|
|
- 2016
基于混沌的改进粒子群优化粒子滤波算法
|
Abstract:
摘要 针对基本粒子滤波(PF)算法存在的粒子退化和重采样引起的粒子多样性丧失,导致粒子样本无法精确表示状态概率密度函数真实分布,提出了一种基于混沌的改进粒子群优化(PSO)粒子滤波算法。通过引入混沌序列产生一组混沌变量,将产生的变量映射到优化变量的区间提高粒子质量,并利用混沌扰动克服粒子群优化局部最优问题。利用单变量非静态增长模型(UNGM)在高斯噪声和非高斯噪声环境下将该算法与基本粒子滤波和粒子群优化粒子滤波(PSO-PF)的性能进行仿真比较。结果表明:该算法的性能在有效粒子数和均方根误差(RMSE)等参数都优于基本粒子滤波和粒子群优化粒子滤波,改善了算法的精度和跟踪性能。
Abstract：To solve the degeneracy phenomenon and the sample impoverishment problem of basic particle filter (PF) algorithm, which makes the particles of PF algorithm unable to express the real distribution of probability density function, a novel PF algorithm based on chaos particle swarm was proposed. Chaos sequence was adopted in this proposed algorithm. The chaos sequence was used to generate a set of chaotic variables, which was mapped to the interval of optimization variables to improve the quality of particles. And chaos perturbation was utilized to overcome the search being trapped in local optimum for particle swarm optimization (PSO) algorithm. The univariate nonstationary growth model (UNGM) was used for simulation to compare the proposed algorithm with basic PF and particle swarm optimization particle filter (PSO-PF). Under the conditions of Gaussian and non-Gaussian noise, the performances of the proposed algorithm had been verified by the simulation. The results show that the performances of the number of effective particles and root mean square error (RMSE) in the algorithm are better than the performances of the basic PF and the PSO-PF algorithm. Therefore, the accuracy and tracking performance of PF are improved.
| [1] | IBARGUREN A,MAURTUA I,PEREZ M A,et al.Multiple target tracking based on particle filtering for safety in industrial robotic cells[J].Robotics and Autonomous Systems,2015,72:105-113. |
| [2] | 张华,张有光,李国彦.基于混合粒子滤波的载波估计算法[J].北京航空航天大学学报,2013,39(2):184-189. ZHANG H,ZHANG Y G,LI G Y.Carrier estimation algorithm based on novel hybrid particle filtering[J].Journal of Beijing University of Aeronautics and Astronautics,2013,39(2):184-189(in Chinese). |
| [3] | KADIRKAMANATHAN V,LI P,JAWARD M H,et al.Particle filtering based fault detection in nonlinear stochastic systems[J].International Journal of Systems Science,2002,33(4):259-265. |
| [4] | GORDON N,SALMOND D,SMITH A.Novel approach to nonlinear/non-Gaussian Bayesian state estimation[J].IEEE Proceedings on Radar,Sonar and Navigation,1993,140(2):107-113. |
| [5] | DOUCET A,GODSILL S,ANDRIEU C.On sequential Monte Carlo sampling methods for Bayesian filtering[J].Statistics and Computing,2000,10(3):197-208. |
| [6] | FU X Y,JIA Y M.An improvement on resampling algorithm of particle filters[J].IEEE Transactions on Signal Processing,2010,58(10):5414-5420. |
| [7] | 陈志敏,薄煜明,吴盘龙,等.基于自适应粒子群优化的新型粒子滤波在目标跟踪中的应用[J].控制与决策,2013,28(2):193-200. CHEN Z M,BO Y M,WU P L,et al.Novel particle filter algorithm based on adaptive particle swarm optimization and its application to radar target tracking[J].Control and Decision,2013,28(2):193-200(in Chinese). |
| [8] | CARPENTER J,CLIFFORD P,FEARNHEAD P.Improved particle filter for nonlinear problems[J].IEEE Proceedings-Radar Sonar and Navigation,1999,146(1):1-7. |
| [9] | 佘黎煌,张石,王鸿雁.非高斯条件下基于粒子滤波的T波交替检测算法[J].电子学报,2014,42(2):223-229. SHE L H,ZHANG S,WANG H Y.A T-wave alternans detection algotithm based on particle filtering in non-Gaussian environment[J].Acta Electronica Sinica,2014,42(2):223-229(in Chinese). |
| [10] | 张玲霞,刘志仓,王辉,等.非线性系统故障诊断的粒子滤波方法[J].电子学报,2015,43(3):615-619. ZHANG L X,LIU Z C,WANG H,et al.Particle filter method for fault diagnosis in nonlinear system[J].Acta Electronica Sinica,2015,43(3):615-619(in Chinese). |
| [11] | GUSTAFSSON F,BERGMAN N,FORSSELL U,et al.Particle filters for positioning,navigation,and tracking[J].IEEE Transaction on Signal Processing,2002,50(2):425-437. |
| [12] | ARULAMPALAM M S,MASKELL S,GORDON N,et al.A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking[J].IEEE Transactions on Signal Processing,2002,50(2):174-188. |
| [13] | ZHAO J,LI Z Y.Particle filter based on particle swarm optimization resampling for vision tracking[J].Expert Systems with Applications,2010,37(12):8910-8914. |
| [14] | ZHAO Z S,FENG X,LIN Y Y,et al.Improved rao-blackwellized particle filter by particle swarm optimization[J].Journal of Applied Mathematics,2013(4):1-6. |
| [15] | LORENZ E N.The essence of chaos[M].Seattle:University of Washington Press,1993:3-7. |
| [16] | WAKANO J Y,HAUERT C.Pattern formation and chaos in spatial ecological public goods games[J].Journal of Theoretical Biology,2011,268(1):30-38. |
