2-D MIMO Radar: A Method for Array Performance Assessment and Design of a Planar Antenna Array

Serio, Adolfo Di; Hügler, Philipp; Roos, Fabian; Waldschmidt, Christian

doi:10.1109/tap.2020.2972643

Cited by 43 publications

(22 citation statements)

References 22 publications

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“…With the receivers located close to the MMICs, an interleaved sparse array with a hardware aperture size of 184 × 40.5 mm 2 is designed. Utilizing the genetic optimization from [6], the Rx antenna positions are optimized to adhere the design restrictions and to form an unambiguous array. The optimized Rx array performance is analyzed and shown in Fig.…”

Section: Mimo Antenna Arraymentioning

confidence: 99%

“…4(c). Comparing S with a fixed threshold leads to the ambiguity indicator matrix Q as introduced in [6], but S gives a better visualization and insight on the array performance.…”

Section: Mimo Antenna Arraymentioning

confidence: 99%

“…Radar sensors are used in various areas of application as they are able to provide accurate information on range, velocity, and the direction-of-arrival (DoA) of surrounding objects, even under harsh environmental conditions [1]- [5]. By distributing the antennas in two dimensions, DoA estimation in both azimuth and elevation is enabled, yielding a 4D imaging system [6], [7]. This information depth is required for the development of autonomous driving and future advanced driver assistance systems (ADAS) in the automotive 77 / 79 GHz band [8]- [10].…”

Section: Introductionmentioning

confidence: 99%

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System Performance of a 79 GHz High-Resolution 4D Imaging MIMO Radar With 1728 Virtual Channels

Schwarz¹,

Riese²,

Dorsch³

et al. 2022

IEEE J. Microw.

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Future driver assistance and autonomous driving systems require high-resolution 4D imaging radars that provide detailed and robust information about the vehicle's surroundings, even in poor weather or lighting conditions. In this work, a novel high-resolution radar system with 1728 virtual channels is presented, exceeding the state-of-the-art channel count for automotive radar sensors by a factor of 9. To realize the system, a new mixed feedthrough and distribution network topology is employed for the distribution of the ramp oscillator signal. A multilayer printed circuit board is designed and fabricated with all components assembled on the back side, while the radio frequency signal distribution is on a buried layer and only the antennas are on the front side. The array is optimized to enable both multipleinput multiple-output operation and transmit beamforming. A sparse array with both transmit and receive antennas close to the transceivers is realized to form a 2D array with a large unambiguous region of 130 • × 75 • with a maximal sidelobe level of −15 dB. The array features a 3 dB beamwidth of 0.78 • × 3.6 • in azimuth and elevation, respectively. Radar measurements in an anechoic chamber show that even the individual peaks of the absorber in the chamber can be detected and separated in the range-angle cut of the 4D radar image. The performance is validated by measurements of a parking lot, where cars, a pedestrian, a fence, and a street lamp can be detected, separated, and estimated correctly in size and position.INDEX TERMS Advanced driver assistance systems (ADAS), automotive radar, chirp sequence modulation, direction-of-arrival (DoA) estimation, frequency modulated continuous wave (FMCW), imaging radar, local oscillator (LO) feedthrough, mm-wave, multiple-input multiple-output (MIMO), time delay correction.This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination.

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Section: Mimo Antenna Arraymentioning

confidence: 99%

“…4(c). Comparing S with a fixed threshold leads to the ambiguity indicator matrix Q as introduced in [6], but S gives a better visualization and insight on the array performance.…”

Section: Mimo Antenna Arraymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

System Performance of a 79 GHz High-Resolution 4D Imaging MIMO Radar With 1728 Virtual Channels

Schwarz¹,

Riese²,

Dorsch³

et al. 2022

IEEE J. Microw.

Self Cite

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“…In engineering applications, two-dimensional (2D) direction estimation, i.e., 2D-DOD and 2D-DOA estimation, is more attractive than the former. It is well-known that in order to obtain 2D angle estimation using the scalar-array-based MIMO radar, non-linear Tx arrays and Rx arrays must be adopted [20][21][22][23], e.g., rectangular array, circular array, arbitrary array. Unfortunately, these nonlinear scalar geometries are usually too complex to be conformal with the platform.…”

Section: Introductionmentioning

confidence: 99%

PARAFAC Estimators for Coherent Targets in EMVS-MIMO Radar with Arbitrary Geometry

et al. 2022

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In the past few years, multiple-input multiple-output (MIMO) radar with electromagnetic vector sensor (EMVS) array, or called EMVS-MIMO radar, has attracted extensive attention in target detection. Unlike the traditional scalar sensor-based MIMO radar, an EMVS-MIMO radar can not only provides a two-dimensional (2D) direction finding of the targets but also offers 2D polarization parameter estimation, which may be important for detecting weak targets. In this paper, we investigate into multiple parameter estimations for a bistatic EMVS-MIMO radar in the presence of coherent targets, whose transmitting EMVS and receiving EMVS are placed in an arbitrary topology. Three tensor-aware spatial smoothing estimators are introduced. The core of the proposed estimators is to de-correlate the coherent targets via the spatial smoothing technique and then formulate the covariance matrix into a third-order parallel factor (PARAFAC) tensor. After the PARAFAC decomposition of the tensor, the factor matrices can be obtained. Thereafter, the 2D direction finding can be accomplished via the normalized vector cross-product technique. Finally, the 2D polarization parameter can be estimated via the least squares method. Unlike the state-of-the-art PARAFAC estimator, the proposed estimators are suitable for arbitrary sensor geometries, and they are robust to coherent targets as well as sensor position errors. In addition, they have better estimation performance than the current matrix-based estimators. Moreover, they are computationally efficient than the current subspace methods, especially in the presence of a large-scale sensor array. In addition, the proposed estimators are analyzed in detail. Numerical experiments coincide with our theoretical findings.

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“…Conventional MIMO array setups using non-uniform spacing do not have a straightforward design rule, so the setup is often determined using a genetic algorithm with different possible optimization goals: low sidelobe levels [4], channel capacity for communication systems [5], minimum beamwidth/maximum aperture [6], or a maximum angular range for unambiguous angle estimation in the azimuth angular range [7] or in 2-D [8].…”

mentioning

confidence: 99%

Performance Evaluation and Optimization of MIMO Radars Using Biomimetic Antenna Arrays

Dorsch¹,

Gruner²,

Klose³

et al. 2021

IEEE Trans. Microwave Theory Techn.

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The improvement of the angular resolution of radar sensors is one of the crucial goals of current radar research. A promising approach to achieve this goal is inspired by the ears of a fly called Ormia ochracea. The working principle was adapted for antennas, and the so-called biomimetic antenna arrays (BMAAs) aroused the interest of several research groups. In this work, BMAAs are incorporated into multiple-input multiple-output (MIMO) arrays, a very common approach of improving the angular resolution, to gain more degrees of freedom in array design. The MIMO BMAAs are modeled utilizing the effective biomimetic antenna distance, a fundamentally new measure introduced in this article to translate the special biomimetic phase progression into a spatial quantity. We present straightforward antenna configurations but also describe how a genetic algorithm can be utilized to optimize both antenna positions and BMAA parameters. The proposed arrays show various beneficial effects such as a wider angular range for unambiguous angle estimation or a narrower beamwidth. The impact of MIMO BMAAs on the angular resolution is thoroughly analyzed both theoretically and by radar measurements in the range of 77 GHz. The measurements confirm the modeling method very well and show a significant increase in the angular separability.

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2-D MIMO Radar: A Method for Array Performance Assessment and Design of a Planar Antenna Array

Cited by 43 publications

References 22 publications

System Performance of a 79 GHz High-Resolution 4D Imaging MIMO Radar With 1728 Virtual Channels

System Performance of a 79 GHz High-Resolution 4D Imaging MIMO Radar With 1728 Virtual Channels

PARAFAC Estimators for Coherent Targets in EMVS-MIMO Radar with Arbitrary Geometry

Performance Evaluation and Optimization of MIMO Radars Using Biomimetic Antenna Arrays

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