西安电子科技大学学报（自然科学版）
西安電子科技大學學報（自然科學版）
서안전자과기대학학보（자연과학판）
JOURNAL OF XIDIAN UNIVERSITY(NATURAL SCIENCE)
2014年
6期
37-44
,共8页
交互多模型%粒子滤波%箱粒子滤波%量化量测
交互多模型%粒子濾波%箱粒子濾波%量化量測
교호다모형%입자려파%상입자려파%양화량측
interacting multiple model%particle filter%box particle filter%quantitative measurements
在分布式多传感器网络中，为了节省通信带宽，需要将传感器得到的点量测量化成区间量测，而传统的滤波算法均不能直接处理这种量化量测。箱粒子滤波作为一种“广义粒子滤波”算法，用箱粒子和误差界限模型来取代传统的点粒子和误差统计模型，是新近出现的处理区间量测的有力工具。相比粒子滤波，箱粒子滤波还具有所需粒子数少、算法复杂度低、运行速度快等优点。因此，为了处理量化量测条件下的机动目标跟踪问题，提出了交互多模型箱粒子滤波算法。仿真对比实验表明：在量化量测条件下，交互多模型箱粒子滤波算法和交互多模型粒子滤波算法都能够准确地估计机动目标状态，但交互多模型箱粒子滤波所需粒子数更少、计算效率更高。
在分佈式多傳感器網絡中，為瞭節省通信帶寬，需要將傳感器得到的點量測量化成區間量測，而傳統的濾波算法均不能直接處理這種量化量測。箱粒子濾波作為一種“廣義粒子濾波”算法，用箱粒子和誤差界限模型來取代傳統的點粒子和誤差統計模型，是新近齣現的處理區間量測的有力工具。相比粒子濾波，箱粒子濾波還具有所需粒子數少、算法複雜度低、運行速度快等優點。因此，為瞭處理量化量測條件下的機動目標跟蹤問題，提齣瞭交互多模型箱粒子濾波算法。倣真對比實驗錶明：在量化量測條件下，交互多模型箱粒子濾波算法和交互多模型粒子濾波算法都能夠準確地估計機動目標狀態，但交互多模型箱粒子濾波所需粒子數更少、計算效率更高。
재분포식다전감기망락중，위료절성통신대관，수요장전감기득도적점량측양화성구간량측，이전통적려파산법균불능직접처리저충양화량측。상입자려파작위일충“엄의입자려파”산법，용상입자화오차계한모형래취대전통적점입자화오차통계모형，시신근출현적처리구간량측적유력공구。상비입자려파，상입자려파환구유소수입자수소、산법복잡도저、운행속도쾌등우점。인차，위료처리양화량측조건하적궤동목표근종문제，제출료교호다모형상입자려파산법。방진대비실험표명：재양화량측조건하，교호다모형상입자려파산법화교호다모형입자려파산법도능구준학지고계궤동목표상태，단교호다모형상입자려파소수입자수경소、계산효솔경고。
In the distributed multi-sensor networks,in order to save the communication bandwidth,to quantize the point observations obtained by sensors into the interval measurements is required.However, the traditional filtering algorithm can not directly deal with the quantitative measurements.The box particle filter (Box-PF) as a"generalized particle filter"algorithm uses the box particles and the bounded error model to replace the traditional point particles and the error statistical model.Therefore,it is a powerful tool for processing interval measurements.Key advantages of the Box-PF against the standard particle filter (PF)are a smaller particle number,reduced computational complexity and a fast running speed.Therefore, to cope with the maneuvering target tracking with the quantitative measurements,this paper presents an interacting multiple model box particle filter(IMMBPF)algorithm.Simulation results show that under the condition of quantitative measurements IMMBPF and IMMPF are both able to accurately estimate the states of the maneuvering target.The IMMBPF,however,needs fewer particles,and computes more efficiently.
