An Innovative Asynchronous, Multi-rate, Multi-sensor State Vector Fusion Algorithm for Air Defence Applications

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• 作者：G Shivanand^&lowast ; ; ^{shivlikar@rediffmail.com" class="auth_mail" title="E-mail the corresponding author} ; K Vamshi Krishna Reddy^&lowast ; &lowast ; ; DBN Prasad^&lowast ; &lowast ; &lowast ;
• 关键词：Data fusion ; Kalman Filter
• 刊名：IFAC-PapersOnLine
• 出版年：2016
• 出版时间：2016
• 年：2016
• 卷：49
• 期：1
• 页码：337-342
• 全文大小：506 K

文摘

This paper presents an innovative approach for data fusion of asynchronous, multi-rate, multi-sensor data in real time. This technique is based on state vector data fusion. For air defence applications, the target information from multi sensors is sent to a central control centre to create a complete threat scenario which would be used for taking appropriate decision. This target data needs to be sent in real time, hence there is a need for low bandwidth consuming data fusion algorithms but at the same time there should be minimal degradation in data accuracy. The optimal fusion algorithm requires the entire state covariance information matrix to be transmitted to the data fusion centre, however this requires huge bandwidth for transmission of data. To avoid this generally, only diagonal elements are transmitted at the cost of considerable degradation in performance. The authors present an innovative approach by considering the only covariance of position, velocity and acceleration but by neglecting the cross covariance terms among position, velocity and acceleration. The accuracy of this proposed algorithm is about 95% of that of optimal method but the reduction in bandwidth requirement is of the order of 60%.