplexing is presented, the short pulse is used in short-range to offset the lack of wide LFM signal. Through simulation, it is guaranteed that, by using this kind of signal, the radar has a higher resolution regardless of the target distance, and the short-range blind spot also can be eliminated.

scholarly journals Ionospheric Clutter Model for HF Sky-Wave Path Propagation with an FMCW Source

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Xuguang Yang ◽  
Aijun Liu ◽  
Changjun Yu ◽  
Linwei Wang
Keyword(s):  
High Frequency ◽  
Peak Power ◽  
Continuous Wave ◽  
Model Simulation ◽  
Hf Radar ◽  
Electron Density Fluctuation ◽  
Vertical Drift ◽  
Wave Radar ◽  
Wave Path ◽  
Simulation Results

A theoretical model of the sky-wave path propagation with frequency modulated continuous wave (FMCW) source for high frequency (HF) radar is proposed in this paper. Based on the modeling of pulsed source, the expression of the received electric field with an FMCW source is derived for the reflection case from the ionospheric irregularities. Subsequently, the ionospheric reflection coefficient with different phase power spectrums for vertical and oblique backscattering propagation paths is incorporated into the ionospheric clutter model. Simulation results show that the peak power of FMCW in average is lower than that of pulsed waveform. Furthermore, different incident angles and magnetic field in mid-latitude can also influence the power density of the backscattering ionospheric clutter. Finally, the data analysis results from the high frequency surface wave radar (HFSWR) and Ionosonde collected in Yellow Sea preliminarily verify the inversion of the variance of the electron density fluctuation and the vertical drift velocity of the irregularities within ionosphere.

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