西北工业大学学报
西北工業大學學報
서북공업대학학보
JOURNAL OF NORTHWESTERN POLYTECHNICAL UNIVERSITY
2010年
1期
47-50
,共4页
目标跟踪%BF粒子滤波%卡尔曼滤波器
目標跟蹤%BF粒子濾波%卡爾曼濾波器
목표근종%BF입자려파%잡이만려파기
Kalman filtering%algorithms%target tracking%BF (Bootstrap Particle Filter)
为了对快速目标进行跟踪,在高斯加性白噪声的条件下(AGWN),文章把BF粒子滤波算法和迭代的Kalman滤波器方法结合起来对快速目标状态进行处理,状态估计用BF粒子滤波算法,能减小方差和运算量,同时用Kalman滤波器能提高跟踪精度和对目标状态的估计.仿真结果表明,文中所设计的快速和精确的BF算法能真正地解决快速目标跟踪问题.
為瞭對快速目標進行跟蹤,在高斯加性白譟聲的條件下(AGWN),文章把BF粒子濾波算法和迭代的Kalman濾波器方法結閤起來對快速目標狀態進行處理,狀態估計用BF粒子濾波算法,能減小方差和運算量,同時用Kalman濾波器能提高跟蹤精度和對目標狀態的估計.倣真結果錶明,文中所設計的快速和精確的BF算法能真正地解決快速目標跟蹤問題.
위료대쾌속목표진행근종,재고사가성백조성적조건하(AGWN),문장파BF입자려파산법화질대적Kalman려파기방법결합기래대쾌속목표상태진행처리,상태고계용BF입자려파산법,능감소방차화운산량,동시용Kalman려파기능제고근종정도화대목표상태적고계.방진결과표명,문중소설계적쾌속화정학적BF산법능진정지해결쾌속목표근종문제.
For the purpose of addressing the problem of processing the information of fast targets, sections 1 and 2 explain in some detail how to incorporate, under AGWN (additive Gaussian white noise) environment, the essence of BF (Bootstrap Particle Filter) algorithm into a different Kalman filter. Section 1 explains the essence of BF algorithm; in it, eq. (3) is the most important. Section 2 explains the implementation of my fast and accurate BF algorithm for tracking fast targets through using a Kalman filter that has incorporated the essence of the BF algorithm. In my new algorithm, the BF method can reduce the computational complexity and variance to some degree and the Kalman filtering can enhance tracking accuracy and estimation accuracy of target state. The simulation results, presented in Figs. 3 and 4, show preliminarily that my new fast and accurate BF algorithm can indeed track fast targets.
