1. INTERNATIONAL JOURNAL OF ELECTRONICS AND
International Journal of Electronics and Communication Engineering & Technology (IJECET), ISSN
0976 – 6464(Print), ISSN 0976 – 6472(Online) Volume 4, Issue 2, March – April (2013), © IAEME
COMMUNICATION ENGINEERING & TECHNOLOGY (IJECET)
ISSN 0976 – 6464(Print)
ISSN 0976 – 6472(Online)
Volume 4, Issue 2, March – April, 2013, pp. 137-143
IJECET
© IAEME: www.iaeme.com/ijecet.asp
Journal Impact Factor (2013): 5.8896 (Calculated by GISI) ©IAEME
www.jifactor.com
PERFORMANCE ANALYSIS OF RADAR BASED ON DS-BPSK
MODULATION TECHNIQUE
Ami Munshi1, Srija Unnikrishnan2
1
(Watumull Instiute of Electronics and Telecommunication Engg and Computer Technology,
University of Mumbai, India)
2
(Fr Conceicao Rodrigues College of Engg, University of Mumbai, India)
ABSTRACT
Radar (Radio Detection and Ranging) systems are widely used now-a-days as
automotive radar for Intelligent Transport System (ITS). In this paper we mainly focus on
analyzing the performance short distance radar based on spread spectrum technology. Spread
spectrum modulation technique is chosen as it has some significant properties like accuracy
of ranging, sensitivity, accuracy of power-estimation, interference suppression etc. The
system is implemented in Matlab/Simulink.
Keywords: DSSS, BPSK, Spread Spectrum, BER
I. INTRODUCTION
The electronic principle on which radar operates is very similar to the principle of
sound-wave reflection. If you shout in the direction of a sound-reflecting object, you will hear
an echo. If you know the speed of sound in air, you can then estimate the distance and general
direction of the object. The time required for an echo to return can be roughly converted to
distance if the speed of sound is known [[1]][[2]].
In this paper, we focus on analyzing a radar system based on direct sequence spread
spectrum modulation technique. The goal is to detect target at a very short distance as near as
20cm with high resolution. The system is developed in Matlab/Simulink. Simulink is a
software package for modeling, simulating, and analyzing dynamic systems at any point. The
performance is evaluated using Monte Carlo Simulation method.
Section 2 gives details of DS-BPSK Radar model. Section 3 gives simulation results
followed by conclusion in section 4 and references.
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2. International Journal of Electronics and Communication Engineering & Technology (IJECET), ISSN
0976 – 6464(Print), ISSN 0976 – 6472(Online) Volume 4, Issue 2, March – April (2013), © IAEME
II. IMPLEMENTATION OF DS-BPSK RADAR
DIRECT SEQUENCE SPREAD SPECTRUM MODULATION
Spread spectrum is transmission technique in which pseudo noise code, independent
of the data is employed as spread the signal energy over a bandwidth much greater than
information signal bandwidth. At the receiver, signal is despread using replica of pse
pseudo
noise code generator [[3]].
In DSSS the spreading of the signal bandwidth occurs at baseband by multiplying the
baseband data pulses with a chipping sequence. This chipping sequence is a pseudo
chipping pseudo-random
binary waveform with a pulse duration of Tc and a chipping rate of Rc=1/Tc. Each pulse is
called a chip and Tc is the chip interval. For a given information symbol of duration Ts and a
symbol rate of Rs=1/Ts, the duration of each chip is much less than the pulse length of the
=1/Ts,
information symbol (i.e., Tc<<Ts) and Rc is much higher than the symbol rate (i.e., Rc>>Rs)
than Rc>>Rs).
In practical systems, the number of chips per symbol must be an integer number with t the
transition of the data symbols and the chips occurring at the same time [[3]][[4]].. The ratio of
[ ]..
chips to symbols is called the spreading gain k or bandwidth expansion factor Be where,
k= Be= Nc= Ts/Tc= Rc/Rs (1)
RADAR MODEL
Fig. 1. Model of Spread Spectrum Radar
Fig.1. shows the basic architecture of radar using spread spectrum modulation
technique. Baseband part of the transmitter section mainly consists of binary data generation,
spreading the data using PN sequence and its modulation (BPSK). By using Bernoulli binary
generator block in the communication tool box of Simulink, we can generate binary data
stream of 250Kbps. By using PN sequence generator block in the communication tool box,
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3. International Journal of Electronics and Communication Engineering & Technology (IJECET), ISSN
0976 – 6464(Print), ISSN 0976 – 6472(Online) Volume 4, Issue 2, March – April (2013), © IAEME
we can generate PN sequence of 9Gbps data rate. By using BPSK modulator baseband block
in the communication tool box, we modulate the spread signal [[5]][[6]][[7]].
[
At the receiver front end, the received signal power is measured calculated using radar range
equation as follows
Prec = Pt G2 λ2σ (2)
(4π) 3 R4
The delay between transmitted and received signal is calculated and accordingly
target range is obtained. The Error Rate Calculator is used at the receiver to calculate Bit
Error Rate (BER). It calculates the error rate as a running statistic, by dividing the total
number of unequal pairs of data elements by the total number of input data elements from one
source. Autocorrelation is the one of the vital part of the system that provides uniqueness to
rce.
this radar system. The first operation of autocorrelation block is bit by bit synchronism of the
received and transmitted signal and then bit by bit multiplied, integrated and dumped. The
integrated
power of the received signal represents the presence of target and the delay of the auto
correlation block represents the target distance from the transmitter [[8]][[9]][[10]
[ [10]].
Fig. 2. Target Model
The target model design is shown in Fig 2. Depending on the target range, the
2.
transmitted signal is delayed and the signal power is attenuated. This signal is then reflected
towards the receiver. In the target, there is a provision made to change target cross section,
target range, and accordingly the reflected power towards the receiver.
receiver
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4. International Journal of Electronics and Communication Engineering & Technology (IJECET), ISSN
0976 – 6464(Print), ISSN 0976 – 6472(Online) Volume 4, Issue 2, March – April (2013), © IAEME
III. SIMULATION RESULTS
Various graphs are plotted by using following data in the model:
Chip rate (fc) 1Gbps
Transmitted Power (Pt) 1W
Antenna Gain 100
Wavelength(λ) 0.3m
Target Cross Section (σ) 1m2
Minimum detectable signal 0.011mW
power (Pmin)
Velocity of light (c) 3x108m/s
Maximum Radar Range 8m
(Rmax)
Table. 1. Specifications of Spread Spectrum Radar
EB/NO VERSUS BER
For range (R) = 1m, Eb/No Vs BER graph is plotted using Bit Error Rate Analysis
Tool in Matlab/Simulink. Monte Carlo simulation results and theoretical results are in Fig.3.
below. We can see that as Eb/No ratio increases, BER decreases.
Fig. 3. Eb/No versus BER graph
RANGE VERSUS SIGNAL POWER
As radar range increases, the signal power received at the receiver decreases. The
minimum detectable signal power at the receiver Pmin= 0.000110726W or -39.55dB for
Rmax =8m. Fig.4. shows the graph of range versus received signal power.
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5. International Journal of Electronics and Communication Engineering & Technology (IJECET), ISSN
0976 – 6464(Print), ISSN 0976 – 6472(Online) Volume 4, Issue 2, March – April (2013), © IAEME
Fig. 4. Range versus Received Power graph
CHIP RATE VERSUS MAXIMUM RANGE
Relation between chip rate and maximum radar range is given by the following
equation.
Rmax= (Pt G2 λ2 σ) ¼ (3)
((4π) 3 Pmin) 1/4
where, λ = c/fc
where, c = 3e8 m/s, velocity of light
We see that as the chip rate increases, the maximum range of detection decreases.
Fig.5. portray this relation.
Fig. 5. Chip Rate versus Maximum Range graph
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6. International Journal of Electronics and Communication Engineering & Technology (IJECET), ISSN
0976 – 6464(Print), ISSN 0976 – 6472(Online) Volume 4, Issue 2, March – April (2013), © IAEME
THEORETICAL DISTANCE VERSUS COMPUTED DISTANCE
Fig.6. shows the graph of theoretical distance of the target and the distance computed
by the radar receiver model.
Fig. 6. Theoretical Distance versus Computed Distance graph
IDENTIFICATION OF TARGET
Fig. 7. Detection of Target of σ = 1m2 at range 4m
Fig.7. shows the target of σ= 1m2at 4m range. The received signal power at the
=
receiver is (-26.52dB). In the figure X-axis represents the target range in meters where as Y
26.52dB). X Y-
axis represents the received signal power in dB. Here distance of the target is calculated by
calculating the relative time delay between the received signal and transmitted signal.
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7. International Journal of Electronics and Communication Engineering & Technology (IJECET), ISSN
0976 – 6464(Print), ISSN 0976 – 6472(Online) Volume 4, Issue 2, March – April (2013), © IAEME
IV. CONCLUSION
The work presented here gives design, implementation and analysis of radar transmitter-
receiver using Matlab/Simulink. With chip rate of fc=1 GHz and target cross section σ=1m2 this radar
model is based on radar range equation to detect maximum range of 8m and minimum range of 20cm.
The peculiarity of this radar is that it is able to detect objects placed at a very short distance. The
performance is examined using Monte Carlo simulation. It is observed that the system is more
accurate in computing the distance of the target towards the maximum range. It is also noted that as
the signal to noise ratio (Eb/No) increases the Bit Error Rate (BER) decreases. We can vary the
detection range by changing the chip rate. There is also a provision for changing target cross section
and antenna gain and accordingly the detection range can be varied. In this work, autocorrelation is
one of the vital parts of the system that provides uniqueness to this radar system. The auto correlated
value obtained from the align signal block represents the presence of target and the delay represents
the target distance from the transmitter. The technology uses DS-BPSK signals to create noise like
modulation, making the transmitted signal virtually undetectable to other receivers. The system
developed has virtues such as high reliability, robustness, good efficiency, interference suppression,
low power consumption etc., due to coding of the baseband pulses with PN sequence.
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