mmWave Radar
mmWave Sensor Evaluation Solution
Batman BM201-PC3 mmWave EVM Kit
mmWave People Counting & Detection (PC3)

 

 

mmWave Radar


mmWave Solution bridges Hardware & Software World together with Simplicity

Joybien Batman BM201 mmWave EVM Kit is a Texas Instruments (TI) IWR6843 ASIC based millimeter-wave (mmWave) Kit with Frequency-Modulated Continuous Wave (FMCW) radar technology capable of operation in the 60GHz to 64GHz band with up to 4 GHz continuous chirp, using 3 Transmission Antennas and 4 Receiving Antennas, for sensing target object’s range, velocity, and angle parameters.

Batman BM201 mmWave EVM Kit is with a small and compact mmWave Module (with low-power, self-monitored, ultra-accurate, and lighting condition independent versatilities), along with a Pi-Hat Board for simple and direct connectivity to a Raspberry Pi or NVIDIA Jetson Nano computer, suitable for various applications including: Education, Engineering, Science, Industrial, Medical, and Business & Consumer.


Applications

  • Education’s Practical Radar Introduction
  • Engineering & Science’s Motion Detection, Displacement, etc.
  • Industrial sensor for Displacement & Safe Guard, Factory Automation, Robotics, etc.
  • Building Automation sensor for Occupancy Detection, Proximity & Position sensing, People Counting, Security and Surveillance
  • Business’ Traffic Monitoring, and Proximity Advertisement


People Counting & Detection (PC3)

For a wireless People Counting & Detection in 6 x 6 meter or 36 square meter area (or about 387.5 square feet), for various applications that require people sensing, people counting, or people occupancy density estimation without privacy invasion.


Batman BM201 EVM Kit + NVIDIA Jetson Nano / Raspberry Pi

Batman BM201 EVM Kit + NVIDIA Jetson Nano

Batman BM201 EVM Kit + Raspberry Pi




Selection：Key Data Mode or Raw Data Mode Application




Features

Operating Frequency
  • 60GHz ~ 64GHz coverage
    with 4GHz continuous bandwidth

Antenna
  • 3 Tx and 4 Rx Antennas on Module, with:
    TX Power: 10 dBm
    RX Noise Figure: 14 dB

Processors
  • ARM R4F based MCU and C674x DSP
    for advanced signal processing

On-Chip Memory
  • 1.75MB

•Internal Memories

  • ECC

•Input Power
  • 3.3Vdc, 2.1A

Batman BM201-PC3 EVM Kit includes



Specifications mmWave Sensor Evaluation Module

mmWave ASIC
  • TI IWR6843 Single Chip mmWave Sensor

FMCW Transceiver
  • Integrated PLL, Transmitter, Receiver, Baseband, and A2D
  • 60GHz to 64GHz Coverage With 4GHz Continuous Bandwidth
  • Four Receive Channels
  • Three Transmit Channels
  • Ultra-Accurate Chirp Engine Based on Fractional-N PLL
  • TX Power: 10 dBm
  • RX Noise Figure: 14 dB
  • Phase Noise at 1 MHz: –92 dBc/Hz
  • Antenna Type : ISK Antenna

Built-in Calibration and Self-Test (Monitoring)
  • ARM® Cortex® -R4F-Based Radio Control System
  • Built-in Firmware (ROM)
  • Self-calibrating System Across Frequency and Temperature

DSP
  • C674x DSP for Advanced Signal Processing

On-Chip Memory
  • 1.75MB

MCU
  • ARM R4F Microcontroller for Object Detection, and Interface Control
  • Joybien mmWave Protocol (Per configuration)

I/O
  • Up to 6 ADC Channels (low sample rate monitoring)
  • Up to 2 SPI Ports
  • Up to 2 UARTs
  • I2C – GPIOs

Power Management

  • Built-in LDO Network for Enhanced PSRR
  • I/Os Support Dual Voltage 3.3 V/1.8 V

Clock Source
  • 40MHz

Antenna Orientation

  • 4 receive(RX) 3 transmit (TX) antenna with 108° azimuth field of view (FoV) and 44° elevation FoV

Input Power
  • 3.3VDC, 2.1A source

Operating Temperature
& Humidity
  • 0° to 40° degree Celsius
  • 10 ~ 85% Non-Condensing

Dimensions & Weight
  • 67mm x 46mm x 2mm ; 15 grams net

 

Raspberry Pi-Hat Board /Jetson Nano carrier board

Connector
  • Matching mmWave Module Female Connector
  • Matching Raspberry Pi GPIO Female Connector
  • Micro USB Power Connector
  • Jumpers for Bluetooth Tx/Rx or Raspberry Pi Tx/Rx Selection
  • Jumper for mmWave Raw Data or Key Data Selection

Bluetooth (optional)

  • Joybien JBT24M Bluetooth Low Energy Module

Micro USB Input Power
  • 5VDC, 2Amp.
    (Note: Power Adapter and Micro USB Cable NOT included)

Operating Temperature
Operating Humidity
  • 0° to 40° degree Celsius
  • 10 ~ 85% Non-Condensing

Dimensions & Weight
  • 65.3mm x 56.3mm
    • 30 grams with JBT24M Bluetooth



Python SDK


Python SDK
  • Available on GitHub
    Note: Please refer to README.md file first for proper configuration
  • https://github.com/bigheadG/mmWave

(BM201-LPD)
Long-Range People Detection

(BM201-PC3)
People Counting & Detection

(BM201-TMD)
Traffic Monitoring Detection

(BM201-VSD)
Vital Signs Detection

(BM201-HAM)
High Accuracy Measurement

(BM201-DRN)
Drone Radar Navigation

(BM201-FDS)
Fall Detection Sensing

 



Appendix: Joybien mmWave EVM Kit Application Solution Selection

(BM201-VOD)
Zone Occupancy Detection
  • For plotting a Range-Azimuth-Heatmap with a 64 x 48 Grid Matrix covering: Range of 3 meter / 64 row (approx. 0.047 meter per row) x Azimuth of 108 degree / 48 column (approx. 2.3 degree /column). Subsequently a programmer may write code to group the Grid(s) into Zone(s) for detecting whether the particular Zone(s) is occupied by Target(s); suitable for vehicle occupancy detection or for occupancy detection for an area of around 3 meter x 3 meter.

(BM201-LPD)
Long-Range People Detection
  • For a contactless and wearableless Long-Range People Detection (LPD) of 1 meter ~ 50 meters (about 3 ~ 164 feet), for various applications that require people sensing or counting without privacy invasion.

(BM201-PC3)
People Counting & Detection
  • For a wireless People Counting & Detection in 6 x 6 meter or 36 square meter area (or about 387.5 square feet), for various applications that require people sensing, people counting, or people occupancy density estimation without privacy invasion.

(BM201-TMD)
Traffic Monitoring Detection
  • For detecting moving objects (such as vehicles) in 5m ~ 50m with FOV of approx. +/- 54 degrees with Position X&Y, Velocity X&Y info. And based on the detected data, a programmer may write a program to define virtual Zones, for mapping objects (vehicles) moving in and out of certain Zones for traffic monitoring applications.

(BM201-VSD)
Vital Signs Detection
  • For a contactless and wearableless human Vital Signs Detection (VSD) with real-time Heartbeat Rate & Respiration Rate data, for range of 30cm ~ 90cm (about 1~3 feet); along with Status Indicator for sensing the presence of a person, as well as the measurement stability, and whether the person is present but without Vital Signs.

(BM201-HAM)
High Accuracy Measurement
  • For a wireless High Accuracy Measurement (HAM) of an object distance with range of 30cm ~ 3 meters (about 1~10 feet), having millimeter measurement resolution.

(BM201-FDS)
Fall Detection Sensing
  • For wireless sensing of people-fall-detection along with people movement & tracking in 3-Dimensional region covering 6m x 6m area without privacy invasion. The sensed people behavior data are with Position X/Y/Z, Velocity X/Y/Z, and Acceleration X/Y/Z parameters suitable for people movement analysis such as standing, sitting, lying down or falling down positions.

 

Copyright ©2021 , Joybien Technologies Co., Ltd.
Joybien reserves the right to make changes without further notice to and products herein. Joybien makes no warranty, representation or guarantee regarding the suitability of its products for any particular purpose, nor does Joybien assume any liability arising out of the application or use of any product or circuit. Joybien’s products are not to be used in life support devices or systems, if a failure of an Joybien's product can reasonably be expected to cause the failure of that life support device or system, or to affect the safety or effectiveness of that device or system.


Note:
  • NVIDIA logo, and Jetson Nano are trademarks and/or registered trademarks of NVIDIA Corporation.ducation’s Practical Radar Introduction
  • Raspberry Pi logo and Raspberry Pi 4 are trademarks and/or registered trademarks of Raspberry Pi Foundation.
  • "Python" is a registered trademark of the PSF.
  • This EVM Kit does not include Raspberry Pi computer, nor NVIDIA Jetson Nano computer.

 

Solution



‧ Introduction
   mmWAVE SENSOR EVALUATION SOLUTION

‧mmWave People Counting & Detection (PC3)

 ‧FAQ

 

‧ Python SDK (Github)

 

‧ Datasheet (EN)