Antenna array in eWLB for 61 GHz FMCW radar

PourMousavi, M.; Wojnowski, Maciej; Agethen, Roman; Weigel, Robert; Hagelauer, Amelie

doi:10.1109/apmc.2013.6695129

Cited by 11 publications

(4 citation statements)

References 3 publications

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“…Despite popular technologies used for implementing gesture recognisers such as RGB [27,52,58] or infrared (IR) [11,15,21,53,54] cameras, RF-based solutions including radar [29,40], Wi-Fi [2,41,69], GSM [68], and RFID [14] offer several advantages. Above all, RF sensing technologies are insensitive to light, which usually affects camera and, especially, IR based solutions (both cannot be used in bright sunlight).…”

Section: Rf Sensing Technologiesmentioning

confidence: 99%

Solids on Soli

Pucihar

Attygalle

Kljun

et al. 2022

Proc. ACM Hum.-Comput. Interact.

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Gesture recognition with miniaturised radar sensors has received increasing attention as a novel interaction medium. The practical use of radar technology, however, often requires sensing through materials. Yet, it is still not well understood how the internal structure of materials impacts recognition performance. To tackle this challenge, we collected a large dataset of 14,090 radar recordings for 6 paradigmatic gesture classes sensed through a variety of everyday materials, performed by humans (6 materials) and a robot system (75 materials). Next, we developed a hybrid CNN+LSTM deep learning model and derived a robust indirect method to measure signal distortions, which we used to compile a comprehensive catalogue of materials for radar-based interaction. Among other findings, our experiments show that it is possible to estimate how different materials would affect gesture recognition performance of arbitrary classifiers by selecting just 3 reference materials. Our catalogue, software, models, data collection platform, and labeled datasets are publicly available.

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Section: Rf Sensing Technologiesmentioning

confidence: 99%

Solids on Soli

Pucihar

Attygalle

Kljun

et al. 2022

Proc. ACM Hum.-Comput. Interact.

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“…Regardless of popular technologies used for implementing gesture recognisers such as RGB [ 20 , 21 , 22 , 23 ] or infrared (IR) [ 24 , 25 , 26 , 27 , 28 ] cameras, Radio-frequency solutions including radar [ 29 , 30 ], Wi-Fi [ 31 , 32 , 33 ], GSM [ 34 ], and RFID [ 35 ] offer several advantages. Above all, RF sensing technologies are insensitive to light, which usually affects the camera and especially, IR-based solutions.…”

Section: Related Workmentioning

confidence: 99%

No Interface, No Problem: Gesture Recognition on Physical Objects Using Radar Sensing

Attygalle

Leiva

Kljun

et al. 2021

Sensors

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Physical objects are usually not designed with interaction capabilities to control digital content. Nevertheless, they provide an untapped source for interactions since every object could be used to control our digital lives. We call this the missing interface problem: Instead of embedding computational capacity into objects, we can simply detect users’ gestures on them. However, gesture detection on such unmodified objects has to date been limited in the spatial resolution and detection fidelity. To address this gap, we conducted research on micro-gesture detection on physical objects based on Google Soli’s radar sensor. We introduced two novel deep learning architectures to process range Doppler images, namely a three-dimensional convolutional neural network (Conv3D) and a spectrogram-based ConvNet. The results show that our architectures enable robust on-object gesture detection, achieving an accuracy of approximately 94% for a five-gesture set, surpassing previous state-of-the-art performance results by up to 39%. We also showed that the decibel (dB) Doppler range setting has a significant effect on system performance, as accuracy can vary up to 20% across the dB range. As a result, we provide guidelines on how to best calibrate the radar sensor.

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“…Different FO antennas and antenna arrays are presented at 28 GHz [4,5], 60 GHz [6][7][8][9][10][11], 77 GHz [12][13][14][15], and above 100 GHz [16] where most of the designs use either double molding layers [4,10,12], multiple re-distribution layers (RDL) [5], metallization on top mold [4,5,7,9,10,12], through mold VIAs [4,5,7], or airgap in the mold [6]. These variations make the package complex and thus cost-ineffective.…”

Section: Introductionmentioning

confidence: 99%

“…These variations make the package complex and thus cost-ineffective. Some of the designs implement only a single antenna elements despite the small form factors at 60 and 77 GHz [8,13,14]. In this work, a TX and an RX antenna arrays are presented that cover the 26 and 28 GHz bands n258 (24.250-27.5 GHz) and n257 (26.5-29.5 GHz).…”

Section: Introductionmentioning

confidence: 99%

28 GHz compact dipole antenna array integrated in fan-out eWLB package

Aziz

Öjefors

et al. 2022

Int. J. Microw. Wireless Technol.

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In this paper, we present a 28 GHz antenna array in package which covers the n257 and n258 frequency bands designated for 5G applications. The dipole antenna array is placed on one of the two re-distribution layers in the fan-out eWLB (embedded Wafer Level Ball Grid Array) package. For TX and RX, separate but identical antenna arrays are placed on each side of the die. The paper presents a novel horn-shaped heatsink which not only dissipates the heat, but also improves the radiation performance. The four-elements dipole array has the impedance bandwidth of almost 6 GHz (24–30 GHz) and shows a maximum realized gain of 9.5 dBi. Beam-steering in ± 35 deg is achieved in the azimuth plane (H-plane) by providing different phases to the dipoles through the chip. The measurements nicely agree with the simulation results.

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Antenna array in eWLB for 61 GHz FMCW radar

Cited by 11 publications

References 3 publications

Solids on Soli

Solids on Soli

No Interface, No Problem: Gesture Recognition on Physical Objects Using Radar Sensing

28 GHz compact dipole antenna array integrated in fan-out eWLB package

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