基于人工蜂群技术的海杂波参数优化方法
来源期刊：中南大学学报(自然科学版)2012年第9期
论文作者：贾宗圣 司锡才 王桐
文章页码：3485 - 3489
关键词：人工蜂群；雷达；海杂波；参数优化
Key words：artificial bee colony; radar; sea clutter; parameter optimization
摘 要：针对高海情时海杂波有较长拖尾的问题，提出一种基于人工蜂群技术的海杂波参数优化方法。在雷达目标的环境模拟中，海杂波的建模与仿真是重要的组成部分，对于对数正态分布的海杂波，根据零记忆非线性变换法的原理，结合人工蜂群算法对海杂波的产生过程进行参数优化，讨论具体的实现过程，并找出合适的滤波器系 数，得出理想的杂波谱。仿真结果表明：该方法的性能要优于以往的基于粒子群优化技术以及遗传算法的参数优化方法。
Abstract: Aimed at resolving the protraction of sea clutter as high sea-state, a method for sea clutter parameter optimization based on artificial bee colony algorithm was proposed. The modeling and simulation of sea clutter is very important in radar system simulation. To the sea clutter with lognormal distribution, the generation process of the parameter was optimized combined with artificial bee colony algorithm based on the theory of zero-memory non-linearity. The material course of realization was discussed, and the filter coefficients which can result in better spectrum properties was calculated. Simulation results show that the performance is better than the parameter optimization methods based on particle swarm optimization and genetic algorithms.
贾宗圣，司锡才，王桐
(哈尔滨工程大学 信息与通信工程学院，黑龙江 哈尔滨，150001)
摘 要：针对高海情时海杂波有较长拖尾的问题，提出一种基于人工蜂群技术的海杂波参数优化方法。在雷达目标的环境模拟中，海杂波的建模与仿真是重要的组成部分，对于对数正态分布的海杂波，根据零记忆非线性变换法的原理，结合人工蜂群算法对海杂波的产生过程进行参数优化，讨论具体的实现过程，并找出合适的滤波器系 数，得出理想的杂波谱。仿真结果表明：该方法的性能要优于以往的基于粒子群优化技术以及遗传算法的参数优化方法。
关键词：人工蜂群；雷达；海杂波；参数优化
JIA Zong-sheng, SI Xi-cai, WANG Tong
(College of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China)
Abstract:Aimed at resolving the protraction of sea clutter as high sea-state, a method for sea clutter parameter optimization based on artificial bee colony algorithm was proposed. The modeling and simulation of sea clutter is very important in radar system simulation. To the sea clutter with lognormal distribution, the generation process of the parameter was optimized combined with artificial bee colony algorithm based on the theory of zero-memory non-linearity. The material course of realization was discussed, and the filter coefficients which can result in better spectrum properties was calculated. Simulation results show that the performance is better than the parameter optimization methods based on particle swarm optimization and genetic algorithms.
Key words:artificial bee colony; radar; sea clutter; parameter optimization
