DSP Project Project Done By

Istiak Mahmood Ayon ID: 021101005

Shahrin Ahammad Shetu ID: 021101027

SONAR APPLICATION

What is Sonar ?Sonar is a technique that uses sound propagation to navigate, communicate with or detect objects on or under the surface of

the water.

How Sonar works: Sonar uses a sound transmitter and a

receiver. Sonar creates a pulse of sound, and then listens for the reflections (echo) of the pulse. To measure the distance to an object, the time from transmission of a pulse to reception is measured and converted into a range (distance) by knowing the speed of sound.

Project Task:In this project we are given two Sonar signals (transmitted signal x(n) and received signal y(n) . At first the received signal y(n) is

passed through a band pass filter to remove noise and interference. Then, the filtered signal is cross-correlated with the transmitted signal x(n) to find the lag for the maximum similarity.

From this lag L, the distance of the object can be estimated.

x(n)

y(n) y2(n)Band Pass Filter

Cross Correlation Lag, L

Plot of x:Transmitted signal x(n)

FFT of x:The Fast Fourier of the transmitted signal

x(n).

Frequency domain representation of x both magnitude and phase.

1) Magnitude response (dB)2) Phase response (degree)

Plot of y:Received signal y(n).

Frequency domain representation of x both magnitude and phase.

1) Magnitude response (dB)2) Phase response (degree)

FFT of y:The Fast Fourier of the received signal y(n).

Bandpass IIR (Chebyshev-1) filter:For filtering the receive signal y(n), as it has noise and

interference of other sound sources .

Frequency Response:

Frequency response of Bandpass IIR (Chebyshev-1) filter.

Impulse response:Impulse response of Bandpass IIR (Chebyshev-1) filter

Plot of y2:y2 is the signal that we gain from filtering

the received signal y(n).

FFT of y2The Fast Fourier of the received signal y2.

Frequency domain representation of y2(n) (both magnitude and phase:

1) Magnitude response (dB)2) Phase response (degree)

Cross correlation:The filtered signal is cross-correlated with the transmitted signal x(n) to find the lag for the maximum similarity. From

this lag L, the distance of the object can be estimated.

CalculationHerer=distance of the object.t=time between the transmission and reception.v=velocity of sound (in water).L=LagDistance, r = v*t/2GivenSampling frequency Fs = 10KHzVelocity of sound in water is v = 1,481m/s.The time between transmission and reception can be calculated from the lag L (t=L/Fs).

Code for distance measurement:L=1.21*10^4; Fs=10^4;t=L/Fs; v=1481; r=(v*t)/2 Ans:The distance ‘r’ is :-r = 896.0050

Matlab Code for the Project: clc; plot(x) %Plot of transmitted signal x(n) figure,freqz(x) %Frequency response of x(n) X=fft(x); figure,plot(abs(X)) figure,plot(y) %Plot of received signal y(n) figure,freqz(y) %Frequency response of y(n) Y=fft(y); figure,plot(abs(Y)) [b,a]=SOS2tf(SOS,G); y2=filter(b,a,y); %filter calling. figure,plot(y2) % plot of filtered signal y2(n) figure,freqz(y2) %Frequency response of y(n) Y2=fft(y2); figure,plot(abs(Y2)) n0=1:length(x); % cross co-relation of transmitted n2=1:length(y2); % signal x(n) and filtered signal y2(n) [x1,n1]=sigfold(x,n0); [z,n]=conv_m(x1,n1,y2,n2); figure,plot(n,z)

Thank You All