西安电子科技大学学报（自然科学版）2018，Vol.45Issue(2)：141-147,7.DOI:10.3969/j.issn.1001-2400.2018.02.024
万有引力优化的粒子滤波算法
Gravity optimized particle filter algorithm
摘要
Abstract
As the traditional particle filter has problems of particle degeneracy and particle diversity loss and filter accuracy depends heavily on the particle number,a gravity optimized particle filter algorithm is proposed.The particle swarm is optimized by the gravity algorithm in the particle filter to improve the filtering accuracy.Each particle is regarded as a mass point and the mass is proportional to the particle weight.The gravity attracts particles moving toward the high likelihood region which optimizes the particle swarm.Then elite particle strategy is introduced to accelerate the particle convergence rate and avoid the local optimum in the gravity algorithm.The perceptual model is used to prevent particles from crowding or overlapping due to excessive convergence.Simulation results show that the proposed algorithm has a better filtering accuracy and speed in the case of few particles compared with the classical particle filter algorithm and particle swarm optimization particle filter algorithm.关键词
粒子滤波/粒子退化/粒子贫化/万有引力/状态估计Key words
particle filter/particle degeneracy/particle impoverishment/gravitation/state estimation分类
信息技术与安全科学引用本文复制引用
刘润邦,朱志宇..万有引力优化的粒子滤波算法[J].西安电子科技大学学报（自然科学版）,2018,45(2):141-147,7.基金项目
国家自然科学基金资助项目(61671222) （61671222）
江苏省自然科学基金资助项目(SBK2015021788) （SBK2015021788）
江苏省研究生科研创新计划资助项目(KYCX17_1843) （KYCX17_1843）
江苏科技大学研究生创新计划资助项目(YCX16S-09) （YCX16S-09）
