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IOSR Journal of Electronics and Communication Engineering (IOSR-JECE)
e-ISSN: 2278-2834,p- ISSN: 2278-8735.Volume 6, Issue 2 (May. - Jun. 2013), PP 27-30
www.iosrjournals.org
www.iosrjournals.org 27 | Page
Reduction of Side Lobes by Using Complementary Codes for
Radar Application
Dodda.H.V.S.Rami Reddy1
, P.P.M.Krishna2
,K. Ranjith Kumar3
1
second. M Tech Student (DECS), 2
Assoc. professor,3
Asst.professor
Dept of E.C.E, Dr.S.G.I.T, Markapur, Prakasam (Dist),India1
, Dept of E.C.E,S.G.I.T, Markapur2
, Dept of
E.C.E,S.G.I.T, Markapur3
DODDA.H.V.S.Rami Reddy1
, P.P.M.Krishna2
,K. Ranjith Kumar3
1
second. M Tech Student (DECS), 2
Assoc. professor,3
Asst.professor
Dept of E.C.E, Dr.S.G.I.T, Markapur, Prakasam (Dist),India1
, Dept of E.C.E,S.G.I.T, Markapur2
, Dept of
E.C.E,S.G.I.T, Markapur3
Abstract: The analysis of new types of Complementary direct sequence complex signals which have synthesized
with well – know code sequences like Barker, Walsh, Golay, and complementary codes. Build on the
autocorrelation function (ACF) and ambiguity function (AF) of signals, the numerical method estimates the
volume of side lobes separately for each signal. The results obtained show that the signals, which have a low
volume of side lobes, means of approximately zero in by using complementary codes with compare to different
codes.
Keywords: Ambiguity function, complementary codes, autocorrelation function etc.
I. INTRODUCTION
In wireless communication systems such radars radio, TV and navigation systems, electromagnetic
signals are transmitted in the frequency based on the different frequency bands of range from KHz to GHz. In
recent years many authors have published a set of research works related to estimation of ambiguity functions
(AF) of these signals (communication, television or radio), i.e. estimation of the radar properties. It was
concluded that the good characteristics of their ambiguity functions are not always combined with dynamic
range restriction. The usage of such radars is very perspective, but related with many restrictions.
In existing system for radar communication by using the electromagnetic wave is used to find the targets
in the radar receivers by extracting the received signal with the help of barker, Walsh and golay codes are used
to find the location and distance of the target. But here one problem occurred i.e., high side lobes are occurred
in some cases it is dominate the main lobe it causes a (False Alarm).
In proposed system to avoid the side lobes or False alarm by using the new technique i.e., complementary
codes are used instead of barker, Walsh and golay codes to get almost zero side lobes easy to find the target
location and distance from radar.
I .Evaluation of side lobes
In the study, we use the general definition of the following quality factors: Maximal Peak Side lobe
Power (PSP), Peak Side lobe Level (PSL), Integrated Side lobe Level (ISL) and Golay Merit Factor (MF).
These quality factors are often used in order to analyze the volume of signal side lobes at the filter output:
 Max Peak Side lobe Power (PSP) = 1/N - is the maximum amplitude at the filter output , and N is the
code length;
 Peak Side lobe Level (PSL) – is the highest side lobe power level relative to the main lobe:
obepowertotalmainl
bepowerpeaksidelo
PSL log10 … 1.1
 Integrated Side lobe Level (ISL) – is the power distributed in all side lobes and defined as:
obepowertotalmainl
rsidelobesegratedovepower
ISL
int
log10 … 1.2
 The Golay Merit Factor (MF) of binary sequences of length N is given by:
Reduction Of Side Lobes By Using Complementary Codes For Radar Application
www.iosrjournals.org 28 | Page



 1
1
2
2
2
N
k
ka
N
MF … 1.3
 
kii sskN
i
kaAACF


 
1
0
1 , Nk 1
AACF - Aperiodic autocorrelation function. (1.4)
II. EXPERIMENTAL DESCRIPTION
The study is realized by developing the specialized software in Matlab 7.6. This software computes
PSL and ISL of ambiguity functions of signals under study and visualizes the results. The main quality factors
of signals under study are evaluated and visualized. The structure of this software is shown in Fig. 2.1. The
function of computational algorithm includes the following operations: input of the information for the type and
the parameters of codes under study; calculation and normalization of the code autocorrelation function (ACF);
computation of the Merit factor; calculation of PSL and ISL, graphical and numerical visualization of the final
results. In case of complementary codes two codes are applied to the input; in the block for calculation of ACF a
sum of two code’s ACF is computed. In the next block a partial minimization of the volume of the body of
ambiguity is performed resulting into a new matrix, which is normalized (a sum of matrixes in case of
complementary codes). After that the quality factors PSL and ISL of the minimized ambiguity function are
calculated, and, finally, the numerical and graphical results are visualized. The main purpose of this study is to
analyze which of these signals have the better (lower) values of Peak Side lobe Level and Integrate Side lobe
Level.
Fig 2.1: Block diagram of the computational algorithm
For the above computational algorithm is used to find the target location by applying different codes.
The ex-perimental results are the given below in graphical model.
Reduction Of Side Lobes By Using Complementary Codes For Radar Application
www.iosrjournals.org 29 | Page
Fig 2.2.a: Autocorrelation of Walsh sequence.
In the above fig 2.2.a for detecting the target but difficult to analyze that because noise or side lobes
are very high in the Walsh sequence.
The Ambiguity function for the Walsh sequence is also same but it is in 3-dimentional manner here
we find easily the side lobes compare to the Autocorrelation function.
Fig 2.2.b: Ambiguity diagram of Walsh sequence.
In my proposed model by using the complementary codes to overcome the noise occurred in the
Walsh codes. The results for complementary codes are given below.
Fig 2.3.a: Autocorrelation of complementary sequence.
Compare to both autocorrelation’s complementary sequence have almost zero noise. Same for
ambiguity function also is in the given below.
Reduction Of Side Lobes By Using Complementary Codes For Radar Application
www.iosrjournals.org 30 | Page
Fig.2.3.b:Ambiguity diagram of complementary sequence
III. Conclusion
Based on the results obtained, we conclude that the complementary codes have the best characteristics
ACF and MAF in comparison with all the rest codes. The results are obtained by the software Matlab R2011a.
This confirms that at the present time and in the future the complementary codes can be successfully used in
passive radar systems.
REFERENCES
[1]. M. J. E. Golay, "Complementary Series, „ IEEE Trans Info. Theory, vol. IT-7, 1961, pp 82-87.
[2]. R. Turyn, "Ambiguity Function of Complementary Sequences, „ IЕЕЕ Trans. Info. Theory, vol. IT-9, Jan. 1963, pp. 46-47.
[3]. N. Suehiro, "Complete Complementary Code Composedof NMultipleshift Orthogonal Sequences, „ Trans. /ЕICЕ (in Japanese), vol.
J65-A, Dec. 1982, pp. 1247-53.
[4]. N. Suehiro and M. Hatori, "N-Shift Cross-OrthogonalSequences, „ IEEE Trans. Info. Theory, vol. IT-34, no. 1, Jan. 1988, pp. 143-
46.
[5]. Cherniakov M., Kubik M.: “Secondary applications of wireless technology (SAWT)”, 2000 European Conference on Wireless
Technology – Paris 2000
[6]. Price R., E. Hofstetter, “Bounds on the Volume and Height Distributions of the Ambiguity Function”, IEEE Transactions on
Information Theory, April, 1965.
[7]. D.B. Vakman and R. M. Sedletskii, “Problems in Synthesis of Radar Signals”. Soviet Radio, Moscow, 1973 (in Russian).
[8]. D.E. Vakman, “Complex signals and ambiguity function” Soviet Radio, Moscow, 1965 (in Russian).
[9]. Diplom work of eng.A. Kabakchiev “Automatics synthesis of discrete complex signals”. ( in Bulgarian)
[10]. Dissertation of professor doctor of science, Borislav Bedzhev “Improving noise protection in radar systems on the basis of algebraic
method „. (in Bulgarian)
[11]. Hsiao-Hwa Chen, Jun-Feng Yeh, Naoki Suehiro, “A Multicarrier CDMA Architecture Based on Orthogonal Complementary Codes
for New Generations of Wideband Wireless Communications”- Topics in Wireless Communication – IEEE Communication
Magazine October 2001
[12]. Pingzhi Fan, Senior Member, IEEE, Weina Yuan, and Yifeng Tu” Z-complementary Binary Sequences”, IEEE SIGNAL
PROCESSING LETTERS, VOL. 14, NO. 8, AUGUST 2007
[13]. J. L. Walsh, “A closed set of normal orthogonal functions, „ Amer. J.Math., vol. 55, pp. 5–24, 1923.
[14]. „Walsh-Like Nonlinear Phase Orthogonal Codes for Direct Sequence CDMA Communications” Ali N. Akansu, Senior Member,
IEEE, and Radha Poluri.
I DODDA.H.V.S.RAMI REDDY completed my B.Tech in 2010 from Loyola Institute of
Technology and Management . I pursuing M.Tech in Dr Samuel George Engineering College
Markapur.
I P Prasanna Murali Krishna working as Assoc.prof in ECE Dept and also Head of the
Department with Dr.SGIET Markapur from 2001 to till date.
I K.Ranjith Kumar working as Asst Prof in ECE Dept with Dr.SGIET Markapur from 2012 to
till date.

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Reduction of Side Lobes by Using Complementary Codes for Radar Application

  • 1. IOSR Journal of Electronics and Communication Engineering (IOSR-JECE) e-ISSN: 2278-2834,p- ISSN: 2278-8735.Volume 6, Issue 2 (May. - Jun. 2013), PP 27-30 www.iosrjournals.org www.iosrjournals.org 27 | Page Reduction of Side Lobes by Using Complementary Codes for Radar Application Dodda.H.V.S.Rami Reddy1 , P.P.M.Krishna2 ,K. Ranjith Kumar3 1 second. M Tech Student (DECS), 2 Assoc. professor,3 Asst.professor Dept of E.C.E, Dr.S.G.I.T, Markapur, Prakasam (Dist),India1 , Dept of E.C.E,S.G.I.T, Markapur2 , Dept of E.C.E,S.G.I.T, Markapur3 DODDA.H.V.S.Rami Reddy1 , P.P.M.Krishna2 ,K. Ranjith Kumar3 1 second. M Tech Student (DECS), 2 Assoc. professor,3 Asst.professor Dept of E.C.E, Dr.S.G.I.T, Markapur, Prakasam (Dist),India1 , Dept of E.C.E,S.G.I.T, Markapur2 , Dept of E.C.E,S.G.I.T, Markapur3 Abstract: The analysis of new types of Complementary direct sequence complex signals which have synthesized with well – know code sequences like Barker, Walsh, Golay, and complementary codes. Build on the autocorrelation function (ACF) and ambiguity function (AF) of signals, the numerical method estimates the volume of side lobes separately for each signal. The results obtained show that the signals, which have a low volume of side lobes, means of approximately zero in by using complementary codes with compare to different codes. Keywords: Ambiguity function, complementary codes, autocorrelation function etc. I. INTRODUCTION In wireless communication systems such radars radio, TV and navigation systems, electromagnetic signals are transmitted in the frequency based on the different frequency bands of range from KHz to GHz. In recent years many authors have published a set of research works related to estimation of ambiguity functions (AF) of these signals (communication, television or radio), i.e. estimation of the radar properties. It was concluded that the good characteristics of their ambiguity functions are not always combined with dynamic range restriction. The usage of such radars is very perspective, but related with many restrictions. In existing system for radar communication by using the electromagnetic wave is used to find the targets in the radar receivers by extracting the received signal with the help of barker, Walsh and golay codes are used to find the location and distance of the target. But here one problem occurred i.e., high side lobes are occurred in some cases it is dominate the main lobe it causes a (False Alarm). In proposed system to avoid the side lobes or False alarm by using the new technique i.e., complementary codes are used instead of barker, Walsh and golay codes to get almost zero side lobes easy to find the target location and distance from radar. I .Evaluation of side lobes In the study, we use the general definition of the following quality factors: Maximal Peak Side lobe Power (PSP), Peak Side lobe Level (PSL), Integrated Side lobe Level (ISL) and Golay Merit Factor (MF). These quality factors are often used in order to analyze the volume of signal side lobes at the filter output:  Max Peak Side lobe Power (PSP) = 1/N - is the maximum amplitude at the filter output , and N is the code length;  Peak Side lobe Level (PSL) – is the highest side lobe power level relative to the main lobe: obepowertotalmainl bepowerpeaksidelo PSL log10 … 1.1  Integrated Side lobe Level (ISL) – is the power distributed in all side lobes and defined as: obepowertotalmainl rsidelobesegratedovepower ISL int log10 … 1.2  The Golay Merit Factor (MF) of binary sequences of length N is given by:
  • 2. Reduction Of Side Lobes By Using Complementary Codes For Radar Application www.iosrjournals.org 28 | Page     1 1 2 2 2 N k ka N MF … 1.3   kii sskN i kaAACF     1 0 1 , Nk 1 AACF - Aperiodic autocorrelation function. (1.4) II. EXPERIMENTAL DESCRIPTION The study is realized by developing the specialized software in Matlab 7.6. This software computes PSL and ISL of ambiguity functions of signals under study and visualizes the results. The main quality factors of signals under study are evaluated and visualized. The structure of this software is shown in Fig. 2.1. The function of computational algorithm includes the following operations: input of the information for the type and the parameters of codes under study; calculation and normalization of the code autocorrelation function (ACF); computation of the Merit factor; calculation of PSL and ISL, graphical and numerical visualization of the final results. In case of complementary codes two codes are applied to the input; in the block for calculation of ACF a sum of two code’s ACF is computed. In the next block a partial minimization of the volume of the body of ambiguity is performed resulting into a new matrix, which is normalized (a sum of matrixes in case of complementary codes). After that the quality factors PSL and ISL of the minimized ambiguity function are calculated, and, finally, the numerical and graphical results are visualized. The main purpose of this study is to analyze which of these signals have the better (lower) values of Peak Side lobe Level and Integrate Side lobe Level. Fig 2.1: Block diagram of the computational algorithm For the above computational algorithm is used to find the target location by applying different codes. The ex-perimental results are the given below in graphical model.
  • 3. Reduction Of Side Lobes By Using Complementary Codes For Radar Application www.iosrjournals.org 29 | Page Fig 2.2.a: Autocorrelation of Walsh sequence. In the above fig 2.2.a for detecting the target but difficult to analyze that because noise or side lobes are very high in the Walsh sequence. The Ambiguity function for the Walsh sequence is also same but it is in 3-dimentional manner here we find easily the side lobes compare to the Autocorrelation function. Fig 2.2.b: Ambiguity diagram of Walsh sequence. In my proposed model by using the complementary codes to overcome the noise occurred in the Walsh codes. The results for complementary codes are given below. Fig 2.3.a: Autocorrelation of complementary sequence. Compare to both autocorrelation’s complementary sequence have almost zero noise. Same for ambiguity function also is in the given below.
  • 4. Reduction Of Side Lobes By Using Complementary Codes For Radar Application www.iosrjournals.org 30 | Page Fig.2.3.b:Ambiguity diagram of complementary sequence III. Conclusion Based on the results obtained, we conclude that the complementary codes have the best characteristics ACF and MAF in comparison with all the rest codes. The results are obtained by the software Matlab R2011a. This confirms that at the present time and in the future the complementary codes can be successfully used in passive radar systems. REFERENCES [1]. M. J. E. Golay, "Complementary Series, „ IEEE Trans Info. Theory, vol. IT-7, 1961, pp 82-87. [2]. R. Turyn, "Ambiguity Function of Complementary Sequences, „ IЕЕЕ Trans. Info. Theory, vol. IT-9, Jan. 1963, pp. 46-47. [3]. N. Suehiro, "Complete Complementary Code Composedof NMultipleshift Orthogonal Sequences, „ Trans. /ЕICЕ (in Japanese), vol. J65-A, Dec. 1982, pp. 1247-53. [4]. N. Suehiro and M. Hatori, "N-Shift Cross-OrthogonalSequences, „ IEEE Trans. Info. Theory, vol. IT-34, no. 1, Jan. 1988, pp. 143- 46. [5]. Cherniakov M., Kubik M.: “Secondary applications of wireless technology (SAWT)”, 2000 European Conference on Wireless Technology – Paris 2000 [6]. Price R., E. Hofstetter, “Bounds on the Volume and Height Distributions of the Ambiguity Function”, IEEE Transactions on Information Theory, April, 1965. [7]. D.B. Vakman and R. M. Sedletskii, “Problems in Synthesis of Radar Signals”. Soviet Radio, Moscow, 1973 (in Russian). [8]. D.E. Vakman, “Complex signals and ambiguity function” Soviet Radio, Moscow, 1965 (in Russian). [9]. Diplom work of eng.A. Kabakchiev “Automatics synthesis of discrete complex signals”. ( in Bulgarian) [10]. Dissertation of professor doctor of science, Borislav Bedzhev “Improving noise protection in radar systems on the basis of algebraic method „. (in Bulgarian) [11]. Hsiao-Hwa Chen, Jun-Feng Yeh, Naoki Suehiro, “A Multicarrier CDMA Architecture Based on Orthogonal Complementary Codes for New Generations of Wideband Wireless Communications”- Topics in Wireless Communication – IEEE Communication Magazine October 2001 [12]. Pingzhi Fan, Senior Member, IEEE, Weina Yuan, and Yifeng Tu” Z-complementary Binary Sequences”, IEEE SIGNAL PROCESSING LETTERS, VOL. 14, NO. 8, AUGUST 2007 [13]. J. L. Walsh, “A closed set of normal orthogonal functions, „ Amer. J.Math., vol. 55, pp. 5–24, 1923. [14]. „Walsh-Like Nonlinear Phase Orthogonal Codes for Direct Sequence CDMA Communications” Ali N. Akansu, Senior Member, IEEE, and Radha Poluri. I DODDA.H.V.S.RAMI REDDY completed my B.Tech in 2010 from Loyola Institute of Technology and Management . I pursuing M.Tech in Dr Samuel George Engineering College Markapur. I P Prasanna Murali Krishna working as Assoc.prof in ECE Dept and also Head of the Department with Dr.SGIET Markapur from 2001 to till date. I K.Ranjith Kumar working as Asst Prof in ECE Dept with Dr.SGIET Markapur from 2012 to till date.