During the course of prediction and estimation to the target in opto-electronic tracking system, stochastic noises statistical character is one of the main reasons which affect the prediction precision. To solve this problem, extend set-membership estimation is introduced to the target prediction. Result of the simulation shows that, comparing with extend Kalman filter (EKF) , the precision of extend set-membership estimation is as same as that of EKF. And based on the assumption of unknown but bounded noise, extend set-membership estimation has good robustness to overcome the effect coursed by stochastic measurement.%在光电跟踪系统目标状态估计过程中,噪声统计特性不确定是导致滤波精度下降的主要原因之一.针对该问题,研究了一种基于扩展集员估计的目标状态估计方法,并与扩展卡尔曼滤波算法做了比较.结果表明,在保证滤波精度前提下,基于噪声特性未知但能量有界(Unknown but Bounded-UBB)假设的扩展集员估计方法能有效克服噪声统计特性不确定造成的影响,具有较强的工程实用性.
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