Design of Eight-Phase Sequences using Modified Particle Swarm Optimization for Spread Spectrum and Radar Applications

Authors

  • S. Srinivasa Rao Departement of Electronics and Communicaton Engineering, Mahatma Gandhi Institute of Technology
  • P Siddaiah Departement of Electronics and Communicaton Engineering, Acharya Nagarjuna University

DOI:

https://doi.org/10.34306/csit.v6i1.368

Keywords:

Hamming Scan Algorithm, Radio Detection and Ranging, Genetic Algorithm, Auto-Correlation Function, Cross-Correlation Function

Abstract

 For a multiple access communication system and radar system, it is desirable to have a set of sequences such that each sequence has a peaky autocorrelation and each pair of sequence has a negligible cross-correlation as possible. Peakyness of the auto-correlation of a sequence is measured in terms of its discrimination, which is to be maximized. The negligibility of a cross-correlation is judged based on the energy in the cross-correlation which is to be minimized. Obtaining such sequences is a combinatorial problem for which many global optimization algorithms like genetic algorithm, particle swarm optimization algorithm, simulated annealing algorithm were reported in the literature. In this paper a Modified Particle Swarm Optimization (MPSO) Algorithm is being designed to achieve these sequences. The MPSO Algorithm is a combination of the Hamming Scan Algorithm (HAS) and Particle Swarm Optimization (PSO) and has the fast convergence rate of Hamming Scan and global minima convergence of Particle Swarm Optimization. Eight-phase sequences of lengths varying from 40 to 300 have been synthesized using MPSO and synthesized sequence sets achieved have better values of the above two properties compared with the literature.

Downloads

Download data is not yet available.

References

J.Kennedy and R. Eberhart, “Particle swarm optimization”, In Proc. IEEE Int. Conf. Neural logical Networks”, vol. IV, Perth, Australia, 1995, pp. 1942–press.1948.

Xiangneng Zeng, Yongshun Zhang, and Yiduo Guo, "Poly-phase coded signal design for MIMO radar using MO-MicPSO", Journal of Systems Engineering and Electronics, vol.22, no.3, pp.381–386, June 2011.

Sergio Gil-López, Javier Del Sera, Sancho Salcedo-Sanz, Ángel M. Pérez-Bellido, José Mar?´a Cabero and José A. Portilla-Figueras, "A hybrid harmony search algorithm for the spread spectrum radar poly-phase codes design problem," Expert Systems with Applications”, vol.39, no.12, pp.11089–11093, 15 September 2012.

Jin Yang, Zhaokun Qiu, Weidong Jiang and Xiang Li, "Poly-phase codes optimisation for multi-input multi-output radars," IET Signal Processing, vol.7, no.2, pp.93-100, April 2013.

Li Hong, Qin Yuliang, Wang Hongqiang, Li Yanpeng and Li Xiang ,"A Fast Parameter Estimation Algorithm For Polyphase Coded CW Signals," Journal Of Electronics(China), vol.28, no.1, January 2011.

Paolo Ghelfi, Filippo Scotti, Francesco Laghezza, and Antonella Bogoni, "Phase Coding of RF Pulses in Photonics-Aided Frequency-Agile Coherent Radar Systems," IEEE Journal of Quantum Electronics, vol.48, no.9, pp. 1151 - 1157, 2012.

Antonio De Maio, Silvio De Nicola, Yongwei Huang, Zhi-Quan Luo, and Shuzhong Zhang, "Design of Phase Codes for Radar Performance Optimization With a Similarity Constraint," IEEE Transactions on Signal Processing, vol. 57, no. 2, pp.610 - 621, Nov, 2008.

S. P. Singh, and K. Subba Rao, "Orthogonal Poly-phase Sequence Sets Design for Radar Systems," In Proceedings of the International Radar Symposium”, pp. 1-4, 2006.

N. Balaji and K. Subba Rao, “VLSI-based Real-time Signal Processing Solution Employing Four-phase Codes for Spread- spectrum Applications”, IETE Journal of research, Vol.58, Issue 1, pp. 57-64, Jan-Feb 2012

Merrill I. Skolnik, “Introduction to Radar Systems,” 2nd edition, 2008.

Nadav Levanon, Eli Mozeson, “Radar Signals”, 1st Editon, Wilet-Interscience, 2004.

Changhe Li at.el, “A Fast Particle Optimization Algorithm with Cauchy Mutation and Natural Selection Strategy”,. Proceedings of the 2nd international conference Advances in computation and Intelligence 2007, Wuhan, China, pp.334-343

Lindner, J. (1975), “Binary sequences up to length 40 with best possible Autocorrelation functions”, Letters, 11(1975), 507.

Molin Jia, Xiao Cai, Syahrulanuar Ngah, Yuji Tanabe and Takaaki Baba, “A Pipeline Architecture of Particle Swarm Optimization for Polyphase Coded CW Signals," Journal Of Electronics (China)”, vol 28, no.1, January 2011.

H. Zhu, Y. Tanabe and T. Baba, “A random time-varying particle swarm optimization for the real time location systems”, IEEE Transaction on Real-Time Control,” Journal of Signal Processing, Vol. 14, No. 6, pp. 405-414, Nov.2010.

Golay. M.J.E., “The merit factor of long low autocorrelation binary sequences”, IEEE Transactions on Information Theory. IT-28, 1982, pp 543-549.

Molin Jia, Xiao Cai, Syahrulanuar Ngah, Yuji Tanabe and Takaaki Baba, “A Pipeline Architecture of Particle Swarm Optimization for Real-Time Control,” Journal of Signal Processing, Vol. 14, No. 6, pp. 405-414, Nov. 2010.

Pujiati, D., & Margianti, E. S. (2020). Meta Analysis of Management Control System, Strategy and Performance of Business Unit. APTIKOM Journal on Computer Science and Information Technologies, 5(3), 100-109. https://doi.org/10.34306/csit.v5i3.188

Zarlis, M., Roslina, R., & Elviwani. (2020). Implementation of Information Extraction Algorithm for Indonesian Research Report. APTIKOM Journal on Computer Science and Information Technologies, 5(3), 154-159. Retrieved from https://aptikom-journal.id/index.php/csit/article/view/318

Shah, A., & Patel, N. (2020). Efficient and Scalable Multitenant Placement Approach for In-memory Database Over Supple Architecture. APTIKOM Journal on Computer Science and Information Technologies, 5(3), 137-145. Retrieved from https://aptikom-journal.id/index.php/csit/article/view/192

Downloads

Published

2021-04-01

How to Cite

Rao, S. S., & Siddaiah, P. (2021). Design of Eight-Phase Sequences using Modified Particle Swarm Optimization for Spread Spectrum and Radar Applications. APTIKOM Journal on Computer Science and Information Technologies, 6(1), 36-46. https://doi.org/10.34306/csit.v6i1.368

Issue

Section

Articles