Data fusion for ballistic targets tracking using least squares

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• 作者：Dariusz Janczak^a ; ^{djanczak@pb.edu.pl} ; Miroslaw Sankowski^b ; ^{miroslaw.sankowski@ieee.org}
• 关键词：Nonlinear models ; Radar tracking ; Batch estimation ; Least squares
• 刊名：AEU - International Journal of Electronics and Communications
• 出版年：2012
• 出版时间：June, 2012
• 年：2012
• 卷：66
• 期：6
• 页码：512-519
• 全文大小：697 K

文摘

The paper deals with the problem of state estimation of continuous-time nonlinear system using discrete-time measurements from multiple sensors. In particular, the problem of multi-radar tracking of artillery ballistic objects is considered. A batch estimator based on the iterative least squares approach is developed using simplified and accurate models of ballistic flight. The estimator is applied to process the sequences of measurements from radars tracking the same ballistic target. Estimates of the target state over time are computed and their accuracy is compared to the estimates yielded by the extended Kalman filter. Partial estimates from multiple radars are combined using track fusion approach and propagated using the 3 degree of freedom model of ballistic flight. Accuracy of target's firing point estimation is also analysed with respect to the data rates and locations of the radars with respect to the target. Practical aspects of the proposed method are also discussed.