IP Library › Granted Patent US 12,553,987
Granted Patent B2
US 12,553,987 · App. 18/558,861 · Granted Feb 17, 2026

Ultrawideband localization systems and methods for computing user interface

Inventors: Ashutosh Dhekne (Marietta, GA); Yifeng Cao (Atlanta, GA); Mostafa H. Ammar (Atlanta, GA)
Assignee: Georgia Tech Research Corporation
G01S5/06G01S5/021G01S5/02216G01S5/0247G01S5/0264
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 12,553,987
App. No.
18/558,861
Granted
Feb 17, 2026
Kind
B2
Abstract

An exemplary system and method are disclosed for a handheld or hand-enclosed instrument configured with ultra-wideband localization using unidirectional messaging protocol based on time difference of arrival (TDoA) measurements that can be used as inputs, in a realtime control loop, to a software application that uses the handheld or hand-enclosed instrument as an input user interface. The handheld or hand-enclosed instrument can be readily employed for UI in large work areas (e.g., 2D), such as a whiteboard or wallboard, with sub-millimeter resolution and sub-millisecond latency. The handheld or hand-enclosed instrument can be readily employed in a UI device for non-conforming 3D workspace such as a sculpting instrument, in hand-enclosed game interface, as a remote medical instrument, among others described herein.

Claims (78)

1 . A system comprising:

a localization device configured to interface to a handheld or hand-enclosed instrument comprising an instrument body and an ultra-wide band antenna and communication interface), the localization device comprising:

a plurality of antennas operably connected to an ultra-wide band controller to receive a plurality of unidirectional ultra-wide band signals from the ultra-wide band antenna of the handheld or hand-enclosed instrument; and

the controller comprising a processor unit or logic circuit, the processor unit or logic circuit being configured to:

measure a plurality of time measurements and one or more phase measurements of a plurality of signals received by the plurality of antennas from the ultra-wide band antenna of the handheld or hand-enclosed instrument;

determine a time-difference of arrival (TDOA) measurements, or values derived therefrom, using the plurality of measured time measurements and the one or more measured phase measurements; and

determine at least one localization measurement value of the ultra-wide band antenna of the handheld or hand-enclosed instrument based on the TDOA measurements, or values derived therefrom;

wherein at least the at least one localization measurement value or a parameter derived therefrom is employed as one or more inputs, in a real-time control loop, to a software application that uses the handheld or hand-enclosed instrument as an input user interface.

2 . The system of claim 1 , further comprising:

an ultra-wide band antenna and communication interface; and

a controller, the controller comprising a second processor unit and a second memory having instructions stored thereon, wherein execution of the instructions by the second processor cause the second processor to:

measure a plurality of time measurements and one or more phase measurements of a plurality of unidirectional signals received by the ultra-wide band antenna from a plurality of antennas of a base station system;

determine time-difference of arrival (TDOA) measurements, or values derived therefrom, using the plurality of measured time measurements and the one or more measured phase measurements; and

determine at least one localization measurement value of the ultra-wide band antenna of the handheld or hand-enclosed instrument based on the TDOA measurements, or values derived therefrom;

wherein at least the at least one localization measurement value or a parameter derived therefrom is employed as one or more inputs, in a real-time control loop, to a software application that uses the handheld or hand-enclosed instrument as an input user interface.

3 . The system of claim 1 ,

wherein two or more of the plurality of antennas are connected to the controller through a corresponding set of delay-adjusting connections, including a first delay-adjusting connection and a second delay-adjusting connection,

wherein the first delay-adjusting connection comprises a first cable length and/or electronic component that add a first time or phase delay to (i) a first time measurement of the plurality of time measurements and/or a first phase measurement of the one or more phase measurements,

wherein the second delay-adjusting connection comprises a second cable length and/or electronic component that add a second time or phase delay to (i) a second time measurement of the plurality of time measurements and/or a second phase measurement of the one or more phase measurements, and

wherein the first time or phase delay and the second time or phase delay are different.

4 . The system of claim 3 , wherein the first delay-adjusting connection has a first signal amplitude attenuation characteristic, wherein the second delay-adjusting connection has a second signal amplitude attenuation characteristic, wherein the first signal amplitude attenuation characteristic is different from the second signal amplitude attenuation characteristic.

5 . The system of claim 1 , wherein the plurality of unidirectional ultra-wide band signals comprises a plurality of RF pulses, wherein the measure of the plurality of time measurements and the one or more phase measurements of a plurality of unidirectional signals includes:

interpolating a portion of the plurality of RF pulses associated with a peak RF pulse to generate a plurality of interpolated signals; and

determining a maximum measure of the plurality of interpolated signals as the plurality of time measurements and the one or more phase measurements.

6 . The system of claim 1 ,

wherein the handheld or hand-enclosed instrument comprises an orientation sensor, and

wherein the processor unit is further configured by instructions or circuitry to:

receive orientation measurements, or values derived therefrom, from the orientation sensor;

determine at least one orientation measurement value based on the orientation measurements; and

determine at least one second localization measurement value of a landmark of the handheld or hand-enclosed instrument via a pre-defined transform operator of

(i) the at least one orientation measurement value and

(ii) at least one of the (a) TDOA measurements, or values derived therefrom or (b) the at least one localization measurement value of the ultra-wide band antenna,

wherein the at least one second localization measurement value or a parameter derived therefrom is employed as one or more inputs, in the real-time control loop, to a software application that uses the handheld or hand-enclosed instrument as an input user interface.

7 . The system of claim 1 ,

wherein the handheld or hand-enclosed instrument comprises an orientation sensor and a contact sensor, and

wherein the processor unit is further configured by instructions or circuitry to:

receive orientation measurements, or values derived therefrom, from the orientation sensor;

receive contact measurements, or values derived therefrom, from the contact sensor;

determine at least one contact measurement value based on the contact measurements; and

determine at least one second localization measurement value of a landmark of the handheld or hand-enclosed instrument via a pre-defined transform operator using:

(i) the at least one orientation measurement value and

(ii) at least one of the (a) TDOA measurements, or values derived therefrom or (b) the at least one localization measurement value of the ultra-wide band antenna,

wherein at least (i) the at least one second localization measurement value or a parameter derived therefrom and (ii) the at least one contact measurement value are concurrently employed as one or more inputs, in the real-time control loop, to a software application that uses the handheld or hand-enclosed instrument as an input user interface.

8 . The system of claim 1 ,

wherein the handheld or hand-enclosed instrument comprises an orientation sensor, and

wherein the processor unit is further configured by instructions or circuitry to:

receive orientation measurements, or values derived therefrom, from the orientation sensor; and

determine at least one orientation measurement value based on the orientation measurements;

wherein at least (i) the at least one localization measurement value or a parameter derived therefrom and (ii) the at least one orientation measurement value are concurrently employed as one or more inputs, in the real-time control loop, to a software application that uses the handheld or hand-enclosed instrument as an input user interface.

9 . The system of claim 1 ,

wherein the handheld or hand-enclosed instrument comprises an orientation sensor and a contact sensor, and

wherein the processor unit is further configured by instructions or circuitry to:

receive orientation measurements, or values derived therefrom, from the orientation sensor;

receive contact measurements, or values derived therefrom, from the contact sensor; and

determine at least one contact measurement value based on the contact measurements; and

determine at least one orientation measurement value based on the orientation measurements;

wherein at least (i) the at least one localization measurement value or a parameter derived therefrom, (ii) the at least one orientation measurement value, and (iii) the at least one contact measurement value are concurrently employed as one or more inputs, in the real-time control loop, to a software application that uses the handheld or hand-enclosed instrument as an input user interface.

10 . The system of claim 6 , wherein the controller is configured to maintain a first tracking parameter of the plurality of time measurements and/or the one or more phase measurements, and wherein the controller is further configured to re-calibrate and/or adjust the first tracking parameter via a fusion operation using at least outputs of the orientation sensor.

11 . The system of claim 10 , wherein the controller is configured to maintain a second tracking parameter of the orientation measurements, and wherein the controller is further configured to re-calibrate and/or adjust the second tracking parameter via the fusion operation using at least the first tracking parameter of the plurality of time measurements and/or the one or more phase measurements.

12 . The system of claim 7 , wherein the contact sensor comprises a pressure sensor positioned on a surface of the instrument body to be held by a user, and wherein contact is determined based on an elevated pressure being sensed by the pressure sensor.

13 . The system of claim 7 , wherein the contact sensor comprises a laser rangefinder or a photodiode assembly configured to interrogate a surface to determine when contact is made with said surface.

14 . The system of claim 7 , wherein (i) the orientation measurements, or values derived therefrom, and/or (ii) the contact measurements, or values derived therefrom, are embedded and/or encoded in the plurality of signals.

15 . The system of claim 7 , wherein (i) the orientation measurements, or values derived therefrom, and/or (ii) the contact measurements, or values derived therefrom, are transmitted through (i) a second communication channel in at least one of the plurality of ultra-wide band signals or (ii) a separate second communication channel associated with the localization device.

16 . The system of claim 15 , wherein the localization device further comprises a second ultra-wide band controller or a RF controller configured to receive the orientation measurements, or values derived therefrom, and/or the contact measurements, or values derived therefrom, from the handheld or hand-enclosed instrument.

17 . The system of claim 1 , wherein the handheld or hand-enclosed instrument is configured as a writing instrument, the system further comprising a writing surface apparatus having a dimension greater than 2 feet by 3 feet, wherein the plurality of antennas are positioned at a first position, a second position, and a third position on or near the writing surface apparatus.

18 . The system of claim 6 , wherein the handheld or hand-enclosed instrument is configured as a sculpting instrument, wherein the plurality of antennas are fixably positioned at a first position, a second position, and a third position around a surface of a workpiece, and wherein the localization device is configured to map or operate upon a three-dimensional surface position of the workpiece using (i) the at least one localization measurement value or (ii) the at least one second localization measurement value.

19 . A non-transitory computer-readable medium having instructions stored thereon to perform localization of a hand-held or hand-enclosed instrument, wherein execution of the instructions by a processor causes the processor to:

receive a plurality of time measurements and one or more phase measurements of a plurality of signals received by a plurality of antennas from an ultra-wide band antenna of a handheld or hand-enclosed instrument;

determine a time-difference of arrival (TDOA) measurements, or values derived therefrom, using the plurality of measured time measurements and the one or more measured phase measurements; and

determine at least one localization measurement value of the ultra-wide band antenna of the handheld or hand-enclosed instrument based on the TDOA measurements, or values derived therefrom;

wherein the at least one localization measurement value or a parameter derived therefrom is employed, in a real-time control loop, as one or more inputs to a software application that uses the handheld or hand-enclosed instrument as an input user interface.

20 . A method comprising:

transmitting by a first device one or more ultra-wide band signals; and

receiving by a second device the transmitted one or more ultra-wide band signals;

measuring, via analog and/or digital circuitries, a plurality of time measurements and one or more phase measurements of a plurality of signals received by a plurality of antennas from a ultra-wide band antenna of a handheld or hand-enclosed instrument;

determining, by a processor, a time-difference of arrival (TDOA) measurements, or values derived therefrom, using the plurality of measured time measurements and the one or more measured phase measurements; and

determining, by the processor, at least one localization measurement value of the ultra-wide band antenna of the handheld or hand-enclosed instrument based on the TDOA measurements, or values derived therefrom;

wherein at least the at least one localization measurement value or a parameter derived therefrom is employed as one or more inputs, in a real-time control loop, to a software application that uses the handheld or hand-enclosed instrument as an input user interface.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 13, 2023
From: DHEKNE, ASHUTOSH; CAO, YIFENG; AMMAR, MOSTAFA H.
To: GEORGIA TECH RESEARCH CORPORATION
Reel/Frame 065537/0381 →
Continuity (2)
Provisional Application 63183826 · May 4, 2021
Related Publication 20240230831A1 · Jul 11, 2024
References Cited (72)
US 20100109842A1 · Patel · 2010 [cited by examiner]
US 20140070958A1 · Foo · 2014 [cited by examiner]
US 20160242135A1 · McLaughlin · 2016 [cited by examiner]
US 20190076203A1 · Ang · 2019 [cited by examiner]
International Search Report and Written Opinion received in PCT/US2022/027435 mailed Jul. 14, 2022. [cited by applicant]
Khan et at, “Hand-based gesture recognition for vehicular applications using IR-UWB radar.” Sensors 17.4 (2017): 833. Apr. 11, 2017 (Apr. 11, 2017) Retrieved on Jun. 19, 2022 (Jun. 19, 2022) from <https://www.mdpi.com/1… [cited by applicant]
Wang et at. “Prototyping and experimental comparison of iR-UWB based high precision localization technologies.” 2015 IEEE 12th Intl Conf on Ubiquitous Intelligence and Computing and 2015 IEEE 12th Intl Conf on Autonomic… [cited by applicant]
Wang et al., “MoLe: Motion leaks through smartwatch sensors.” Proceedings of the 21st annual international conference on mobile computing and networking (2015): 1-12. [cited by applicant]
Wang et al., “No need to war-drive: Unsupervised indoor localization.” Proceedings of the 10th international conference on Mobile systems, applications, and services (2012): 197-210. [cited by applicant]
Wang et al., “RF-IDraw: Virtual touch screen in the air using RF signals.” ACM SIGCOMM Computer Communication Review 44.4 (2014): 235-246. [cited by applicant]
Wei et al., “mtrack: High-precision passive tracking using millimeter wave radios.” Proceedings of the 21st Annual International Conference on Mobile Computing and Networking (2015): 1-13. [cited by applicant]
Wu et al., “FingerDraw: Sub-wavelength level finger motion tracking with WiFi signals.” Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 4.1 (2020): 1-28. [cited by applicant]
Xiao et al., “MilliBack: Real-time plug-n-play millimeter level tracking using wireless backscattering.” Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 3.3 (2019): 1-23. [cited by applicant]
Xu et al., “Finger-writing with smartwatch: A case for finger and hand gesture recognition using smartwatch.” Proceedings of the 16th International Workshop on Mobile Computing Systems and Applications (2015): 9-14. [cited by applicant]
Xu et al., “SCPL: Indoor device-free multi-subject counting and localization using radio signal strength.” Proceedings of the 12th international conference on Information Processing in Sensor Networks (2013): 1-12. [cited by applicant]
Yang et al., “Tagoram: Real-time tracking of mobile RFID tags to high precision using COTS devices.” Proceedings of the 20th annual international conference on Mobile computing and networking (2014): 1-12. [cited by applicant]
Yean et al., “Algorithm for 3D orientation estimation based on Kalman Filter and Gradient Descent.” 2016 IEEE 7th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON). IEEE (2016): 1-7. [cited by applicant]
Yin et al., “Learning to recognize handwriting input with acoustic features.” Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 4.2 (2020): 1-26. [cited by applicant]
Yu et al., “Mobile devices based eavesdropping of handwriting.” IEEE Transactions on Mobile Computing 19.7 (2019): 1-14. [cited by applicant]
Yun et al., “Strata: Fine-grained acoustic-based device-free tracking.” Proceedings of the 15th annual international conference on mobile systems, applications, and services (2017): 1-14. [cited by applicant]
Yun et al., “Turning a mobile device into a mouse in the air.” Proceedings of the 13th Annual International Conference on Mobile Systems, Applications, and Services (2015): 1-15. [cited by applicant]
Zhou et al., “EchoPrint: Two-factor authentication using acoustics and vision on smartphones.” Proceedings of the 24th Annual International Conference on Mobile Computing and Networking (2018): 321-336. [cited by applicant]
Adib et al., “3D tracking via body radio reflections.” 11th USENIX Symposium on Networked Systems Design and Implementation (NSDI 14). (2014): 316-329. [cited by applicant]
Adib et al., “See through walls with WiFi!.” Proceedings of the ACM SIGCOMM 2013 conference on SIGCOMM (2013): 75-86. [cited by applicant]
AN5019, “Magnetic calibration algorithms.” NXP Semiconductors. https://www.nxp.com/docs/en/application-note/AN5019.pdf (2016): 1-33. [cited by applicant]
Anderson et al., “Nearly one-in-five teens can't always finish their homework because of the digital divide.” Pew Research Center. https://www.pewresearch.org/fact-tank/2018/10/26/ Oct. 2018, 1-6. [cited by applicant]
Apple, “Dream it up. Jot it down.” Apple Pencil. https://www.apple.com/apple-pencil/ (2018): 1-12. [cited by applicant]
Bai et al., “Acoustic-based sensing and applications: A survey.” Computer Networks 181 (2020): 107447, 1-23. [cited by applicant]
Boxlight Corporation, “Mimiocapture ink recorder datasheet.” Boxlight. https://mimio.boxlight.com/wp-content/uploads/2017/03/MimioCapture_SellSheet.pdf (2016): 1-2. [cited by applicant]
Cao et al., “6Fit-A-part: a protocol for physical distancing on a custom wearable device.” 2020 IEEE 28th International Conference on Network Protocols (ICNP). IEEE (2020): 1-12. [cited by applicant]
Cao et al., “Earphonetrack: involving earphones into the ecosystem of acoustic motion tracking.” Proceedings of the 18th Conference on Embedded Networked Sensor Systems (2020): 1-14. [cited by applicant]
Decawave, “Decawave user manual.” Decawave. https://www.decawave.com/sites/default/files/ resources/dw1000_user_manual_2.11.pdf (2017). [cited by applicant]
Decawave, “Transmit power calibration and management.” Decawave. https://www.decawave.com/wp-content/uploads/2019/07/APS023_Part- 1_Transmit_Power_Calibration_Management.pdf (2019). [cited by applicant]
Dhekne et al., “TrackIO: Tracking First Responders {Inside-Out}.” 16th USENIX Symposium on Networked Systems Design and Implementation (NSDI 19). (2019): 750-764. [cited by applicant]
Feigl et al., “RNN-aided human velocity estimation from a single IMU.” Sensors 20.13 (2020): 3656, 1-30. [cited by applicant]
FT Series, “4-wire analog resistive touch screen datasheet.” Digikey. https://media.digikey.com/pdf/Data\%20Sheets/NKK\%20PDFs/FT_Series_4-Wire_Ds_Oct_2017.pdf (2017). [cited by applicant]
Gowda et al., “Bringing IoT to sports analytics.” 14th USENIX Symposium on Networked Systems Design and Implementation (NSDI 17). (2017): 498-514. [cited by applicant]
Gowda et al., “Tracking drone orientation with multiple GPS receivers.” Proceedings of the 22nd annual international conference on mobile computing and networking (2016): 280-293. [cited by applicant]
Großwindhager et al., “SALMA: UWB-based single-anchor localization system using multipath assistance.” Proceedings of the 16th ACM Conference on Embedded Networked Sensor Systems (2018): 1-13. [cited by applicant]
Guo et al., “The soft iron and hard iron calibration method using extended Kalman filter for attitude and heading reference system.” 2008 IEEE/ION Position, Location and Navigation Symposium. IEEE (2008): 1167-1174. [cited by applicant]
Gutierrez et al., “IEEE 802.15. 4 low-rate wireless personal area networks: Enabling wireless sensor networks.” IEEE Standards Office (2003). [cited by applicant]
Hemingway et al., “Perspectives on Euler angle singularities, gimbal lock, and the orthogonality of applied forces and applied moments.” Multibody system dynamics 44 (2018): 31-56. [cited by applicant]
Ho et al., “An accurate algebraic solution for moving source location using TDOA and FDOA measurements.” IEEE Transactions on Signal Processing 52.9 (2004): 2452-2463. [cited by applicant]
Ho et al., “Step-detection and adaptive step-length estimation for pedestrian dead-reckoning at various walking speeds using a smartphone.” Sensors 16.9 (2016): 1423, 1-13. [cited by applicant]
Hongzhao, “60 GHz RSS localization with omni-directional and horn antennas.” ScholarBank@NUS Repository (2010). [cited by applicant]
Howard et al., “A review of current ultrasound exposure limits.” The Journal of Occupational Health and Safety of Australia and New Zealand 21.3 (2005): 1-10. [cited by applicant]
Huang et al., “Shake and walk: Acoustic direction finding and fine-grained indoor localization using smartphones.” IEEE INFOCOM 2014—IEEE Conference on Computer Communications. IEEE (2014): 1-10. [cited by applicant]
IEEE Standard for Low-Rate Wireless Networks “IEEE Std 802.15. Apr. 2015 (Revision of IEEE Std 802.15. Apr. 2011).” IEEE (2016): 1-709. [cited by applicant]
Jiang et al., “mmVib: micrometer-level vibration measurement with mmwave radar.” Proceedings of the 26th Annual International Conference on Mobile Computing and Networking (2020): 1-13. [cited by applicant]
Kempke et al., “Surepoint: Exploiting ultra wideband flooding and diversity to provide robust, scalable, high-fidelity indoor localization.” Proceedings of the 14th ACM Conference on Embedded Network Sensor Systems CD-R… [cited by applicant]
Li et al., “Effective adaptive Kalman filter for MEMS-IMU/magnetometers integrated attitude and heading reference systems.” The Journal of Navigation 66.1 (2013): 1-16. [cited by applicant]
Liu et al., “Push the limit of WiFi based localization for smartphones.” Proceedings of the 18th annual international conference on Mobile computing and networking (2012): 1-12. [cited by applicant]
Liu et al., “Real-time arm skeleton tracking and gesture inference tolerant to missing wearable sensors.” Proceedings of the 17th Annual International Conference on Mobile Systems, Applications, and Services (2019): 287… [cited by applicant]
Mahony et al., “Nonlinear complementary filters on the special orthogonal group.” IEEE Transactions on automatic control 53.5 (2008): 1-17. [cited by applicant]
Mao et al., “Cat: high-precision acoustic motion tracking.” Proceedings of the 22nd Annual International Conference on Mobile Computing and Networking (2016): 69-81. [cited by applicant]
Microsoft, “Change handwritten ink to shapes, text, or math in powerpoint for microsoft 365.” Microsoft. https://support.microsoft.com/en-us/topic/changehandwritten- ink-to-shapes-text-or-math-in-powerpoint-for-microsof… [cited by applicant]
Microsoft, “Surface Pen.” Microsoft. https://news.microsoft.com/uploads/2017/05/SurfacePenFS.pdf (2017): 1-3. [cited by applicant]
Nandakumar et al., “Fingerio: Using active sonar for fine-grained finger tracking.” Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems (2016): 1515-1525. [cited by applicant]
Parate et al., “RisQ: Recognizing smoking gestures with inertial sensors on a wristband.” Proceedings of the 12th annual international conference on Mobile systems, applications, and services (2014): 1-38. [cited by applicant]
Patwari et al., “Breathfinding: A wireless network that monitors and locates breathing in a home.” IEEE Journal of Selected Topics in Signal Processing 8.1 (2013): 1-10. [cited by applicant]
Ramer, U., “An iterative procedure for the polygonal approximation of plane curves.” Computer graphics and image processing 1.3 (1972): 244-256. [cited by applicant]
Roy et al., “Backdoor: Making microphones hear inaudible sounds.” Proceedings of the 15th Annual International Conference on Mobile Systems, Applications, and Services (2017): 2-14. [cited by applicant]
Roy et al., “Inaudible voice commands: The {Long-Range} attack and defense.” 15th USENIX Symposium on Networked Systems Design and Implementation (NSDI 18). (2018): 546-560. [cited by applicant]
Samsung, “S pen.” Samsung. https://www.samsung.com/global/galaxy/galaxy-note10/s-pen/ (2018): 1-2. [cited by applicant]
Sensonor, “STIM3000.” Safran. https://www.sensonor.com/products/inertial-measurement-units/stim300/ Jun. 2020, 1-3. [cited by applicant]
Shangguan et al., “Leveraging electromagnetic polarization in a two-antenna whiteboard in the air.” Proceedings of the 12th International on Conference on emerging Networking Experiments and Technologies (2016): 443-456. [cited by applicant]
Shen et al., “I am a smartwatch and i can track my user's arm.” Proceedings of the 14th annual international conference on Mobile systems, applications, and services (2016): 85-96. [cited by applicant]
Sullivan, “COVID-19 Has Widened the Homework Gap Into a Full-Fledged Learning Gap.” Diversity and Equity. Ed Surge. https://www.edsurge.com/news/ Jul. 2020, 1-5. [cited by applicant]
Sun et al., “Depth aware finger tapping on virtual displays.” Proceedings of the 16th Annual International Conference on Mobile Systems, Applications, and Services (2018): 283-295. [cited by applicant]
Sun et al., “Vskin: Sensing touch gestures on surfaces of mobile devices using acoustic signals.” Proceedings of the 24th Annual International Conference on Mobile Computing and Networking (2018): 1-15. [cited by applicant]
Wang et al., “Device-free gesture tracking using acoustic signals.” Proceedings of the 22nd Annual International Conference on Mobile Computing and Networking (2016): 82-94. [cited by applicant]
Wang et al., “MAVL: Multiresolution analysis of voice localization.” 18th USENIX Symposium on Networked Systems Design and Implementation (NSDI 21). (2021): 844-858. [cited by applicant]