CAJ | 학술논문

针对标准粒子滤波算法存在的缺陷,本文引入了两种改进的方法,引入最新的量测信息,改进粒子滤波的建议分布.EKPF通过引入扩展卡尔曼算法改进粒子分布,UPF引入无味变换改进粒子的分布,并对其进行了仿真对比分析.实验结果表明,UPF算法优于扩展卡尔曼粒子滤波算法与标准粒子滤波算法.
침대표준입자려파산법존재적결함,본문인입료량충개진적방법,인입최신적량측신식,개진입자려파적건의분포.EKPF통과인입확전잡이만산법개진입자분포,UPF인입무미변환개진입자적분포,병대기진행료방진대비분석.실험결과표명,UPF산법우우확전잡이만입자려파산법여표준입자려파산법.
For the defects of the standard particle filter algorithm, two improved algorithm are proposed, which introduced the latest measurement and improved particle filter proposal distribution. EKPF through the introduction of extended Kalman al-gorithms to improve the particle distribution, UPF introduces the unscented transformation to improve the distribution of the par-ticles, and a simulation of comparative analysis is given. The experimental results show that the UPF algorithm is better than the extended Kalman particle filter algorithm and the standard particle filter algorithm.