系统工程与电子技术
繫統工程與電子技術
계통공정여전자기술
SYSTEMS ENGINEERING AND ELECTRONICS
2014年
7期
1243-1249
,共7页
目标跟踪%交互式多模型%无迹卡尔曼滤波%临近空间
目標跟蹤%交互式多模型%無跡卡爾曼濾波%臨近空間
목표근종%교호식다모형%무적잡이만려파%림근공간
target tracking%interacting multiplt model (IMM)%unscented Kalman filter (UKF)%near space
由于目前机动目标模型越来越向模块化、并行计算的方向发展，对目前算法计算效率提出了更高的要求。对于临近空间超声速机动目标一般采用多种机动模型跟踪，单一模型已经很难满足高精度跟踪的需要。因此需要使用基于多种模型进行交叉耦合的交互式多模型（interacting multiple model，IMM）算法，这种算法特点与临近空间目标高速、高机动特性相适应。同时考虑到扩展卡尔曼滤波（extended Kalman filter，EKF）算法对强非线性对象滤波效果不好，无迹卡尔曼滤波（unscented Kalman filter，UKF）算法对于此类问题，可以很好地加以解决。仿真对比试验表明，交互式多模型无迹卡尔曼滤波（interacting multiple model-unscented Kalman filter， IMM-UKF）算法优于单一模型 EKF 算法。
由于目前機動目標模型越來越嚮模塊化、併行計算的方嚮髮展，對目前算法計算效率提齣瞭更高的要求。對于臨近空間超聲速機動目標一般採用多種機動模型跟蹤，單一模型已經很難滿足高精度跟蹤的需要。因此需要使用基于多種模型進行交扠耦閤的交互式多模型（interacting multiple model，IMM）算法，這種算法特點與臨近空間目標高速、高機動特性相適應。同時攷慮到擴展卡爾曼濾波（extended Kalman filter，EKF）算法對彊非線性對象濾波效果不好，無跡卡爾曼濾波（unscented Kalman filter，UKF）算法對于此類問題，可以很好地加以解決。倣真對比試驗錶明，交互式多模型無跡卡爾曼濾波（interacting multiple model-unscented Kalman filter， IMM-UKF）算法優于單一模型 EKF 算法。
유우목전궤동목표모형월래월향모괴화、병행계산적방향발전，대목전산법계산효솔제출료경고적요구。대우림근공간초성속궤동목표일반채용다충궤동모형근종，단일모형이경흔난만족고정도근종적수요。인차수요사용기우다충모형진행교차우합적교호식다모형（interacting multiple model，IMM）산법，저충산법특점여림근공간목표고속、고궤동특성상괄응。동시고필도확전잡이만려파（extended Kalman filter，EKF）산법대강비선성대상려파효과불호，무적잡이만려파（unscented Kalman filter，UKF）산법대우차류문제，가이흔호지가이해결。방진대비시험표명，교호식다모형무적잡이만려파（interacting multiple model-unscented Kalman filter， IMM-UKF）산법우우단일모형 EKF 산법。
Due to the current maneuvering target model is developing towards more and more modular and parallel computing,which puts forward higher requirements for calculation efficiency of algorithm.For high su-personic maneuvering targets in near space,it is often tracked with multiform maneuvering target models,since precision of single target maneuvering model cannot satisfy the requirement of tracking.So it is necessary to use the interactive multiple model algorithm for cross coupling based on a variety of models.The characteristic of this algorithm is adapted to that of high speed and high maneuver for near space target.At the same time,con-sidering the filtering result of extended Kalman filter (EKF)algorithm for strong nonlinear targets is bad,un-scented Kalman filter (UKF)algorithm can be solved very well for this problem.So through simulation contrast experiment of two kinds of algorithms,it proves that interacting multiple model-unscented Kalman filter (IMM-UKF) algorithm guarantees the target tracking accuracy is within the allowable range,validity of the algorithm is veri-fied with Matlab simulation results.
