9.2 A 192-Virtual-Receiver 77/79GHz GMSK Code-Domain MIMO Radar System-on-Chip

Giannini, Vito; Goldenberg, M.; Eshraghi, A.; Maligeorgos, James; Lim, Lysander; Lobo, Ryan; Welland, Dave; Chow, Chung-Kai; Dornbusch, Andrew; Dupuis, T.; Vaz, Struan; Rush, Fred; Bassett, Paul; Kim, Hong; Maher, Monier; Schmid, Otto; Davis, C.H.; Hegde, Maruti

doi:10.1109/isscc.2019.8662386

Cited by 75 publications

(39 citation statements)

References 3 publications

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“…Due to a wide variety of automotive applications with different resolution requirements, varying number of antenna elements are used in different automotive radars [49]- [51]. Therefore, the TX and RX antenna arrays are considered to be uniform linear arrays with 17, 31, or 257 elements.…”

Section: Numerical Resultsmentioning

confidence: 99%

“…Therefore, the TX and RX antenna arrays are considered to be uniform linear arrays with 17, 31, or 257 elements. Since the recent automotive radar imaging trend is moving towards higher resolution sensing needed for futuristic autonomous driving applications [49], [51], [52], we used the large antenna array size of 257 to meet the best-case resolution requirement. Additionally, a large number of antenna arrays will enable enhanced JCR combined waveform-beamforming design with superior JCR performance.…”

Section: Numerical Resultsmentioning

confidence: 99%

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Adaptive and Fast Combined Waveform-Beamforming Design for MMWave Automotive Joint Communication-Radar

Kumari

Myers

Heath

2021

IEEE J. Sel. Top. Signal Process.

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Millimeter-wave (mmWave) joint communicationradar (JCR) will enable high data rate communication and highresolution radar sensing for applications such as autonomous driving. Prior JCR systems that are based on the mmWave communications hardware, however, suffer from a limited angular field-of-view and low estimation accuracy for radars due to the employed directional communication beam. In this paper, we propose an adaptive and fast combined waveform-beamforming design for the mmWave automotive JCR with a phased-array architecture that permits a trade-off between communication and radar performances. To rapidly estimate the mmWave automotive radar channel in the Doppler-angle domain with a wide field-of-view, our JCR design employs circulant shifts of the transmit beamformer to acquire radar channel measurements and uses two-dimensional compressed sensing (CS) in the spacetime dimension. We optimize these circulant shifts to minimize the coherence of the CS matrix, under the space-time sampling constraints in our problem. We evaluate the JCR performance trade-offs using a normalized mean square error (MSE) metric for radar estimation and a distortion MSE metric for data communication, which is analogous to the distortion metric in the rate-distortion theory. Additionally, we develop a MSEbased weighted average optimization problem for the adaptive JCR combined waveform-beamforming design. Numerical results demonstrate that our proposed JCR design enables the estimation of short-and medium-range radar channels in the Doppler-angle domain with a low normalized MSE, at the expense of a small degradation in the communication distortion MSE.

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Section: Numerical Resultsmentioning

confidence: 99%

Section: Numerical Resultsmentioning

confidence: 99%

Adaptive and Fast Combined Waveform-Beamforming Design for MMWave Automotive Joint Communication-Radar

Kumari

Myers

Heath

2021

IEEE J. Sel. Top. Signal Process.

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“…Other vendors (e.g. Uhnder) have recently unveiled a new, all-digital phase modulated continuous wave (PMCW) radar chip capable of synthesizing multiple-input and multiple-output (MIMO) radar capability with 192 virtual receivers, thereby obtaining very high angular resolution [5]. Such high-resolution radars perform similar functions to lidars, i.e., generate dense point-cloud maps from object returns in the vicinity at a fraction of the cost of lidar systems.…”

Section: Introductionmentioning

confidence: 99%

“…In the calculation of velocity resolution, λ is the wavelength of transmitted signal, Tc is the duration of one chirp, Tc = 1 Ncf F 4. In the calculation of angle resolution, N Rx is the number of elements of receiver array (including the MIMO virtual receiver), d is the separation between receive antenna pair 5. The operating velocity range is (−Vmax, Vmax).…”

mentioning

confidence: 99%

RAMP-CNN: A Novel Neural Network for Enhanced Automotive Radar Object Recognition

et al. 2021

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Millimeter-wave (mmW) radars are being increasingly integrated into commercial vehicles to support new advanced driver-assistance systems (ADAS) by enabling robust and high-performance object detection, localization, as well as recognition-a key component of new environmental perception. In this paper, we propose a novel radar multiple-perspectives convolutional neural network (RAMP-CNN) that extracts location and class of objects based on further processing of the rangevelocity-angle (RVA) heatmap sequences. To bypass the complexity of 4D convolutional neural networks (NN), we propose to combine several lower-dimension NN models within our RAMP-CNN model that nonetheless approaches the performance upperbound with lower complexity. The extensive experiments show that the proposed RAMP-CNN model achieves better average recall (AR) and average precision (AP) than prior works in all testing scenarios (see Table.III). Besides, the RAMP-CNN model is validated to work robustly under the nighttime, which enables low-cost radars as a potential substitute for pure optical sensing under severe conditions.

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“…However, recent market is moving toward CMOS technology that shows a higher level of integration at a more competitive price than SiGe technology [1], [2]. Ad-ditionally, CMOS radar transceiver designs are continuously progressing to implement high-resolution imaging radars to support complete autonomous driving [3]. In addition to mm-wave semiconductor technologies, mm-wave packaging technology is also essential for the overall performance, cost, and yield of a product.…”

Section: Introductionmentioning

confidence: 99%

79 GHz Active Array FMCW Radar System on Low-Cost FR-4 Substrates

Kim

Shin

et al. 2020

IEEE Access

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This work, for the first time to our best knowledge, presents a W-band multi-channel frequency-modulated continuous-wave (FMCW) radar system on low-cost FR-4 substrates. A center-fed patch array antenna on an FR-4 substrate can achieve a maximum gain of 10.8 dBi. It is enabled by aperture coupled feeding using an on-chip feeder implemented on a CMOS radar transmitter (Tx) and receiver (Rx). The proposed radar system consists of one Tx and four Rx channels placed in the back cavity of a microstrip array antenna like an active array antenna system. Additionally, Tx and Rx chipsets include a wideband frequency multiplier with high multiplication ratio of 63, making it easy to distribute reference FMCW waveform synthesized at a very low frequency about 1.25 GHz for 79 GHz output using direct digital synthesis (DDS). Extending the number of channels and implementing various waveforms can be easily accomplished with very good phase noise. The functionality of the proposed radar system on low-cost substrates is confirmed by distance and angle measurements.

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9.2 A 192-Virtual-Receiver 77/79GHz GMSK Code-Domain MIMO Radar System-on-Chip

Cited by 75 publications

References 3 publications

Adaptive and Fast Combined Waveform-Beamforming Design for MMWave Automotive Joint Communication-Radar

Adaptive and Fast Combined Waveform-Beamforming Design for MMWave Automotive Joint Communication-Radar

RAMP-CNN: A Novel Neural Network for Enhanced Automotive Radar Object Recognition

79 GHz Active Array FMCW Radar System on Low-Cost FR-4 Substrates

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