IRZ0140 Signals and Signal Processing

Contact data

IRZ0140 Signals and Signal Processing

Julia Berdnikova e-mail: [email protected]

Lecture 14 Julia Berdnikova

Tallinn University of Technology, Department of Radio and Communication Engineering, IRZ0140 Signals and Signal Processing

Home page of the course: http://www.lr.ttu.ee/signals/


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Signal processing applications

Signal processing applications

Communication systems

Data transmission

Speech, Audio, Television, Broadcasting, Multimedia

Navigation

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Communication system

Space application

Data collecting systems

Automatic Control

Biomedical systems

Robotics

Military applications

jtc.

Data acquisition system (data measuring, sensing systems)

Digital/ Analog user

rtr tr

Fuqin

Signal processing

Transmitter Receiver

Xiong . Digital modulation techniques . Boston (Mass.) ; London : Artech House, 2006 G.S, Fundamentals of Biomedical Engineering Tallinn University of Technology, Department of Radio and Communication Engineering, IRZ0140 Signals and Signal Processing

Sawhney,


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Data acquisition systems

Passive (without transmitting)

Active (signal generation)

Reception types for communication and sensing system

Main signal processing steps for active systems:

signal generation

reception

processing (detection, estimation),

measured data representation,

data storage

data post-processing

Coherent

Noncoherent

Coherent detection – the phase of the signal to be known exactly.


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Digital modulations

Digital modulations N –noncoherently D – differentially


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Digital modulations

Digital modulations

ASK (Amplitude-Shift Keying )

si (t ) = Ai p (t ) cos(2πf c t ), 0 ≤ t ≤ T

FSK (Frequency-Shift Keying)

si = Acos(2πf i t + Φi )

i = 1,2,K M

i = 1,2,3,K M

PSK ( Phase-Shift Keying)

si (t ) = A cos(2πf c t + θ i ), 0 ≤ t ≤ T i = 1,2,K, M

θi =

( 2i − 1 )π M

ASK FSK PSK



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Criteria of Choosing Modulation Scemes for Communication Systems

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Signal processing algorithms Signal processing algorithm depends on the application area and type

power efficiency (bit error rate or bit error probability) Widely used:

bandwidth efficiency, system complexity.


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spectral analysis

filtering

statistical processing


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Biomedical Signals (Example)

Biomedical Signals (Example)

• Heart electrical conduction at limb surfaces

Electrocardiogram (ECG)

Main medical imaging signals:

•

Electroencephalogram (EEG)

•

•

Surface CNS electrical activity

Magnetic fields of neural activity

Muscle electrical activity

a)

x-ray transmission

b)

Gamma-ray transmission

c)

Nuclear magnetic resonance induction

d)

Ultrasound echoes

Magnetoencephalogram (MEG)

Electromyogram (EMG)

Theis, Fabian J. Meyer-Bäse, Anke, Biomedical Signal Analysis : Contemporary Methods and Applications Amine Naīt-Ali , Advanced biosignal processing Tallinn University of Technology, Department of Radio and Communication Engineering, IRZ0140 Signals and Signal Processing


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Biomedical Signals (Example) Active sensing systems

Ultrasound

The range to a target, target velocity and target properties could be measured using a transmitted signal.

Minkoff J., Signal Processing Fundamentals and Applications for Communications and Sensing Systems Tallinn University of Technology, Department of Radio and Communication Engineering, IRZ0140 Signals and Signal Processing

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Periodic signal generation (example)

Digital signal generation

sine_table

Sine wave generation

s(0) s(1)

Table generation

0

s(2)

N

0x00

0.195

…. s(N-1)

Formula generation (recursive algorithms, step value)

….

…. or

Table addresses are from 0 up to N-1 Next address could be calculated by ADDRi= ADDRi-1+C1

si = A ⋅ sine_table[ADDR i ] ∆t d


If sampling frequency is

t

Fd

the output signal frequency will be

Fout = C1⋅ Fd / N Tallinn University of Technology, Department of Radio and Communication Engineering, IRZ0140 Signals and Signal Processing

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Sine wave generation, recursive algorithm

Fd - sampling frequency,

∆=

Fout =

td =

1 , Fd

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Sawtooth signal generation

- sampling frequency,

0xE7

s(t)

∆s (t )

Fd

N

0x31

-0.195

0x18

N

0.384

Signal phase value: ϕi=2π⋅Fout⋅i⋅∆ ,

ϕi-1=2π⋅F out⋅(i-1)⋅∆,

1 Fd

1 - output signal frequency T ϕ1=2π⋅F out⋅ 1⋅∆ =2πF out⋅ /Fd.

N- number of level between min. and max. of the signal 16-bits Fixed point

N=65536

Out_Si=A⋅sin(ϕi)= A⋅sin(ϕi-1+ ϕ1)=A⋅sin(ϕi-1)⋅cos(ϕ1)+A⋅cos(ϕi-1)⋅sin(ϕ1)

Cosine signal: Out_Ci=A⋅cos(ϕi)= A⋅cos(ϕi-1+ ϕ1)=A⋅cos(ϕi-1)⋅cos(ϕ1)-A⋅sin(ϕi-1)⋅sin(ϕ1)

F 1 Fout < d , Tout = 2 Fout Fout td ∆ = ⋅N = ⋅N Fd T

Output signal frequency should be


Sine signal:

C_s= sin(ϕ1)=sin(2πFout /Fd), C_c= cos(ϕ1)=cos(2πFout /Fd) Recursive output for sine and cosine signals 19

Out_Si= Out_Si-1 ⋅ Cc+Out_Ci-1⋅ Cs Out_Ci= Out_Ci-1 ⋅ Cc-Out_Si-1⋅ Cs


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MATLAB Demos

NI LabVIEW


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