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TI毫米波雷达呼吸、心率检测原理 DriverVitalSigns_DevelopersGuide

毫米波雷达

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TI官方指南 DriverVitalSigns_DevelopersGuide，毫米波雷达心率、呼吸检测原理。介绍了毫米波雷达心率、呼吸频率检测的基本原理和算法流程，并通过TI的AWR1642 实现了其功能。

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TI mmWave Labs

Driver Vital Signs – Developer’s Guide

Lab Overview

• This lab exercise demonstrates the ability of AWR-1642 TI-mmWave sensor to measure body

displacements due to breathing and heart beat

• Typical body surface displacement parameters due to breathing and heart-beat are

From Front From Back

Vital Signs Frequency

Amplitude Amplitude

Breathing Rate (Adults)

0.1 – 0.5 Hz ~ 1- 12 mm ~ 0.1 – 0.5 mm

Heart Rate (Adults) 0.8 – 2.0 Hz

~ 0.1 – 0.5 mm ~ 0.01 – 0.2 mm

• To measure these small scale vibrations/displacements, we measure the change in phase of the

FMCW signal with time at the target range bin







  

- corresponds to the change in phase when the target moves a distance R

- Note that a smaller wavelength will give better displacement sensitivity







• Code Composer Studio (CCS) project along with source code is provided for this lab

• Pre-built binary files are also provided that can be loaded on to the AWR-1642 EVM

FMCW Radar Basics

 Periodic linearly-increasing frequency chirps (known as Frequency-Modulated Continuous Wave (FMCW))

are transmitted by radar towards the object

Time, sec

Frequency, Hz

()

j f t t

s t e













 Transmitted FMCW signal is given by

 Signal at the receiver is a delayed version of the transmitted signal

Time, sec

 

( ). ( )

j t R

j f t

s t r t e e



















 The received signal from an object at range R after mixing and filtering is given by

   

()

c d d

j f t t t t

r t e





  







FMCW Radar – Vital signs Measurements

 

()

j t R

j f t

b t e e





















 Note that for a single object, the beat signal b(t) is a sinusoidal and has both frequency 𝑓

𝑏

and phase ∅

𝑏

 To measure small scale vibrations, we measure the change in phase of the FMCW signal with time at the

object range bin. If an object moves a distance ∆R then the change in phase between consecutive

measurements is given by







  

 Phase can be measured by taking the FFT of the beat signal b(t) and computing the phase at the object

range-bin.

 Suppose we take the FFT and the object is at range-bin m, then the vibration signal x(t) can be extracted by

measuring the phase at range-bin m at time indices nT

, where n is the chirp index and T

is the time

between consecutive measurements

Note that we are assuming that the vibrations x(t) are

small so that the object remains in the same range-bin

during the duration of the measurements

As an example at λ=4 mm when we have displacements as

small as ∆R = 1mm, the corresponding phase change is





( , ) ( , )

s b s

x m nT m nT









Chirp Configuration for Demo

 100 ADC Samples per chirp. Chirp duration is 50 ms based on the IF sampling rate of 2 MHz

 Each frame is configured to have 2 chirps. However only the 1st Chirp in the frame is used for processing

 A single TX-RX antenna pair is currently used for processing (Although all the RX antennas are enabled)

 Vital signs waveform is sampled along the “slow time axis” hence the vital signs sampling rate is equal to the Frame-rate of system

Frame Periodicity = 50 ms

Frame 1

Frame 2

Frame 3

Range-Bins

Slow Time Axis

Range-

FFT

Range-

FFT

Range-

FFT

Extract Phase and unwrap

for the object range bin

Object

Range Bin

Slow Time Axis

Frame N

Range-

FFT

Further Processing for

Vital Signs Estimation

Duty Cycle < 1 %

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