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中文摘要：
针对现有基于伪量测的异步融合算法存在的实时性差、融合时刻中心处理器计算负荷大以及引入噪声等相关问题,提出一种新的基于状态转换的多传感器顺序式异步融合算法。新算法通过连续系统离散化获得融合周期内各采样点同融合时刻之间状态的动态关系,并利用该关系来建立相邻两个采样时刻间符合标准Kal-man滤波条件的状态递归方程以及相应的测量方程,然后通过执行顺序Kalman滤波来实现异步数据融合。详细推导了融合算法的具体形式,并通过理论分析和计算机仿真证明了该算法不仅能避免现有基于伪量测的异步融合算法所存在的诸多问题,而且能获得更好的跟踪性能。
英文摘要：
Aiming at the problems which exist in the asynchronous fusion methods based on pseudo-measurements, such as time delay, excessive computation burden at the fusion time, and man-made noises correlation etc. , this paper proposes a novel sequential asynchronous fusion algorithm based on state transform as a re- sult of researching the continuous and distributed multisensor dynamic system. The proposed algorithm establi- shes the dynamic equation of state between the adjoining sampling time by use of the state relation obtained by a discreteprocess between these sampling times and the fusion time. Accordingly, it can obtain a series of new state and measurement equations which accord with the requirements of the standard Kalman filter in the fusion period, and the asynchronous data fusion is finished by using these measurements and these new state equations to perform the sequential Kalman filter. The theoretic analysis shows that the proposed method can not only avoid these problems which exist in the asynchronous fusion methods based on pseudo-measurements but also achieve the better fusion estimate accuracy. It presents the detail form of the proposed method and the computer simulation proves the validity of the proposed algorithm.
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