MTechProjectPhase-2

8/10/2019 MTechProjectPhase-2

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Dayananda Sagar College of EngineeringCenter for Post Graduation Studies

Department of Electronics and Communications Engineering

Project Seminar MTech Project Phase 3

Project Title : EVALUATION OF POLYPHASE FFTARCHITECTURE FOR PULSE DETECTION AND MEASUREMENT

Student Name : JEEVITHA T (1DS12LEC06)

Internal Project Guide: External Project Guide:Prof. Kiran Gupta Hemanth Vasant ParanjapeECE dept,DSCE Scientist E, DARE,DRDO


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Title of the Project

Problem statement

Time of Arrival(TOA) PDW parameter that assigns a time tag to the leading edge of

a received pulse at the receiver input.

For a digital EW receiver, the spectrum estimator (normally an FFT) is usually

the limiting factor in update rate due to its computational complexity.

update rate 1/ frequency resolution.

Consider a monobit receiver:

256 samples at 2.56GHz TOA resolution 100ns.

with 50% overlap at the same Fs TOA resolution 50ns

increasing the number of FFTs.


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Phase 1 ReviewPhase 1 Review

Receiver considered is a Multi-bit Electronic Warfare Receiver

Receiver consists of a decimation filter and FFT block along with an encoder thatoutputs the PDW(Pulse Descriptor Words).

The shaded block is realized as a polyphase DFT which uses decimation in frequencydomain.


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objective

the proposed method to increase the TOA resolution is to use decimation in the

frequency domain.

implement the decimation in frequency domain through a channelised polyphase

filtering method.

incorporate the channelised polyphase filtering method in the receiver model.


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Frequency Channelization

Filter bank:


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Polyphase Structure for FFT filter bank

USN: 1DS12LEC06 6


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Decimation filter design process:

STAGE 1: FFT filter bank

rectangular window in time domain sinc function in frequency domain

filter shape is not desirable

sidelobes are very high

Weighing function can be used in time domain

the detailed response of the single filter and the filter bank is as shown


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USN: 1DS12LEC06 8


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Continued..

STAGE 2 : Decimated FFT filter BankALGORITHM: Decimation in Frequency Domain:

Step 1:

Step 2:


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Step 4:

Step 5:


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Step 6:


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Results:

USN: 1DS12LEC06 13


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Continued..

Stage 3: Windowed Decimated FFT filter Bank

To widen the individual filters and also suppress the sidelobes a window is appliedto the input data.

The corresponding effect in the frequency domain is the wide bandwidth of eachindividual filter shape in the filter bank.

ALGORITHM:

Step 1:

Step 2:


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Continued..

Step 3:

Step 4: 32 point FFT is performed on these y values , 16 individual filters aregenerated.


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Window function generated using an FDATOOL

Design Parameters:

N=256; M=8; 1= 0.01; 2=0.001; fs=3000MHz;Fp =fs/(N/M) ; Fs = 2*Fp;

USN: 1DS12LEC06 16


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Continued..

Step 1:

Step 2:

Park Mc- Clellans Criteria:


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Advantages of Polyphase Filtering

First, by parallelizing the filter through polyphase decomposition, the sampling rate of

each individual filter is reduced by a factor of 1 /D, where D is the number of filters.

A second significant advantage to using the channelized polyphase filtering

method is an increase in time resolution, which improves the TOA and PW calculations

in an EW receiver.


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Comparison:

USN: 1DS12LEC06 21


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Remaining Work:

incorporate the filter designed into the receiver model

Generate the test signals

perform various processing such as:

Deinterleaving

PRI generation

Tracking

PDW generation

GUI design in MATLAB.


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MATLAB simulation

Generation of the input signals:

FILE NAME DESCRIPTION

Known_pattern.m Accepts the number of pulses transfers the control test_case_generator.

Outputs the details of the input info.txt

Test_case_pattern.m Provides the user a platform to enter the details of the inputpattern.Transfers the control to cw_generator.m depending on theuser entries.

Cw_generator.m Used to generate cw pulses.

Info.txt Contains the details of the input signal.


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COMPLETE_MODEL.M ALGORITHM

1. The input data/ samples are stored in samples.txt

2. Grouping of the data begins :P = length(A);P = P - mod(P,256);L = (P/N);

where A is a variable which contains the imported data (samples.txt)

3. Design an equiripple low pass FIR filter with the following parameters: Fs=1350MHz Fp=21.09375MHz Fs=42.1875MHz Wp=1/64 Ws=1/32

Fdatool is used to generate the filter co-efficients.


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Samples(14080)

L21

1 2 3256

P= P- mod(P,256) Mod(x,y)= x-n.*yn = floor(x./y)


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Continued.

4. Decimation in the frequency domain is applied on the incoming data:

Let x(n) be the input, h(n) be the filter co-efficients :

5. Calculate the 32 point FFT of the processed data.


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Peak detection:

6. Calculate the first peak(maximum) using


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Continued

THANK YOU

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