【作者】 刘双剑； 倪红霞； 葛泉波； 文成林；

【Author】 LIU Shuang-jian1,NI Hong-xia1,GE Quan-bo2,WEN Cheng-lin1(1.College of Automation,Hangzhou Dianzi Universiy,Hangzhou 310018,China;2.Department of Electrical Automation,Shanghai Maritime University,Shanghai 200135,China)

【机构】 杭州电子科技大学自动化学院； 上海海事大学电气自动化系；

【摘要】 在处理异步目标航迹融合问题时,为降低复杂度,通常会忽略部分相关性,但这会给融合精度带来很大的影响。为了提高融合精度,以一类异步采样系统为研究对象,在考虑局部预测估计误差之间的相关性的情况下,依据融合估计误差协方差矩阵的迹最小准则,推导出一种最优异步多传感器预测航迹融合算法。通过与现有的某种异步航迹预测融合算法相比,验证该算法具有较高的融合估计精度,并通过简要的算法分析和计算机仿真验证了新算法的优越性。更多还原

【Abstract】 In processing asynchronous target track problems,to reduce complexity,some relativity may be ignored,but it may affect fusion precision seriously.To resolve this problem,based on a simple asynchronous sampling system,an optimal prediction weighted fusion algorithm of target tracks for asynchronous system is proposed by minimizing the track of the fusion estimation error covariance matrix and considering the correlation between the local predict estimate errors.Compared with the existing asynchronous prediction track algorithms,the proposed algorithm is more accurate.The simple analysis of the algorithm and simulation show the advantage of the new algorithm.更多还原