DocumentCode
2822405
Title
Radar phase-coded waveform design using MOEAs
Author
Stringer, Jeremy ; Lamont, Gary ; Akers, Geoffrey
Author_Institution
Dept. of Electr. & Comput. Eng., Air Force Inst. of Technol., Dayton, OH, USA
fYear
2012
fDate
10-15 June 2012
Firstpage
1
Lastpage
8
Abstract
This study applies the NSGA-II, SPEA2, and MOEA/D Multi-Objective Evolutionary Algorithms (MOEAs) to the radar phase coded waveform design problem. The MOEAs are used to generate a series of radar waveform phase codes that have excellent range resolution and Doppler resolution capabilities, while maintaining excellent autocorrelation properties. The study compares the ability of NSGA-II, SPEA2, and MOEA/D to generate a Pareto front of phase code solutions, and then improve upon the quality of the solutions while maintaining a sufficient diversity of available radar phase codes. Results demonstrate that for solving moderate to large instances of the radar phase code problem all three MOEAs generate a diverse set of Pareto optimal radar phase codes. The phase codes generated by NSGA-II have overall better autocorrelation properties than those generated by SPEA2 and MOEA/D, however, all three MOEAs produce useable phase codes.
Keywords
Pareto optimisation; genetic algorithms; phased array radar; radar resolution; Doppler resolution; MOEA/D; NSGA-II; Pareto front; Pareto optimal radar phase codes; SPEA2; autocorrelation property; multiobjective evolutionary algorithm; radar phase-coded waveform; range resolution; Correlation; Doppler effect; Doppler radar; Measurement; Signal to noise ratio; Vectors;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation (CEC), 2012 IEEE Congress on
Conference_Location
Brisbane, QLD
Print_ISBN
978-1-4673-1510-4
Electronic_ISBN
978-1-4673-1508-1
Type
conf
DOI
10.1109/CEC.2012.6256554
Filename
6256554
Link To Document