scholarly journals An MIMO Radar System Based on the Sparse-Array and Its Frequency Migration Calibration Method

Sensors ◽  
2019 ◽  
Vol 19 (16) ◽  
pp. 3580 ◽  
Author(s):  
Yue Ma ◽  
Chen Miao ◽  
Yangying Zhao ◽  
Wen Wu
Keyword(s):  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Calibration Method ◽  
Transformation Method ◽  
Side Lobe ◽  
Mimo Radar ◽  
Radar System ◽  
Side Lobe Level ◽  
Automotive Radar ◽  
Sparse Array

In this paper, a Multiple Input Multiple Output (MIMO) radar system based on a sparse-array is proposed. In order to reduce the side-lobe level, a genetic algorithm (GA) is used to optimize the array arrangement. To reduce the complexity of the system, time-division multiplexing (TDM) technology is adopted. Since the signals are received in different periods, a frequency migration will emerge if the target is in motion, which will lead to the lower direction-of-arrival (DOA) performance of the system. To solve this problem, a stretching transformation method in the fast-frequency slow-time domain is proposed, in order to eliminate frequency migration. Only minor adjustments need to be implemented for the signal processing, and the root-mean-square error (RMSE) of the DOA estimation will be reduced by about 90%, compared with the one of an uncalibrated system. For example, a uniform linear array (ULA) MIMO system with 2 transmitters and 20 receivers can be replaced by the proposed system with 2 transmitters and 12 receivers, achieving the same DOA performance. The calibration formulations are given, and the simulation results of the automotive radar system are also provided, which validate the theory.

scholarly journals A MIMO Radar System based on Fractal Antenna Arrays for Level Measurement Applications

2021 ◽  
Vol 19 ◽  
pp. 23-29
Author(s):  
Christoph Dahl ◽  
Michael Vogt ◽  
Ilona Rolfes
Keyword(s):  
Antenna Array ◽  
Antenna Arrays ◽  
Multiple Input Multiple Output ◽  
Side Lobe ◽  
Mimo Radar ◽  
Radar System ◽  
Scanning Angle ◽  
Level Measurement ◽  
Multiple Input ◽  
Input Multiple Output

Abstract. In this contribution, the design of a multiple-input multiple-output (MIMO) radar system in 77–81 GHz range with 18 transmitting antennas and 24 receiving antennas for measuring the height profile of bulk solids in silos, is presented and discussed. The antenna array topologies are optimized by utilizing space filling fractals in order to approximate a circular shaped antenna array on a hexagonal grid. The proposed MIMO radar system achieves an angular resolution of 3.1∘ for a maximum scanning angle of ±45∘ and a side lobe suppression of 12.6 dB. The performance of the system has been evaluated by test measurements on a sand heap, showing an improved measurement accuracy compared to conventional radar level systems.

scholarly journals Fractal antenna arrays for MIMO radar applications

2017 ◽  
Vol 9 (10) ◽  
pp. 2019-2028 ◽  
Author(s):  
Christoph Dahl ◽  
Michael Vogt ◽  
Ilona Rolfes
Keyword(s):  
Antenna Arrays ◽  
Angular Resolution ◽  
Multiple Input Multiple Output ◽  
Side Lobe ◽  
Mimo Radar ◽  
Side Lobe Level ◽  
Fractal Antenna ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Radar Applications

In this contribution, fractal antenna arrays are analyzed for their applicability in multiple-input multiple-output (MIMO) radars. Array geometries based on the Fudgeflake fractal and the Gosper island fractal are investigated. In addition, a concept for the combination of both fractals is shown in order to increase the flexibility concerning the number of transmitting and receiving antennas. The presented fractal MIMO concepts can be utilized in order to improve the angular resolution and to reduce the sidelobe level for a given number of transmitting and receiving antennas. It is shown that a fractal MIMO concept with 21 transmitting antennas and 21 receiving antennas improves the angular resolution to 4.6 degrees and reduces side lobe level by 3.1 dB compared to a MIMO configuration based on two linear arrays with the same number of antenna elements. In addition, the results are experimentally validated by broadband radar measurements.

scholarly journals Interchannel Interference and Mitigation in Distributed MIMO RF Sensing

Sensors ◽  
2021 ◽  
Vol 21 (22) ◽  
pp. 7496
Author(s):  
Sahil Waqar ◽  
Matthias Pätzold
Keyword(s):  
Continuous Wave ◽  
Channel Model ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Three Dimensional ◽  
Mimo Radar ◽  
Radar System ◽  
Channel Interference ◽  
Rf Sensing ◽  
K Band

In this paper, we analyze and mitigate the cross-channel interference, which is found in multiple-input multiple-output (MIMO) radio frequency (RF) sensing systems. For a millimeter wave (mm-Wave) MIMO system, we present a geometrical three-dimensional (3D) channel model to simulate the time-variant (TV) trajectories of a moving scatterer. We collected RF data using a state-of-the-art radar known as Ancortek SDR-KIT 2400T2R4, which is a frequency-modulated continuous wave (FMCW) MIMO radar system operating in the K-band. The Ancortek radar is currently the only K-band MIMO commercial radar system that offers customized antenna configurations. It is shown that this radar system encounters the problem of interference between the various subchannels. We propose an optimal approach to mitigate the problem of cross-channel interference by inducing a propagation delay in one of the channels and apply range gating. The measurement results prove the effectiveness of the proposed approach by demonstrating a complete elimination of the interference problem. The application of the proposed solution on Ancortek’s SDR-KIT 2400T2R4 allows resolving all subchannel links in a distributed MIMO configuration. This allows using MIMO RF sensing techniques to track a moving scatterer (target) regardless of its direction of motion.

scholarly journals High-Resolution and Large-Detection-Range Virtual Antenna Array for Automotive Radar Applications

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1702
Author(s):  
Haythem Abdullah ◽  
Mohamed Mabrouk ◽  
Ahmed Abd-Elnaby Kabeel ◽  
Amr Hussein
Keyword(s):  
High Resolution ◽  
Antenna Array ◽  
Collision Avoidance ◽  
Antenna Arrays ◽  
Mimo System ◽  
Side Lobe ◽  
Side Lobe Level ◽  
Automotive Radar ◽  
Detection Range ◽  
Receiving Antenna

Collision avoidance and autonomous control of vehicles have become essential needs for providing a high-quality and safe life. This paper introduces a new generic scheme for a virtual antenna array (VAA) and its application in a train collision-avoidance system (TCAS). The proposed TCAS shall have the capability of identifying the range and angle of an object in front of a moving train and provide the required alerts. Thereby, a new virtual array distribution for both the transmitting and the receiving antenna arrays is introduced to get a long-range object detection and high-resolution multi-input multi-output (MIMO) system. This can be accomplished because the VAA radiation pattern is the multiplication of the radiation patterns for both the transmitting and receiving antenna arrays, which is different than each one of them alone. In this work, the VAA is utilized in radar systems in which the radar range depends on the multiplication of the gain of the transmitting and receiving antennas. So, we introduce a new scheme for the general design of VAA-based radars. A prototype for the antenna system was fixed on a of Texas Instruments platform for the cascading radar. One of the main problems of the VAA is the loss of radiated power in undesired directions, which affects the maximum detection range in beamforming systems and degrades the diversity gain in MIMO applications. These issues have been solved by the introduction of the practical implementation of a proposed high-gain, low side lobe level VAA system for automotive radar that is based on the integration of four AWR1243 RF chips operating in a frequency range of 76 GHz to 81 GHz. It was implemented using low-power 45 nm (TI) RFCMOS technology. The measured gain of the realized VAA was 47.2 dBi, which was 1.815 times higher than that of the Texas instrumentation linear frequency modulated continuous wave (TI’ LFMCW) radar, which was 26 dBi. The proposed VAA saved 45% of the required implementation area compared to the TI’ LFMCW antenna array. The VAA system was fabricated and tested in an anechoic chamber, and it was found that the simulated and measured patterns of the proposed VAA were highly matched in terms of half-power beamwidth and side lobe level.

Hybrid SIMO and MIMO sparse array radar

2014 ◽  
Vol 6 (3-4) ◽  
pp. 389-395 ◽  
Author(s):  
Takuya Takayama ◽  
Masayuki Sugano ◽  
Yukinobu Tokieda ◽  
Hiroki Sugawara
Keyword(s):  
Multiple Input Multiple Output ◽  
Mimo Radar ◽  
Chirp Pulse ◽  
Pulse Waveform ◽  
Sparse Array ◽  
Input Multiple Output ◽  
Array Calibration ◽  
Code Division Multiple ◽  
The Cost ◽  
Array Imaging

This paper clarifies what we benefit from single-input–multiple-output (SIMO) or multiple-input–multiple-output (MIMO) radar. We have developed an X-band sparse array imaging radar system capable of operating at both SIMO and MIMO modes. The hybrid radar modes are realized without any modification in hardware, but simply by switching the scheme of waveform generation and post-processing. A comparison has been made between the SIMO mode adopting a chirp pulse waveform and the MIMO mode based on the code-division multiple access method using the Gold-coded pulse waveform. Mutually complementary properties between the SIMO and MIMO modes in terms of the cost of computation, the ease of array calibration, and the detectability of targets are clarified through simulations and an experiment.

scholarly journals FMCW sparse array imaging and restoration for microwave gauging

2012 ◽  
Vol 10 ◽  
pp. 333-339
Author(s):  
S. Kolb ◽  
R. Stolle
Keyword(s):  
Continuous Wave ◽  
Imaging System ◽  
Side Lobe ◽  
Side Lobe Level ◽  
Essential Property ◽  
Sparse Array ◽  
The Cost ◽  
Array Imaging ◽  
Multistatic Radar ◽  
The Given

Abstract. The application of imaging radar to microwave level gauging represents a prospect of increasing the reliability of target detection. The aperture size of the used sensor determines the underlying azimuthal resolution. In consequence, when FMCW-based multistatic radar (FMCW: frequency modulated continuous wave) is used, the number of antennas dictates this essential property of an imaging system. The application of a sparse array leads to an improvement of the azimuthal resolution by keeping the number of array elements constant with the cost of increased side lobe level. Therefore, ambiguities occur within the imaging process. This problem can be modelled by a point spread function (PSF) which is common in image processing. Hence, an inverse system to the imaging system is needed to restore unique information of existing targets within the observed radar scenario. In general, the process of imaging is of ill-conditioned nature and therefore appropriate algorithms have to be applied. The present paper first develops the degradation model, namely PSF, of an imaging system based on a uniform linear array in time domain. As a result, range and azimuth dimensions are interdependent and the process of imaging has to be reformulated in one dimension. Matrix-based approaches can be adopted in this way. The second part applies two computational methods to the given inverse problem, namely quadratic and non-quadratic regularization. Notably, the second one exhibits an ability to suppress ambiguities. This can be demonstrated with the results of both, simulations and measurements, and enables sparse array imaging to localize point targets more unambiguously.

scholarly journals An Imaging Plane Calibration Method for MIMO Radar Imaging

Sensors ◽  
2019 ◽  
Vol 19 (23) ◽  
pp. 5261
Author(s):  
Yuanyue Guo ◽  
Bo Yuan ◽  
Zhaohui Wang ◽  
Rui Xia
Keyword(s):  
Multiple Input Multiple Output ◽  
Calibration Method ◽  
Radar Imaging ◽  
Spatial Spectrum ◽  
Mimo Radar ◽  
Cooperative Movement ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Calibration Algorithm ◽  
Imaging Plane

In two dimensional cross-range multiple-input multiple-output radar imaging for aerial targets, due to the non-cooperative movement of the targets, the estimated imaging plane parameters, namely the center and the posture angles of the imaging plane, may have deviations from true values, which defocus the final image. This problem is called imaging plane mismatch in this paper. Focusing on this problem, firstly the deviations of spatial spectrum fulfilling region caused by imaging plane mismatch is analyzed, as well as the errors of the corresponding spatial spectral values. Thereupon, the calibration operation is deduced when the imaging plane parameters are accurately obtained. Afterwards, an imaging plane calibration algorithm is proposed to utilize particle swarm optimization to search out the imaging plane parameters. Finally, it is demonstrated through simulations that the proposed algorithm can accurately estimate the imaging plane parameters and achieve good image focusing performance.

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 Design and Simulation of Microstrip Comb-Line Array Antenna at 78.5GHz for Automotive Radar Applications

2020 ◽  
Vol 9 (5) ◽  
pp. 696-699
Keyword(s):  
Side Lobe ◽  
Travelling Wave ◽  
Substrate Material ◽  
Array Antenna ◽  
Side Lobe Level ◽  
Automotive Radar ◽  
Sidelobe Level ◽  
Line Array ◽  
Linearly Polarized ◽  
Radar Applications

The design of low side lobe level 45 degree linearly polarized microstrip comb-line shaped travelling wave array antenna for 77GHz automotive radar applications is presented. The 20 elements array is designed on Astra Isola substrate material. Variable width radiating elements are incorporated in the design to utilize an amplitude tapering technique to achieve lower sidelobe level. Taylor distribution is used to determine voltage excitation. The measured gain is found to be around 16.23dB and the side lobe level of -14.28dB at 78.5GHz.

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