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公开(公告)号：US10241581B2
公开(公告)日：2019-03-26
申请号：US15142689
申请日：2016-04-29
Inventor： Jaime Lien , Erik M. Olson , Patrick M. Amihood , Ivan Poupyrev
Abstract: This document describes techniques for radio frequency (RF) based micro-motion tracking. These techniques enable even millimeter-scale hand motions to be tracked. To do so, radar signals are used from radar systems that, with conventional techniques, would only permit resolutions of a centimeter or more.
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公开(公告)号：US20160320854A1
公开(公告)日：2016-11-03
申请号：US15142829
申请日：2016-04-29
Inventor： Jaime Lien , Patrick M. Amihood , Ivan Poupyrev
CPC classification number: G06F3/017 , G01S7/292 , G01S7/354 , G01S7/415 , G01S13/08 , G01S13/58 , G01S13/88 , G06F3/011
Abstract: This document describes techniques and devices for type-agnostic radio frequency (RF) signal representations. These techniques and devices enable use of multiple different types of radar systems and fields through type-agnostic RF signal representations. By so doing, recognition and application-layer analysis can be independent of various radar parameters that differ between different radar systems and fields.
Abstract translation: 本文档描述了用于类型无关射频（RF）信号表示的技术和设备。 这些技术和设备能够通过类型无关的RF信号表示来使用多种不同类型的雷达系统和领域。 通过这样做，识别和应用层分析可以独立于不同雷达系统和领域之间不同的各种雷达参数。
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公开(公告)号：US10401490B2
公开(公告)日：2019-09-03
申请号：US15286512
申请日：2016-10-05
Applicant: Google Inc.
Inventor： Nicholas Edward Gillian , Carsten C. Schwesig , Jaime Lien , Patrick M. Amihood , Ivan Poupyrev
IPC: G01S13/86 , G06F3/01 , G06K9/62 , G01S13/93 , G01S13/90 , G01S7/41 , G01S13/56 , H04Q9/00 , G06K9/00 , G06F16/245 , G06F21/62 , G08C17/02 , G06F1/16 , G06F3/0484 , G01S19/42 , G06F3/0346 , G06F3/16 , G06T7/00
Abstract: This document describes apparatuses and techniques for radar-enabled sensor fusion. In some aspects, a radar field is provided and reflection signals that correspond to a target in the radar field are received. The reflection signals are transformed to provide radar data, from which a radar feature indicating a physical characteristic of the target is extracted. Based on the radar features, a sensor is activated to provide supplemental sensor data associated with the physical characteristic. The radar feature is then augmented with the supplemental sensor data to enhance the radar feature, such as by increasing an accuracy or resolution of the radar feature. By so doing, performance of sensor-based applications, which rely on the enhanced radar features, can be improved.
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公开(公告)号：US10540001B1
公开(公告)日：2020-01-21
申请号：US15287253
申请日：2016-10-06
Applicant: Google Inc.
Inventor： Ivan Poupyrev , Patrick M. Amihood
IPC: G06F3/01 , G06F3/0481
Abstract: This document describes techniques for fine-motion virtual-reality or augmented-reality control using radar. These techniques enable small motions and displacements to be tracked, even in the millimeter or sub-millimeter scale, for user control actions even when those actions are small, fast, or obscured due to darkness or varying light. Further, these techniques enable fine resolution and real-time control, unlike conventional RF-tracking or optical-tracking techniques.
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公开(公告)号：US11080556B1
公开(公告)日：2021-08-03
申请号：US15287359
申请日：2016-10-06
Applicant: Google Inc.
Inventor： Nicholas Edward Gillian , Jaime Lien , Patrick M. Amihood , Ivan Poupyrev
Abstract: Various embodiments dynamically learn user-customizable input gestures. A user can transition a radar-based gesture detection system into a gesture-learning mode. In turn, the radar-based gesture detection system emits a radar field configured to detect a gesture new to the radar-based gesture detection system. The radar-based gesture detection system receives incoming radio frequency (RF) signals generated by the outgoing RF signal reflecting off the gesture, and analyzes the incoming RF signals to learn one or more identifying characteristics about the gesture. Upon learning the identifying characteristics, the radar-based gesture detection system reconfigures a corresponding input identification system to detect the gesture when the one or more identifying characteristics are next identified, and transitions out of the gesture-learning mode.
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Patent Agency Ranking
公开(公告)号：US10310620B2
公开(公告)日：2019-06-04
申请号：US15142829
申请日：2016-04-29
Inventor： Jaime Lien , Patrick M. Amihood , Ivan Poupyrev
Abstract: This document describes techniques and devices for type-agnostic radio frequency (RF) signal representations. These techniques and devices enable use of multiple different types of radar systems and fields through type-agnostic RF signal representations. By so doing, recognition and application-layer analysis can be independent of various radar parameters that differ between different radar systems and fields.
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公开(公告)号：US10300370B1
公开(公告)日：2019-05-28
申请号：US15286495
申请日：2016-10-05
Applicant: Google Inc.
Inventor： Patrick M. Amihood , Ivan Poupyrev
Abstract: Techniques are described herein that enable advanced gaming and virtual reality control using radar. These techniques enable small motions and displacements to be tracked, even in the millimeter or submillimeter scale, for user control actions even when those actions are optically occluded or obscured.
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公开(公告)号：US10222469B1
公开(公告)日：2019-03-05
申请号：US15287200
申请日：2016-10-06
Applicant: Google Inc.
Inventor： Nicholas Edward Gillian , Carsten C. Schwesig , Jaime Lien , Patrick M. Amihood , Ivan Poupyrev
Abstract: This document describes apparatuses and techniques for radar-based contextual sensing. In some aspects, a radar sensor of a device is activated to obtain radar data for a space of interest. Three-dimensional (3D) radar features are extracted from the radar data and positional data is received from sensors. Based on the positional data, spatial relation of the 3D radar features is determined to generate a set of 3D landmarks for the space. This set of 3D landmarks is then compared with known 3D context models to identify a 3D context model that matches the 3D landmarks. Based on a matching 3D context model, a context for the space is retrieved and used to configure contextual settings of the device. By so doing, contextual settings of the device be dynamically configured to address changes in context or for different device environments.
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公开(公告)号：US10310621B1
公开(公告)日：2019-06-04
申请号：US15286837
申请日：2016-10-06
Applicant: Google Inc.
Inventor： Jaime Lien , Patrick M. Amihood , Hakim Kader Bhai Raja
Abstract: This document describes techniques using, and devices embodying, radar gesture sensing using existing data protocols. These techniques and devices enable transmitting data according to an existing data protocol, modulating the data on a radar field to transmit to another device, and sensing user gestures by analyzing reflections of portions of transmitted data by the transmitting or receiving device. Techniques are also described to filter received signals based on addressing information in the transmitted data to limit gesture recognition at a receiving device to transmitting devices known to the receiver.
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公开(公告)号：US20170097413A1
公开(公告)日：2017-04-06
申请号：US15286512
申请日：2016-10-05
Applicant: Google Inc.
Inventor： Nicholas Edward Gillian , Carsten C. Schwesig , Jaime Lien , Patrick M. Amihood , Ivan Poupyrev
CPC classification number: G06F3/017 , A63F13/21 , A63F13/24 , A63F2300/8082 , G01S7/41 , G01S7/415 , G01S13/56 , G01S13/66 , G01S13/86 , G01S13/865 , G01S13/867 , G01S13/90 , G01S13/931 , G01S19/42 , G06F1/163 , G06F3/011 , G06F3/0346 , G06F3/0484 , G06F3/165 , G06F16/245 , G06F21/6245 , G06F2203/0384 , G06K9/00201 , G06K9/6288 , G06K9/629 , G06T7/75 , G08C17/02 , G08C2201/93 , H04Q9/00 , H04Q2209/883
Abstract: This document describes apparatuses and techniques for radar-enabled sensor fusion. In some aspects, a radar field is provided and reflection signals that correspond to a target in the radar field are received. The reflection signals are transformed to provide radar data, from which a radar feature indicating a physical characteristic of the target is extracted. Based on the radar features, a sensor is activated to provide supplemental sensor data associated with the physical characteristic. The radar feature is then augmented with the supplemental sensor data to enhance the radar feature, such as by increasing an accuracy or resolution of the radar feature. By so doing, performance of sensor-based applications, which rely on the enhanced radar features, can be improved.
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