Lecture 6 doppler techniques physics processing interpretation l.jpg
This presentation is the property of its rightful owner.
Sponsored Links
1 / 58

Lecture 6 : Doppler Techniques: Physics, processing, interpretation PowerPoint PPT Presentation


  • 107 Views
  • Uploaded on
  • Presentation posted in: General

Lecture 6 : Doppler Techniques: Physics, processing, interpretation . Doppler US Techniques . As an object emitting sound moves at a velocity v , the wavelength of the sound in the forward direction is compressed ( λ s ) and

Download Presentation

Lecture 6 : Doppler Techniques: Physics, processing, interpretation

An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -

Presentation Transcript


Lecture 6 doppler techniques physics processing interpretation l.jpg

Lecture 6:

Doppler Techniques:

Physics, processing, interpretation


Doppler us techniques l.jpg

Doppler US Techniques

  • As an object emitting sound moves at a velocity v,

  • the wavelength of the sound in the forward direction is compressed (λs) and

  • the wavelength of the sound in the receding direction is elongated (λl).

  • Since frequency (f) is inversely related to wavelength, the compression increases the perceived frequency and the elongation decreases the perceived frequency.

  • c = sound speed.


Doppler us techniques3 l.jpg

Doppler US Techniques

  • InEquations (1) and (2), fis the frequency of the sound emittedby the object and would be detected by the observer if the objectwere at rest. ±Δf represents a Doppler effect–inducedfrequency shift

  • The sign depends on the direction in whichthe object is traveling with respect to the observer.

  • These equations apply to the specific condition that the objectis traveling either directly toward or directly away from theobserver


Doppler us techniques4 l.jpg

Doppler US Techniques

ftis transmitted frequency

fr is received frequency

v is the velocity of the target,

θisthe angle between the ultrasound beam and the direction of the target's motion, and

cis the velocity of sound in the medium


A general doppler ultrasound signal measurement system l.jpg

A general Doppler ultrasound signal measurement system


A simplified equivalent representation of an ultrasonic transducer l.jpg

A simplified equivalent representation of an ultrasonic transducer


Block diagram of a non directional continuous wave doppler system l.jpg

Block diagram of a non-directional continuous wave Doppler system


Block diagram of a non directional pulsed wave doppler system l.jpg

Block diagram of a non-directional pulsed wave Doppler system


Oscillator l.jpg

Oscillator


Transmitter l.jpg

Transmitter


D emodulator l.jpg

Demodulator


T wo channel differential audio amplifier l.jpg

Two channel differential audio amplifier


Programmable bandpass filter and amplifier l.jpg

Programmable bandpass filter and amplifier


The audio amplifier l.jpg

the audio amplifier


Pc interface l.jpg

PC interface


Slide17 l.jpg

PROCESSING OF DOPPLER ULTRASOUND SIGNALS


Processing of doppler ultrasound signals l.jpg

sin

cos

Gated

transmiter

Master

osc.

Demodulator

Sample

& hold

Band-pass

filter

si

Further

processing

Logic

unit

Receiver

amplifier

RF

filter

Demodulator

Sample

& hold

Band-pass

filter

sq

Transducer

  • Demodulation

  • Quadrature to directional signal conversion

  • Time-frequency/scale analysis

  • Data visualization

  • Detection and estimation

  • Derivation of diagnostic information

V

Processing of Doppler Ultrasound Signals


Single side band detection l.jpg

Single side-band detection


Heterodyne detection l.jpg

Heterodyne detection


Frequency translation and side band filtering detection l.jpg

Frequency translation and side-band filtering detection


Direct sampling l.jpg

direct sampling

  • Effect of the undersampling.

    (a) before sampling; (b) after sampling


Quadrature phase detection l.jpg

Quadrature phase detection


Slide24 l.jpg

TOOLS FOR DIGITAL SIGNAL PROCESSING


Understanding the complex fourier transform l.jpg

Understanding the complex Fourier transform

  • The Fourier transform pair is defined as

  • In general the Fourier transform is a complex quantity:

  • where R(f) is the real part of the FT,I(f) is the imaginary part, X(f) is the amplitude or Fourier spectrum of x(t) and is given by ,θ(f) is the phase angle of the Fourier transform and given by tan-1[I(f)/R(f)]


Slide26 l.jpg

  • If x(t) is a complex time function, i.e. x(t)=xr(t)+jxi(t) where xr(t) and xi(t) are respectively the real part and imaginary part of the complex function x(t), then the Fourier integral becomes


Properties of the fourier transform for complex time functions l.jpg

Properties of the Fourier transform for complex time functions


Interpretation of the complex fourier transform l.jpg

Interpretation of the complex Fourier transform

  • If an input of the complex Fourier transform is a complex quadrature time signal (specifically, a quadrature Doppler signal), it is possible to extract directional information by looking at its spectrum.

  • Next, some results are obtained by calculating the complex Fourier transform for several combinations of the real and imaginary parts of the time signal (single frequency sine and cosine for simplicity).

  • These results were confirmed by implementing simulations.


Slide29 l.jpg

  • Case (1).

  • Case (2).

  • Case (3).

  • Case (4).

  • Case (5).

  • Case (6).

  • Case (7).

  • Case (8).


The discrete fourier transform l.jpg

The discrete Fourier transform

  • The discrete Fourier transform (DFT) is a special case of the continuous Fourier transform. To determine the Fourier transform of a continuous time function by means of digital analysis techniques, it is necessary to sample this time function. An infinite number of samples are not suitable for machine computation. It is necessary to truncate the sampled function so that a finite number of samples are considered


D iscrete fourier transform pair l.jpg

Discrete Fourier transform pair


Complex modulation l.jpg

complex modulation


Hilbert transform l.jpg

Hilbert transform

  • The Hilbert transform (HT) is another widely used frequency domain transform.

  • It shifts the phase of positive frequency components by -900 and negative frequency components by +900.

  • The HT of a given function x(t) is defined by the convolution between this function and the impulse response of the HT (1/πt).


Hilbert transform34 l.jpg

Hilbert transform

  • Specifically, if X(f) is the Fourier transform of x(t), its Hilbert transform is represented by XH(f), where

  • A ±900 phase shift is equivalent to multiplying by ej900=±j, so the transfer function of the HT HH(f) can be written as


Impulse response of ht l.jpg

impulse response of HT

An ideal HT filter can be approximated using standard filter design techniques. If a FIR filter is to be used , only a finite number of samples of the impulse response suggested in the figure would be utilised.


Slide36 l.jpg

  • x(t)ejωct is not a real time function and cannot occur as a communication signal. However, signals of the form x(t)cos(ωt+θ) are common and the related modulation theorem can be given as

  • So, multiplying a band limited signal by a sinusoidal signal translates its spectrum up and down in frequency by fc


Digital filtering l.jpg

Digital filtering

  • Digital filtering is one of the most important DSP tools.

  • Its main objective is to eliminate or remove unwanted signals and noise from the required signal.

  • Compared to analogue filters digital filters offer sharper rolloffs,

  • require no calibration, and

  • have greater stability with time, temperature, and power supply variations.

  • Adaptive filters can easily be created by simple software modifications


Digital filters l.jpg

Digital Filters

  • Non-recursive (finite impulse response, FIR)

  • Recursive (infinite impulse response, IIR).

  • The input and the output signals of the filter are related by the convolution sum.

  • Output of an FIR filter is a function of past and present values of the input,

  • Output of an IIR filter is a function of past outputs as well as past and present values of the input


B asic iir filter and fir filter realisations l.jpg

Basic IIR filter and FIR filter realisations


Dsp for quadrature to directional signal conversion l.jpg

DSP for Quadrature to Directional Signal Conversion

  • Time domain methods

    • Phasing filter technique (PFT) (time domain Hilbert transform)

    • Weaver receiver technique

  • Frequency domain methods

    • Frequency domain Hilbert transform

    • Complex FFT

    • Spectral translocation

  • Scale domain methods (Complex wavelet)

  • Complex neural network


General definition of a quadrature doppler signal l.jpg

GENERAL DEFINITION OF A QUADRATURE DOPPLER SIGNAL

  • A general definition of a discrete quadrature Doppler signal equation can be given by

  • D(n)and Q(n), each containing information concerning forward channel and reverse channel signals (sf(n) and sr(n) and their Hilbert transforms H[sf(n)] and H[sr(n)]), are real signals.


Asymmetrical implementation of the pft l.jpg

Asymmetrical implementation of the PFT


Symmetrical implementation of the pft l.jpg

Symmetrical implementation of the PFT


Slide44 l.jpg

  • An alternative algorithm is to implement the HT using phase splitting networks

  • A phase splitter is an all-pass filter which produces a quadrature signal pair from a single input

  • The main advantage of this algorithm over the single filter HT is that the two filters have almost identical pass-band ripple characteristics


Weaver receiver technique wrt l.jpg

Weaver Receiver Technique (WRT)

  • For a theoretical description of the system consider the quadrature Doppler signal defined by

    which is band limited tofs/4, and a pair of quadrature pilot frequency signals given by

    where ωc/2π=fs/4.

  • The LPF is assumed to be an ideal LPF having a cut-off frequency of fs/4.


Asymmetrical implementation of the wrt l.jpg

Asymmetrical implementation of the WRT


Symmetrical implementation l.jpg

Symmetrical implementation


Implementation of the wrt algorithm using low pass high pass filter pair l.jpg

Implementation of the WRT algorithm using low-pass/high-pass filter pair


Frequency domain processing l.jpg

FREQUENCY DOMAIN PROCESSING

  • These algorithms are almost entirely implemented in the frequency domain (after fast Fourier transform),

  • They are based on the complex FFT process.

  • The common steps for the all these implementations are the complex FFT, the inverse FFT and overlapping techniques to avoid Gibbs phenomena

  • Three types of frequency domain algorithm will be described:

    Hilbert transform method,

    Complex FFT method, and

    Spectral translocation method.


Frequency domain hilbert transform algorithm l.jpg

frequency domain Hilbert transform algorithm


Complex fft method cfft l.jpg

Complex FFT Method (CFFT)

  • The complex FFT has been used to separate the directional signal information from quadrature signals so that the spectra of the directional signals can be estimated and displayed as sonograms.

  • It can be shown that the phase information of the directional signals is well preserved and can be used to recover these signals.


Spectral translocation method stm l.jpg

Spectral Translocation Method (STM)


  • Login