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Particle swarm optimization for radar binary phase code selection
Author(s): Bingcheng Li
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Paper Abstract

Binary phased codes have many applications in communication and radar systems. These applications, including spread spectrum communication and low probability of intercept radar, require low sidelobes and long code lengths. Many techniques for finding long binary phased codes with low sidelobes have been investigated in literatures. These techniques include exhaust search, neural network, and evolutionary methods, and they all have high computational cost. In this paper, we propose particle swarm optimization (PSO) to select long low sidelobe binary phased codes with reasonable computational cost. We investigate two techniques for initialization: random number approach and linear chirp approach and show that linear chirp initialization performs significantly better than random number approach. By implementing the proposed techniques, we demonstrate that PSO approach with linear chirp initialization can find binary codes with sidelobes equal to or lower than the neural network and genetic algorithm techniques in literatures.

Paper Details

Date Published: 4 May 2018
PDF: 8 pages
Proc. SPIE 10633, Radar Sensor Technology XXII, 106330A (4 May 2018); doi: 10.1117/12.2305768
Show Author Affiliations
Bingcheng Li, Lockheed Martin Systems Integration-Owego (United States)


Published in SPIE Proceedings Vol. 10633:
Radar Sensor Technology XXII
Kenneth I. Ranney; Armin Doerry, Editor(s)

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