Data fusion for ballistic targets tracking using least squares

Abstract 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.

[1]  Jack G. Rudd,et al.  Surveillance and tracking of ballistic missile launches , 1994, IBM J. Res. Dev..

[2]  Peter Willett,et al.  Projectile Identification and Impact Point Prediction , 2010, IEEE Transactions on Aerospace and Electronic Systems.

[3]  George M Siouris,et al.  Missile Guidance and Control Systems , 2004 .

[4]  S. Immediata,et al.  Comparison of recursive and batch processing for impact point prediction of ballistic targets , 2005, IEEE International Radar Conference, 2005..

[5]  Vesselin P. Jilkov,et al.  A survey of maneuvering target tracking: approximation techniques for nonlinear filtering , 2004, SPIE Defense + Commercial Sensing.

[6]  W. Fishbein.  Firefinder, a radar forty years in the making , 2008, IEEE Transactions on Aerospace and Electronic Systems.

[7]  Gabriel Frenkel,et al.  Multisensor tracking of ballistic targets , 1995, Optics & Photonics.

[8]  Branko Ristic,et al.  CRLB and ML for parametric estimate: New results , 2006, Signal Process..

[9]  D. L. Hall,et al.  Mathematical Techniques in Multisensor Data Fusion , 1992 .

[10]  Michael Athans,et al.  A comparison of three non-linear filters , 1969, Autom..

[11]  A. Farina,et al.  Tracking a ballistic target: comparison of several nonlinear filters , 2002 .

[12]  D. Janczak,et al.  The GLR failure detection algorithm for a class of nonlinear dynamic models with application to radar tracking problems , 2008, 2008 International Radar Symposium.

[13]  S. Musick,et al.  Projectile launch point estimation from radar measurements , 2005, Proceedings of the 2005, American Control Conference, 2005..