An Ultrasound Imaging System With Onchip Pervoxel Rx Beamfocusing For Realtime Drone Applications

• doi: 10.1109/JSSC.2022.3202502
• title: An Ultrasound Imaging System With On-Chip Per-Voxel RX Beamfocusing for Real-Time Drone Applications
• publisher: IEEE
• isbn:
• issn: 1558-173X
• rank: 1530
• access_type: OPEN_ACCESS
• content_type: Journals
• abstract: For drone vision and navigation, low-power 3-D depth sensing with robust operations against strong/weak light and various weather conditions is crucial. CMOS image sensor (CIS) and light detection and ranging (LiDAR) can provide high-fidelity imaging. However, CIS lacks depth sensing and has difficulty in low light conditions. LiDAR is expensive with issues of dealing with strong direct interference sources. Ultrasound imaging system (UIS), on the other hand, is robust in various weather and light conditions and is cost-effective. However, in air channel, it often suffers from long image reconstruction latency and low framerate. To address these issues, we present a UIS application-specific integrated circuit (ASIC) that adopts the one-shot transmitter (TX) and on-chip per-voxel receiver (RX) beamfocusing (PV-RXBF) image reconstruction scheme. The ASIC adopts the designs of fully differential charge-reuse high-voltage TX (FDCR-HVTX), digital back-end (DBE), and an on-chip power management unit (PMU). FDCR-HVTX generates 28 $\text{V}_{\mathrm {pp}}$ pulses and reduces the average power consumption by 25% by charge reuse (CR). The DBE achieves 7.76- $\mu \text{s}$ processing latency and 9.83M-FocalPoint/s throughput to effectively translate real-time 3-D image streaming at 24 frames/s. A prototype UIS, with an $8\times 8$ bulk piezo transducer array, is assembled with the proposed ASIC and a wireless data transmission module [field-programmable gate array (FPGA) + ESP32] on an entry-level consumer drone, and the real-time wireless 3-D image streaming at 24 frames/s with a range of 7 m is verified while the drone is flying. The ASIC implemented in 180-nm 1P6M Standard CMOS occupies 32.5 mm2 and consumes 142.3 mW.
• article_number: 9903852
• pdf_url: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9903852
• html_url: https://ieeexplore.ieee.org/document/9903852/
• abstract_url: https://ieeexplore.ieee.org/document/9903852/
• publication_title: IEEE Journal of Solid-State Circuits
• conference_location:
• conference_dates:
• publication_number: 4
• is_number: 9926114
• publication_year: 2022
• publication_date: Nov. 2022
• start_page: 3186
• end_page: 3199
• citing_paper_count: 7
• citing_patent_count: 0
• download_count: 3689
• insert_date: 20220927
• index_terms:
  • ieee_terms:
    • Drones
    • CMOS technology
    • Ultrasonic imaging
    • System-on-chip
    • Real-time systems
    • Application specific integrated circuits
  • author_terms:
    • 3-D imaging
    • all light condition
    • charge reuse (CR)
    • depth sensing
    • drone
    • high-voltage transmitter (TX)
    • low power
    • per-voxel RX beamfocusing (PV-RXBF)
    • real time
    • standard CMOS
    • ultrasound
  • dynamic_index_terms:
    • Ultrasound Imaging
    • Ultrasound Imaging System
    • Drone Applications
    • Prototype
    • Light Conditions
    • 3D Images
    • Power Consumption
    • Image Reconstruction
    • Iterative Reconstruction
    • Tomographic Reconstruction
    • Light Detection And Ranging
    • Lidar
    • Low Light Conditions
    • Processing Latency
    • Standard CMOS
    • Air Channel
    • Electrode
    • Spatial Resolution
    • Image Quality
    • Focal Point
    • Red Arrows
    • Static Random Access Memory
    • Static Random-access Memory
    • Unmanned Aerial Vehicles
    • Beam Focusing
    • Focal Beam
    • Beam Focus
    • Lateral Angle
    • Minimum Latency
    • Transduction Channels
    • Volumetric Imaging
    • Clock Cycles
    • Boost Converter
    • Sound Pressure
    • Acoustic Pressure
• authors:
  • Author Name: Liuhao Wu
    Affiliation: Department of Electrical and Computer Engineering, National University of Singapore, Queenstown, Singapore
    Author URL: https://ieeexplore.ieee.org/author/37088919366
    ID: 37088919366
    Order: 1
    Author Affiliations:
    • Department of Electrical and Computer Engineering, National University of Singapore, Queenstown, Singapore
  • Author Name: Jiaqi Guo
    Affiliation: Department of Electrical and Computer Engineering, National University of Singapore, Queenstown, Singapore
    Author URL: https://ieeexplore.ieee.org/author/37089187335
    ID: 37089187335
    Order: 2
    Author Affiliations:
    • Department of Electrical and Computer Engineering, National University of Singapore, Queenstown, Singapore
  • Author Name: Rucheng Jiang
    Affiliation: Department of Electrical and Computer Engineering, National University of Singapore, Queenstown, Singapore
    Author URL: https://ieeexplore.ieee.org/author/37089336698
    ID: 37089336698
    Order: 3
    Author Affiliations:
    • Department of Electrical and Computer Engineering, National University of Singapore, Queenstown, Singapore
  • Author Name: Yande Peng
    Affiliation: Department of Mechanical Engineering, University of California at Berkeley, Berkeley, CA, USA
    Author URL: https://ieeexplore.ieee.org/author/37088807582
    ID: 37088807582
    Order: 4
    Author Affiliations:
    • Department of Mechanical Engineering, University of California at Berkeley, Berkeley, CA, USA
  • Author Name: Han Wu
    Affiliation: Department of Electrical and Computer Engineering, National University of Singapore, Queenstown, Singapore
    Author URL: https://ieeexplore.ieee.org/author/37088367078
    ID: 37088367078
    Order: 5
    Author Affiliations:
    • Department of Electrical and Computer Engineering, National University of Singapore, Queenstown, Singapore
  • Author Name: Jiamin Li
    Affiliation: School of Microelectronics, Southern University of Science and Technology (SUSTech), Shenzhen, China
    Author URL: https://ieeexplore.ieee.org/author/37088368107
    ID: 37088368107
    Order: 6
    Author Affiliations:
    • School of Microelectronics, Southern University of Science and Technology (SUSTech), Shenzhen, China
  • Author Name: Yang Luo
    Affiliation: Department of Electrical and Computer Engineering, National University of Singapore, Queenstown, Singapore
    Author URL: https://ieeexplore.ieee.org/author/37089572956
    ID: 37089572956
    Order: 7
    Author Affiliations:
    • Department of Electrical and Computer Engineering, National University of Singapore, Queenstown, Singapore
  • Author Name: Liwei Lin
    Affiliation: Department of Mechanical Engineering, University of California at Berkeley, Berkeley, CA, USA
    Author URL: https://ieeexplore.ieee.org/author/37280273000
    ID: 37280273000
    Order: 8
    Author Affiliations:
    • Department of Mechanical Engineering, University of California at Berkeley, Berkeley, CA, USA
  • Author Name: Jerald Yoo
    Affiliation: Department of Electrical and Computer Engineering, National University of Singapore, Queenstown, Singapore
    Author URL: https://ieeexplore.ieee.org/author/37292165500
    ID: 37292165500
    Order: 9
    Author Affiliations:
    • Department of Electrical and Computer Engineering, National University of Singapore, Queenstown, Singapore
    • N.1 Institute for Health, 28 Medical Dr, Singapore

Image Sensor

• sensor_type: CMOS
• resolution: Not specified
• dynamic_range: Not specified
• pixel_size: Not specified
• dark_current: Not specified

Optical Data

• focal_length: Not specified
• aperture: Not specified
• field_of_view: Not specified
• distortion: Not specified

Performance Metrics

• frame_rate: 24 frames/s
• power_consumption: 142.3 mW

Applications & Benefits

• cell_imaging: Not specified
• benefits: Robust operation against varied lighting and weather conditions, suitable for drone vision and navigation.

Supporting Organizations

• supported_by: Agency for Science, Technology and Research (A*STAR), Samsung Electronics

Manuscript Details

• publication_date: Nov. 2022

Relevancy Score

• score: 8
• missing_fields:
  • pixel_size
  • fill_factor
  • quantum_efficiency
  • dark_current
  • dynamic_range
  • power_consumption

Processed JSON Filename

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