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International Journal of Advanced Research in Electronics and Communication Engineering (IJARECE)

Volume 4, Issue 4, April 2015

1032 ISSN: 2278 – 909X All Rights Reserved © 2015 IJARECE

Simulation and Extraction of Radar Signal

Parameters using Digital Signal Processor

D Priyanka1, Ch Viswanadham

2, Afroz

3

1Student, M. Tech, Department of ECE,

Vasavi College of Engineering, Osmania University, Hyderabad, India – 530003

2Senior Deputy General Manager, Bharat Electronics,

IE, Nacharam, Hyderabad, India – 500076

3Assistant Professor, Department of ECE,

Vasavi College of Engineering, Osmania University, Hyderabad, India – 530003

Abstract: Modern Electronic Warfare (EW)

systems are built with state of the art electronic circuits

and complex algorithms, are installed on different

varieties of military platforms that guard country’s

security continuously. These systems use complex

analogue and digital hardware along with many signal

processing algorithms. The paper involves the

development algorithms for the existing DSP hardware

for extraction of radar signal parameters. The

parameters are modulation type, inter and intra pulse

characteristics, statistics of the signal characteristics on

pulse and sample basis. The inter pulse characteristics

include linear frequency modulation-up chirp, down

chirp, Baker codes intra pulse characteristics include

stagger and jitter. The modulations, various DSP

processors and signal processing algorithms to extract

the radar parameters, development of software in

MATLAB and simulation in System Vue. The

developed hardware and software has to be tested and

verify for the input signal parameters that are

generated by radar simulator using software called IP

Analysis Tool. The entire work is carried out simulation

mode, before verifying on the target PCB.

Keywords: Inter pulse, Intra pulse, Barker, LFM,

Stagger, Jitter

I. INTRODUCTION

Modern Electronic Warfare (EW) systems are built

with state of the art electronic circuits and complex

algorithms, are installed on different varieties of

military platforms that guard country’s security

continuously. Three armed forces are equipped

with modern EW systems that are capable of

detecting, measuring, identifying, classifying,

analyzing, threat prioritizing and jamming of wide

variety of hostile radars including complex Low

probability of Intercept (LPI) radars used in

military applications. EW systems are wide open

systems in frequency, space and parameters and

hence EW system functionality is complex. The

operational requirements of these systems are keep

changing rapidly, due to faster advancements in

radar technologies related to antennas, signal

processing, communications, variety of

modulations, networking, software, installation,

multi role of today’s platforms & unpredictable

environmental conditions in the field. In fact, EW

systems are Ultra Wide Band (UWB) Systems.

The main functions of EW system is to receive,

measure & identify the electromagnetic waves

radiated by radars around it and create an

intentional interference in the enemy’s

electromagnetic (EM) environment. Thus the

capability to measure the parameters of the various

radar signals and effectiveness of jamming

techniques against all types of radars signals are the

key performance factors of an EW system. ESM is

part of EW and shall measure and analyze the

parameters of the EM signals radiated by radars

before they were analyzed by radars available

across the world. To achieve this task, the ESM

system capabilities like antenna performance,

detection capabilities, parameter measurement

techniques & accuracies, operational sensitivity,

processing speed & capability to analyse complex

radar waveforms are very much important. The

detection, measurement and processing capability

of ESM systems are characterized by type of

receiver (analogue, digital, wide open and / or

narrow band), Processor, Software & associated

antennas. Hence measurement and analysis of

radar parameters plays major role in ESM systems.

Digital Signal Processing (DSP) is one of the best

suitable fields for extraction of radar signal

characteristics in modern ESM systems.

II. BLOCK DIAGRAM OF ESM

RECEIVER FOR SIGNAL ANALYSIS

The block diagram of signal analysis receiver is

shown in Figure2.1-.




Figure - 2.1: Block diagram of Signal analysis

receiver

The principle of operation of the receiver depends

on the use of frequency mixing. The signal from

the antenna is filtered sufficiently at least to reject

the image frequency and amplified. A local

oscillator in the receiver produces a sine wave,

which mixes with that signal, shifting it to a

specific intermediate frequency (IF), usually a

lower frequency. The IF signal is itself filtered and

amplified and possibly processed in additional

ways. The demodulator uses the IF signal rather

than the original radio frequency to recreate a copy

of the original information. The following essential

elements are common: a receiving antenna; a tuned

stage, which may optionally contain amplification

(RF amplifier); a variable frequency local

oscillator; a frequency mixer; a band pass filter

and intermediate frequency (IF) amplifier; and a

demodulator plus additional circuitry to (or other

transmitted information). The speciality of this

receiver is usage of digital receiver. The down

converted IF (750 to 1250 MHz) is sampled with

1.3 Giga samples / sec ADC for In-phase and

Quadrilateral phase format and is given to Digital

signal processor PCB. The PCB is embedded with

digital processor which provides the signal

characteristics in detail. The software in DSP does

the analysis and presents the data for GUI.

2.1 INTRODUCTION TO INTER AND INTRA

PULSE

Each radar is built with some descriptive

characteristics such as modulation type, scan type,

pulse repetition interval (PRI) pattern and

polarization. Modern radars have complex signal

processing algorithms.

PRI is the time duration that passes between the

transmissions of two consecutive pulses of radar.

PRI determines the maximum range at which the

radar can make unambiguous range measurements.

Constant, Staggered, Dwell-and-Switch and Jittered

PRIs are among the types of PRI patterns..

Depending on the complexity of the radar system,

various kinds of modulations can be applied to the

pulse train. There are two basic types of

modulation inter pulse and intra pulse.

Inter pulse modulations refer to variations seen on

the PRI, Frequency, and Amplitude or Angle of

Arrival values between pulses. In other words, inter

pulse modulations separate the radar pulses from a

fixed PRI, constant pulse radar. Inter pulse

modulation helps the radar reduce range

ambiguities. This is due to the fact that echo of

each pulse must be received by the radar before a

new pulse is transmitted. Hence, modifying the PRI

of the radar, one can improve the maximum range

that a specific target can be detected. Another point

is that, Radio Frequency (RF) Jammers usually

save the pulse received from radar and then sends it

back to that radar at an unexpected time to make

the radar misunderstand the location of the target.

For this reason, if inter pulse modulation is applied

on the radar signal, this will help the radar to

distinguish between a real echo-signal and a

synthetic one, improving the anti-jamming

characteristics of the radar.

The second type of modulation applied on radar

signals is the intra pulse modulation, or Intentional

Modulation on Pulse (IMOP). IMOP radars, also

named as Pulse Compression Radars, apply

intentional changes in the amplitude, frequency or

phase of the generated pulse. In other words,

instead of the pulse being a burst of RF energy at a

given carrier frequency, the pulse is a form of RF

energy at a carrier frequency that varies in phase

(PMOP), frequency (FMOP), or amplitude

(AMOP). Intra pulse modulation techniques make

it possible to simultaneously maximize the target

range, the range resolution, and the velocity

resolution of the radar.

2.2 Intra-pulse modulations

Intra pulse modulations are classified according to

the part of the signal where modulation is applied.

Mainly, they can be grouped as:

2.3 Amplitude modulation on pulse modulations

As the name implies, in this type of signals, the

Amplitude of the signal is intentionally modulated

while the Frequency or Phase of the signal is kept

constant. These modulation shapes can be mainly

divided into two groups as; Linear AMOP and

Nonlinear AMOP. Modulation shapes such as

Parabolic, Sinusoidal, Ramp, Triangular, and

Square may be counted as Nonlinear AMOP types.

2.4 Frequency modulation on pulse

In this class of signals, Amplitude is kept constant,

and intentional modulation is applied on the

Frequency component of the radar signal. FMOP

modulation types are mainly divided into two

groups as; Linear FMOP and Nonlinear FMOP.

http://en.wikipedia.org/wiki/Frequency_mixer

http://en.wikipedia.org/wiki/Superheterodyne_receiver#Image_frequency_.28fimg.29

http://en.wikipedia.org/wiki/Local_oscillator



http://en.wikipedia.org/wiki/Intermediate_frequency

http://en.wikipedia.org/wiki/Demodulator

http://en.wikipedia.org/wiki/Antenna_(radio)





http://en.wikipedia.org/wiki/Intermediate_frequency




Linear FMOP signals are also named as “Chirp”

signals. Modulation shapes such as Parabolic,

Sinusoidal, Ramp, Triangular, Square and FSK

may be counted as Nonlinear FMOP types.

Frequency Modulation is applied to the signals so

that Pulse Compression is achieved and the

Ambiguity diagram is approximated to the ideal

case.

2.5 Phase modulation on pulse

Phase Modulation on Pulse is another method for

Pulse Compression. In this modulation type, Phase

of the signal is modulated depending on a binary

code, while the Amplitude of the signal is kept

constant.

2.6 Linear frequency modulation

This technique is dominantly used for narrow band

operations .In this case, pulse compression is

accomplished by adding frequency modulation to a

long pulse at transmission, and by using a matched

filter receiver in order to compress the received

signal. Using LFM with in a rectangular pulse

compresses the matched filter output by a factor,

which is directly proportional to the pulse width

and bandwidth. Thus, by using long pulses and

wideband LFM modulation we can achieve large

compression ratios. This form of pulse compression

is known as “correlation processing” .LFM pulse

compression technique is a kind of technique in

which the frequency of the transmitted signal is

varied over pulse duration of T. This variation of

the frequency from low to high or vice a versa is

known as “chirping”. Changing the frequency from

low to high is called “up-chirp” or upsweep.

Similarly, changing the frequency from high to low

is called “down-chirp”. The technique of applying a

different chirp rate for each pulse is known as

“chirp diversity”. One of the combined modulation

techniques is that used in radars and called LFM.

[5]

2.7 Rectangular RF Pulse with LFM

Commonly, a carrier signal with simultaneous

amplitude and angular modulation is written as

y(t) = A(t) cos [ω0( t) + ψ(t)]

Where the AM function A(t) and PM function ψ(t)

may be either harmonic or complex. If AM is

performed with a rectangular pulse and PM is due

to FM, then the RF single pulse may be sketched as

in Fig.2.4. Here, the frequency ω(t) is modulated

with a linear law having a deviation ±∆ω/2 around

the carrier frequency ω0 .

A generalized form is

y(t) = A(t) cos Ψ(t)

Figure-2.2: Rectangular Linear Frequency

Modulation

where the total phase Ψ(t) is determined by the

integral relation

in which ω(t) is given with the linear FM law

Where the co-efficient α defines the rate of LFM

allowing ψ0 = 0, the phase function becomes

Where α is determined by the deviation of

frequency ∆ω and duration τ as

a rectangular LFM pulse may be written as

Figure-2.3. a) Up-Chirp and b) Down-Chirp[1]

2.7 Barker Code

A Barker code is a sequence of N values of +1 and

−1, aj for j=1, 2..., N such that

The Barker code is a short sequence and popular




for radar applications. The Barker codes have

different sequence lengths. The side lobes

generated from the autocorrelation of the Barker

code have constant amplitude. The maximum

length of a Barker code is limited to 13.

Consequently, a binary Barker sequence has

elements ai {−1, +1}, which are only known for

lengths Nc = 2, 3, 4, 5, 7, 11, and 13.. The longest

code is of length Nc=13. The nine sequences are

listed where a +1 is represented by a + and a −1 is

represented by a −. It has been shown that binary

Barker sequences with lengths greater than 13,

with Nc odd, do not exist. [4]

Figure-2.4: Representation of Barker code

Figure-2.5 Barker Code Graphical Representation.

III INTER MODULATION

By using PRI modulation recognition in ESM

systems, the process of recognizing the radars can

be developed. Common types of PRI modulation

are constant, jittered, staggered, sliding, wobulated

and DS (Dwell and Switch). In conventional

methods, constant and staggered PRI modulations

are recognized in pulse de-interleaving process

.The modern ELINT systems may measure modulations of PRI and RF with a very high precision. If the variations occur on pulse or from pulse to pulse or from pulse group to pulse group, they are considered fast. If they occur from scan to scan or over longer periods, they are considered slow. PRI is the interval from start of one pulse to the start of the next pulse. These are radars with: PRI stable, PRI sliding, PRI dwell and switch, PRI stagger, PRI jitter.

Figure-3.1 Pulse Waveform

3.1 STAGGER PRI

PRI stagger is the use of two or more PRIs selected

in a fixed sequence. The sequence may contain

more than one of the several intervals before it

repeats. The sequence is described by the number

of “positions” or intervals used in making up the

sequence and the number of different intervals

used. A common stagger sequence consists of

altering long and short PRIs. This has two intervals

and two positions. [3]

3.2 JITTER PRI

A parameter PRI is considered to be a jittered if the

variations from the mean PRI occur in a random or

pseudorandom fashion. PRI jitter variations can

occur between minimum and maximum PRI limits

or can be variations from a mean value using

discrete values. [2]

IV MATLAB IMPLEMENTATION

The MATLAB implementation of the some of the

above modulations is given below:

4.1 MATLAB Code for Barker 3

clc;

close all;

clear all;

n=0;

pulse_on = 1; % flag to switch

on/off pulses

for i=1:2;

t1=n+0:0.1:n+1.5;

t2=n+1.5:0.1:n+3.25;

t3=n+3.2:0.1:n+4.84;

if(pulse_on == 1)

A = 2;

else

A = 0;

end

w=A*pi*500/800;

z1=A*(sin(w*t1));

z2=A*(sin(w*t2));

z3=A*(-sin(w*t3));

n=max(t3);




z=plot(t1,z1,t2,z2,t3,z3);

if(pulse_on == 1)

pulse_on = 0 ;

else

pulse_on = 1 ;

end

hold on;

end

xlabel('time');

ylabel('phase');

title('Barker3');

Figure - 4.1 MATLAB Implementation of Barker code 3

4.2 MATLAB IMPLEMENTATION FOR

BARKER 7

clc;

close all;

clear all;

n=0;

pulse_on = 1;

for i=1:4;

t1=n+0:0.1:n+2.5;

t2=n+1.5:0.1:n+3.25;

t3=n+3.19:0.1:n+4.84;

t4=n+4.8:0.1:n+6.45;

t5=n+6.4:0.1:n+8;

t6=n+8:0.1:n+9.5;

t7=n+9.5:0.1:n+11.2;

if(pulse_on == 1)

A = 2 ;

else

A = 0 ;

end

w=2*pi*500/800;

z1=A*(sin(w*t1));

z2=A*(sin(w*t2));

z3=A*(sin(w*t3));

z4=A*(-sin(w*t4));

z5=A*(-sin(w*t5));

z6=A*(sin(w*t6));

z7=A*(sin(w*t7));

n=max(t7);

z=plot(t1,z1,t2,z2,t3,z3,t4,z4,t5,z5,t

6,z6,t7,z7);

if(pulse_on == 1)

pulse_on = 0;

else

pulse_on = 1 ;

end

xlabel('time');

ylabel('phase');

title('Barker7');

hold on;

end

Figure-4.2 MATLAB Implementation of Barker code 7

4.3 MATLAB IMPLEMENTATION FOR LFM

(DOWN-CHIRP) clc;

clear all;

close all;

t =-4:0.02:0;

f0=input('fundamental frequency f0 =

');

k =input('slope K = ');

f =f0+k*t;

phase=360;

amplitude=2;

s1=amplitude*cos(2*pi*f.*t+phase);

subplot(5,1,1)

plot(t,f)

xlabel('time');

ylabel('frequency');

title('Linear Frequency Modulation');

subplot(5,1,2);

plot(t,s1)

xlabel('time');


title('Down chirp');

array_frequency=[f];

disp(array_frequency)

subplot(5,1,3);

stem(t,array_frequency);

array_phase=[phase];

disp(array_phase);

subplot(5,1,4);

plot(t,array_phase);

xlabel('time');

ylabel('phase');

title('phase plot');

array_amplitude=[amplitude];

disp(array_amplitude);

subplot(5,1,5);

plot(t,array_amplitude);

xlabel('time');

ylabel('amplitude');

title('amplitude plot');




Figure-4.3 MATLAB Implementation of LFM-Down

Chirp

4.4 MATLAB IMPLEMENTATION FOR LFM

(UP-CHIRP) clc;

clear all;

close all;

t =0:0.02:4;

f0=input('fundamental frequency f0 =

');

k =input('slope K = ');

f =f0+k*t;

phase=0;

amplitude=2;

s1=amplitude*cos(2*pi*f.*t+phase);

subplot(5,1,1)

plot(t,f)

xlabel('time');


title('Linear Frequency Modulation');

subplot(5,1,2);

plot(t,s1)

xlabel('time');


title('Up chirp');

array_frequency=[f];

disp(array_frequency);

subplot(5,1,3);

stem(t,array_frequency);

array_phase=[phase];

disp(array_phase);

subplot(5,1,4);

plot(t,array_phase);

xlabel('time');

ylabel('phase');

title('phase plot');

array_amplitude=[amplitude];

disp(array_amplitude);

subplot(5,1,5);

plot(t,array_amplitude);

xlabel('time');

ylabel('amplitude');

title('amplitude plot');

Figure-4.4 MATLAB Implementation of LFM-Up Chirp

4.5 SYSTEMVUE SIMLULATION OF STAGGER:

Figure-4.5 Simulation of Stagger

Figure-4.6 Output of Stagger.

4.6 SYSTEMVUE SIMULATION OF JITTER :

Figure-4.7 Simulation of Jitter

Figure-4.8 Output of Jitter




V EXTRACTION OF SIGNAL PARAMETERS

The signals are analysed by using Offline analysis

tool. It is used for extraction of the Intra pulses and

their analysis. The purpose of this analysis is

Automatic & Manual classification.

Including LPI radars detection &

classification

5.1 Opening an IP file:

IP files: Files which have not been

analyzed using the IP analysis tool.

Results files: Files containing

modifications or work carried out by

the Operator.

Screen of intra pulse is divided into 6 parts:

1. Menu Area window

2. Graphical Window

3. File description window

4. IP Sample table window

5. More Information window

Figure-5.1 IP Analysis of Barker 5

Figure-5.2 IP Analysis of LFM Down-Chirp

5.1 DSP PCB Module

Figure-5.2: FPGA based DSP BOARD#

5.2 FLOWCHART FOR EXTRACTION

Figure-5.3 Flow Chart of LFM and Barker Code

Figure -5.4 :Flow Chart for Stagger and Jitter

5.3 COMPARISON OF MATLAB AND

EXTRACTED MODULATIONS

The output of the MATLAB simulation in a file is

provided to extraction algorithm developed as input

and the characteristics of the original signal are




observed as the classification output for different

varieties of signals. This shows the algorithms are

satisfactory and results are comparable. The tests

are done for Barker, Chirp Down modulations.

VI CONCULSION

In this paper, the finger printing of modulated

signals of various types have been analysed and

suitable algorithms have been developed to extract

these radar signal parameters. To verify these

characteristics, initially MATLAB CODE is

developed and analysed through the simulations,

which are presented in the paper. Also, the

simulation is done for extraction of characteristics

of the samples using DSP algorithms is carried out

and presented in the paper. Hence, the simulation

of Inter and intra pulse characteristics and

extraction of the same has been carried out and

presented in the paper. The same work can be

further carried out by much complex signals like

Huff-man code, etc.,.

VII REFERENCES

[1]http://www.ijetae.com/files/Volume4Issue4/IJ

ETAE_0414_18.pdf

[2] Richard G. Wiley “The analysis of radar

signals” Chapter 8 page no 150

[3] Richard G. Wiley “The analysis of radar

signals” Chapter 8 page no 154

[4] http://en.wikipedia.org/wiki/Barker_code

[5] J.C.Toomay,Paul J.Hannen “Radar Principles

for the Non-Specialist” Third edition.

VIII BIO DATA OF AUTHOR

Devarapalli Priyanka completed her

schooling and Intermediate in Hyderabad,

Telangana .She has done her B.Tech from Swami

Vivekananda Institute of Technology near

Secunderabad from the stream Electronics and

Communication Engineering. Presently pursuing

M.E (Communication and Signal Processing) from

Vasavi College of Engineering .At present she is

doing her project work in Bharat Electronics

Limited, Hyderabad as part of her M.E. curriculum.

Ch Viswanadham, born in

Ampolu, a village in suburbs

of Srikakulam, Andhra

Pradesh, India joined Bharat

Electronics Limited, a premier

defence electronics industry in

1990 immediately after B Tech

(ECE) from Nagarjuna

University, Guntur, and

Andhra Pradesh. He worked in various Naval EW

Systems from design to field trails. He has

received internal R&D award for developing light

weight ESM system for Indian Naval Ships. He

has been deputed to Israel, Spain & South Korea to

participate in technical discussions on EW systems

with international companies. He has completed

Master’s degree in Digital Systems from Osmania

University, Hyderabad in 1997, while working at

BEL. Presently he is working as Senior Deputy

General Manager (D&E) and heading RF & MWP

group. He has presented many technical papers in

BEL-House journal, national & international

journals and conferences. He is Fellow of IETE &

IE (I), Life member of SEMCE (I) & CSI and

MIEEE. He is pursuing PhD in Andhra University,

Visakhapatnam. His areas of interest are antennas,

radomes, RF & Microwave designs and wide band

/ narrow band receivers.

SK. Afroz Begum, received the

Bachelor of Technology in Electronics and

Communication Engineering from JNT University

and the Master of Engineering in Systems and

Signal processing from JNTU Hyderabad.

Currently, she is working as Assistant Professor in

the department of Electronics and Communication

Engineering, Vasavi College of Engineering,

Hyderabad. She has presented technical papers in

national & international conferences and attended

many workshops. She is member of IETE. Her

Research interests include DSP processors and

digital image processing.

http://en.wikipedia.org/wiki/Barker_code

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Simulation and Extraction of Radar Signal Parameters using ...ijarece.org/wp-content/uploads/2015/04/IJARECE-VOL-4-ISSUE-4-1032... · Abstract: Modern Electronic ... varieties of