电子科技大学学报Issue(3)：344-349,6.DOI:10.3969/j.issn.1001-0548.2015.03.005
基于遗传算法改进的粒子滤波重采样模型
Improved Resampling Procedure Based on Genetic Algorithm in Particle Filter
摘要
Abstract
Particle filtering is a nonlinear and non-Gaussian dynamical filtering system. It has found widespread applications in detection, navigation, and tracking problems. The strong maneuverability of target tracking brings heavy impact on particle attributes in resampling process of particle filters, such as, particle state, particle weights, and so on. This paper proposes a new particle filter algorithm based on genetic algorithm optimization. This algorithm combines the hereditability and aberrance of the genetic algorithm into the resampling procedure of particle filter to improve the adaptability of maneuvering target tracking.关键词
遗传算法/机动目标跟踪/非线性滤波器/粒子滤波/重采样Key words
genetic algorithm/maneuvering target tracking/nonlinear filtering/particle filter/particle resampling分类
信息技术与安全科学引用本文复制引用
张民,贾海涛,沈震..基于遗传算法改进的粒子滤波重采样模型[J].电子科技大学学报,2015,(3):344-349,6.基金项目
FoundationSupport by the National Science Foundation of China(61172117)基金项目国家自然科学基金(61172117) （61172117）
