Optimization of a MIMO radar antenna system for automotive applications

Vasanelli, Claudia; Batra, Rahul; Waldschmidt, Christian

doi:10.23919/eucap.2017.7928056

Cited by 27 publications

(20 citation statements)

References 13 publications

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“…The array alignment is optimized using a Genetic Algorithm (GA). The implemented algorithm is adapted from [28] and [29]. The allowed MMIC positions are discretized with a grid of 0.1 λ within the simulation.…”

Section: B Design Criterion and Optimization Algorithmmentioning

confidence: 99%

“…In (7) (·) H denotes the Hermitian operator, · the Euclidian norm of a vector, and v(ϕ)=a(ϕ)⊗b(ϕ) is the virtual steering vector, which is given by Kronecker product ⊗ of the transmitter and receiver steering vectors a(ϕ) and b(ϕ) [33]. In comparison to [29], the fitness function f n is extended by a weighting with the maximum SLL max of the antenna pattern. Thus, arrays with a lower sidelobe level get a higher rank resulting into more robust arrays.…”

Section: B Design Criterion and Optimization Algorithmmentioning

confidence: 99%

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High-Resolution 160-GHz Imaging MIMO Radar Using MMICs With On-Chip Frequency Synthesizers

Dürr

Schwarz

Häfner

et al. 2019

IEEE Trans. Microwave Theory Techn.

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A high-resolution frequency modulated continuous wave imaging radar for short-range applications is presented. A range resolution of about 1 cm is achieved with a bandwidth of up to 16 GHz around 160 GHz. In order to overcome losses and large tolerances on a printed circuit board (PCB), 8 coherently coupled monolithic microwave integrated circuits (MMIC) are used, each with one transmit and receive antenna on-chip and each representing a single channel radar system. The signals on the PCB are below 12 GHz, which facilitates fabrication and enables a design with low-cost substrates. The MMIC comprises a phase noise optimized architecture with a fully integrated on-chip frequency synthesizer. Due to partly uncorrelated phase noise between the frequency synthesizer components, the noise level is increased in bistatic radar measurements between two different MMICs, which is explained by a thorough phase noise analysis. Time-division multiplexing is used to realize a multiple-input multiple-output system with a virtual array of 64 elements and an angular resolution better than 1.5 • for the designed array. The positioning tolerances of the MMICs are included into the design resulting in a robust array design. The high-resolution radar performance is proven by imaging radar measurements of two exemplary scenarios.

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Section: B Design Criterion and Optimization Algorithmmentioning

confidence: 99%

Section: B Design Criterion and Optimization Algorithmmentioning

confidence: 99%

High-Resolution 160-GHz Imaging MIMO Radar Using MMICs With On-Chip Frequency Synthesizers

Dürr

Schwarz

Häfner

et al. 2019

IEEE Trans. Microwave Theory Techn.

Self Cite

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show abstract

“…Simulation of radio wave propagation through the radome provides knowledge of the latter’s precise influence on the system accuracy and performances. Thus, an important issue concerns the effect of bumpers on the radar performances, topic that attracted great interest [ 12 , 13 , 14 , 15 , 16 , 17 ]. In the just referred works the coupling radar-radome effects (e.g., attenuation, signal pollution, …) was investigated but a parametric numerical modeling was not considered.…”

Section: Introductionmentioning

confidence: 99%

Parametric Electromagnetic Analysis of Radar-Based Advanced Driver Assistant Systems

Vermiglio

Champaney

Sancarlos

et al. 2020

Sensors

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Efficient and optimal design of radar-based Advanced Driver Assistant Systems (ADAS) needs the evaluation of many different electromagnetic solutions for evaluating the impact of the radome on the electromagnetic wave propagation. Because of the very high frequency at which these devices operate, with the associated extremely small wavelength, very fine meshes are needed to accurately discretize the electromagnetic equations. Thus, the computational cost of each numerical solution for a given choice of the design or operation parameters, is high (CPU time consuming and needing significant computational resources) compromising the efficiency of standard optimization algorithms. In order to alleviate the just referred difficulties the present paper proposes an approach based on the use of reduced order modeling, in particular the construction of a parametric solution by employing a non-intrusive formulation of the Proper Generalized Decomposition, combined with a powerful phase-angle unwrapping strategy for accurately addressing the electric and magnetic fields interpolation, contributing to improve the design, the calibration and the operational use of those systems.

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“…Strategies for the optimum placement of the antennas in sparse arrays have extensively been discussed [3][4][5]. These design strategies do not consider non-idealities and mutual coupling within the design process, resulting in a degradation of DoA estimation performance [6].…”

Section: Introductionmentioning

confidence: 99%

On the Calibration of mm-Wave MIMO Radars Using Sparse Antenna Arrays for DoA Estimation

Dürr¹,

Schwarz²,

Roos³

et al. 2019

2019 49th European Microwave Conference (EuMC)

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The multiple-input and multiple-output (MIMO) principle is a well-established method to improve the angular resolution of radars. Due to hardware limitations the maximum number of transmit and receive channels is often limited. In order to further increase the angular resolution with a given number of hardware channels, sparse arrays can be employed. However, the optimal placement of the antenna positions is a critical design parameter and it is difficult to consider non-idealities and mutual coupling within the design process. This paper addresses the non-idealities and the influence of coupling on the virtual array positions of a MIMO radar. An efficient calibration method to determine the real antenna positions is proposed. The discrete Fourier transform (DFT) based direction-of-arrival (DoA) estimation is shown with measurements of a 77 GHz and a 160 GHz MIMO radar for a uniform linear array (ULA) and two sparse arrays in comparison.

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Optimization of a MIMO radar antenna system for automotive applications

Cited by 27 publications

References 13 publications

High-Resolution 160-GHz Imaging MIMO Radar Using MMICs With On-Chip Frequency Synthesizers

High-Resolution 160-GHz Imaging MIMO Radar Using MMICs With On-Chip Frequency Synthesizers

Parametric Electromagnetic Analysis of Radar-Based Advanced Driver Assistant Systems

On the Calibration of mm-Wave MIMO Radars Using Sparse Antenna Arrays for DoA Estimation

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