军械工程学院学报
軍械工程學院學報
군계공정학원학보
JOURNAL OF ORDNANCE ENGINEERING COLLEGE
2013年
5期
55-62
,共8页
卡尔曼滤波%粒子滤波%迭代卡尔曼粒子滤波%目标跟踪
卡爾曼濾波%粒子濾波%迭代卡爾曼粒子濾波%目標跟蹤
잡이만려파%입자려파%질대잡이만입자려파%목표근종
kalman filter%particle filter%iterative kalman-particle filter%object tracking
粒子滤波在基于图像序列的目标跟踪中获得了广泛应用。针对其计算量较大的问题，提出一种迭代卡尔曼粒子滤波算法，将非线性跟踪问题分解为线性子结构的全局状态空间模型和非线性子结构的局部状态空间模型，利用粒子滤波在卡尔曼滤波估计值的局部范围内搜索目标，逼近真实目标状态。将实验结果与粒子滤波进行比较，结果表明，迭代卡尔曼粒子滤波减少了粒子数，降低了计算量，能够对高机动目标进行实时稳定的跟踪。
粒子濾波在基于圖像序列的目標跟蹤中穫得瞭廣汎應用。針對其計算量較大的問題，提齣一種迭代卡爾曼粒子濾波算法，將非線性跟蹤問題分解為線性子結構的全跼狀態空間模型和非線性子結構的跼部狀態空間模型，利用粒子濾波在卡爾曼濾波估計值的跼部範圍內搜索目標，逼近真實目標狀態。將實驗結果與粒子濾波進行比較，結果錶明，迭代卡爾曼粒子濾波減少瞭粒子數，降低瞭計算量，能夠對高機動目標進行實時穩定的跟蹤。
입자려파재기우도상서렬적목표근종중획득료엄범응용。침대기계산량교대적문제，제출일충질대잡이만입자려파산법，장비선성근종문제분해위선성자결구적전국상태공간모형화비선성자결구적국부상태공간모형，이용입자려파재잡이만려파고계치적국부범위내수색목표，핍근진실목표상태。장실험결과여입자려파진행비교，결과표명，질대잡이만입자려파감소료입자수，강저료계산량，능구대고궤동목표진행실시은정적근종。
Particle filters(PF)are widely applied for various visual tracking problems but restrictedwith computation load,and then hierarchical Kalman-particle filter (IKPF)based on coarse to finestrategy is proposed to reduce the computation for real-time tracking.The algorithm regards thesignificant nonlinear system as the combination of a linear state space describing global motionand a nonlinear state space describing local motion.As the optimal linear filter,Kalman filter(KF)is introduced to predict the global motion state.Then Particle filter is used to search the true ob-ject state in the local area based on the estimation by Kalman filter.The comparisons between IK-PF and PF are undertaken,and the results indicate that IKPF need less particles and reduce thecomputation,and can achieve successful object tracking in real video sequences in which the targetobjects undergo rapid and abrupt motion.
