matched filter detection

14
Matched Filter Detection Using lab view

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MATCHED FILTER DETACTION USING LABVIEW BY:M.SURYADEEPAK

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Page 1: Matched filter detection

Matched Filter DetectionUsing lab view

Page 2: Matched filter detection

Objectives(Tasks)

Generation of chrip signal

Generation of noisy

wave form

Matched filter

detection

• Generation of chirp signal

• Generation of noisy wave form

• Matched filter detection

Page 3: Matched filter detection

2

Matched Filter

• Detection of pulse in presence of additive noiseReceiver knows what pulse shape it is looking for

Channel memory ignored (assumed compensated by other means, e.g. channel equalizer in receiver)

Additive white Gaussian noise (AWGN) with zero mean and

variance N0 /2

g(t)

Pulse signal

w(t)

x(t)h(t)

y(t)

t = T

y(T)

Matched filter

)()(

)(*)()(*)()(

0 tntg

thtwthtgty

T is pulse period

Page 4: Matched filter detection

13 - 4

Matched Filter• Given transmitter pulse shape g(t) of duration T, matched filter

is given by hopt(t) = k g*(T-t) for all kDuration and shape of impulse response of the optimal filter is

determined by pulse shape g(t)

hopt(t) is scaled, time-reversed, and shifted version of g(t)

• Optimal filter maximizes peak pulse SNR

Does not depend on pulse shape g(t)

Proportional to signal energy (energy per bit) Eb

Inversely proportional to power spectral density of noise

SNR2

|)(| 2

|)(| 2

0

2

0

2

0

max

N

Edttg

NdffG

N

b

Page 5: Matched filter detection

Typical Application: Radar

][ns

n

Send a Pulse…

][ny

n

0n

… and receive it back with noise, distortion …N

Problem: estimate the time delay , ie detect when we receive it.0n

Page 6: Matched filter detection

Use Inner Product

“Slide” the pulse s[n] over the received signal and see when the inner product is maximum:

][s

][y

0n

N

n

1

0

* ][][][N

ys snynr

0 if ,0][ nnnrys

Page 7: Matched filter detection

Use Inner Product

][s

“Slide” the pulse x[n] over the received signal and see when the inner product is maximum:

][y

N

0n

if 0nn MAXsnynrN

ys

1

0

* ][][][

Page 8: Matched filter detection

Matched Filter

Take the expression

][]0[]1[]1[...]1[]1[

][][][

***

1

0

*

nysnysNnyNs

snynrN

n

ys

Then

]1[]1[]1[]1[...][]0[][̂ NnyNhnyhnyhnr

][ny ][nh

1,...,0 ],1[][ * NnnNsnh

]1[][ˆ Nnrnr ys

Compare this, with the output of the following FIR Filter

Page 9: Matched filter detection

Matched Filter

This Filter is called a Matched Filter

The output is maximum when

][ny ][ˆ nr

][nh

1,...,0 ],1[][ * NnnNsnh

]1[][ˆ Nnrnr ys

01 nNn

10 Nnni.e.

Page 10: Matched filter detection

Example

0 2 4 6 8 10 12 14 16 18 20-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

][ns

0 20 40 60 80 100 120 140 160 180 200-6

-4

-2

0

2

4

6

8

10

12

0 20 40 60 80 100 120 140 160 180-2

-1.5

-1

-0.5

0

0.5

1

1.5

][ny

][ny ][ˆ nr

][nh

1,...,0 ],1[][ * NnnNsnh

1,...,0],[ NnnsWe transmit the pulse shown below, with length 20N

Received signal:

Max at n=1191001201190 n

Page 11: Matched filter detection

Example: Chirp

49,...,49],[ nnrss49,...,0],[ nns

0 5 10 15 20 25 30 35 40 45 50-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

-50 -40 -30 -20 -10 0 10 20 30 40 50-10

-5

0

5

10

15

20

25

30

s=chirp(0:49,0,49,0.1)

Page 12: Matched filter detection

Example

Transmit a Chirp of length N=50 samples, with SNR=0dB

0 50 100 150 200 250 300-2

-1.5

-1

-0.5

0

0.5

1

1.5

2

0 200 400 600 800 1000 1200-15

-10

-5

0

5

10

15

20

25

30

Transmitted Detected with

Matched Filter

Page 13: Matched filter detection

Example

Transmit a Chirp of length N=100 samples, with SNR=0dB

0 50 100 150 200 250 300-2

-1.5

-1

-0.5

0

0.5

1

1.5

2

0 200 400 600 800 1000 1200-20

-10

0

10

20

30

40

50

Transmitted Detected with

Matched Filter

Page 14: Matched filter detection