基于Grefenstette编码下MicPSO的离散频率编码波形设计

曾祥能; 张永顺; 田波; 赵国庆; 雷腾

doi:10.3724/SP.J.1146.2010.00244

基于Grefenstette编码下MicPSO的离散频率编码波形设计

doi: 10.3724/SP.J.1146.2010.00244

曾祥能^{*① 张永顺,},
张永顺,
田波,
赵国庆,
雷腾

基金项目:

国家自然科学基金(60601016)资助课题

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出版历程
- 收稿日期: 2010-03-15
- 修回日期: 2010-10-15
- 刊出日期: 2011-01-19

Discrete Frequency Code Waveform Based on MicPSO Cooperated with Grefenstette Coded

摘要

摘要: 该文在分析离散频率编码波形信号(DFCW)的模糊函数基础上，建立了离散频率编码信号设计的优化模型，将微群粒子群优化算法(MicPSO)应用于DFCW设计。针对DFCW设计为排列优化问题，引入了Grefenstette编码作为MicPSO的粒子编码进行优化设计。仿真结果表明，DFCW的自相关峰值旁瓣、多普勒容限主要与信号码长有关，而通过该优化设计，信号的互相关性能得到极大改善，与已有方法相比，该方法时间开销小，优化结果更理想。
- 离散频率编码波形 /
- Grefenstette编码 /
- 微群粒子群优化算法
Abstract: With the analysis of the ambiguity function for Discrete Frequency Code Waveform (DFCW) signals, the optimized model for DFCW design is established and the Micro swarm Particle Swarm Optimization (MicPSO) algorithm is proposed to design orthogonal discrete frequency-coding waveforms. As an arrangement issue, the DFCW design is optimized by using Grefenstette coding as MicPSO particle code. The simulated results show that, the DFCWs Auto-correlation Sidelobe Peak (ASP) and Doppler tolerance are mainly determined by the length of coded signal, and the cross correlation properties is greatly improved based on the optimization method described in this paper. Compared with existing methods, the proposed method can save processing time and obtain better optimization results.
- Discrete Frequency Code Waveform (DFCW) /
- Grefenstette code /
- Micro swarm Particle Swarm Optimization (MicPSO)

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Liu Bo and He Zi-shu. Orthogonal Discrete Frequency- Coding Waveform design for MIMO radar [J].Journal of Electronics (China.2008, 25(4):471-476[2]Deng H. Discrete frequency-coding wave- form design for netted radar systems[J].IEEE Signal Processing Letters.2004, 11(2):179-182[3]杨明磊, 张守宏, 陈伯孝等. 多载频MIMO 雷达的一种新的信号处理方法[J].电子与信息学报.2009, 31(1):147-151浏览Yang Ming-lei, Zhang Shou-hong, Chen Bai-xiao, et al.. A novel signal processing approach for the multi-carrier MIMO radar [J].Journal of Eelectronics Information Technology.2009, 31(1):147-151[4]Kennedy J and Eberhart R. Particle swarm optimization [C]. Proc IEEE Int. Conf. on Neural Networks. Perth, 1995: 1942-1948.[5]Li W T, Shi X W, and Xu L. Improved GA and PSO culled hybrid algorithm for antenna array pattern synthesis [J]. Progress in Electromagnetics Research, 2008, 80(1): 397-407.[6]Duran O, Rodriguez R, and Consalter L A. PSO for selecting cutting tools geometry [J].Lecture Notes in Computer Science.2008, 5271:265-272[7]Lin Yih-Lon, Chang Wei-Der, and Hsieh Jer-Guang. A particle swarm optimization approach to nonlinear rational filter modeling [J].Expert Systems with Applications.2008, 34(6):1194-1199[8]潘峰, 陈杰, 辛斌等. 粒子群优化方法若干特性分析[J].自动化学报, 2009, 35(7): 1010-1016.Pan Feng and Chen Jie, and Xin Bin, et al.. Several characteristics analysis of particle swarm optimizer[J].Acta Automatica Ainica.2009, 35(7):1010-1016[9]Huang Tony and Ananda Sanagavarapu Mohan. A microparticle swarm optimizer for the reconstruction of microwave images [J].IEEE Transactions on Antennas and Propagation.2007, 55(3):568-576[10]Peer E S, Van den Bergh F, and Engelbrecht A P. Using neighborhoods with the guaranteed convergence PSO [J]. IEEE Swarm Intell. Symp., 2003, 1(1): 235-242.[11]Grefenstette J, et al.. Genetic algorithms for the traveling salesman problems [C]. Proc. of the Int. Conf. on Genetic Algorithms and Their Applications, USA, Carnegie-Mellon University, 1985: 160-168.[12]刘波. MIMO雷达正交波形设计及信号处理研究[D]. [博士论文], 成都:电子科技大学, 2008.

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