An algorithm that integrates dissimilar sensor tracks for today's platform configurations

Today's highly capable threats, low reaction time scenarios, diverse sensor environments, and intelligent adversarial jamming capabilities require a fast and robust tracking fusion process. The fusion of all organic (belonging to the same platform, e.g., ship, airplane, submarine, ...) sensor tracking processes improves the operational effectiveness of any platform be it fire control or situational awareness. This article discusses two concepts relevant in many existing platforms: the fusion of sensors tracks, and the optimal use of legacy systems in the fusion process.

[1]  W. Dale Blair,et al.  Enhanced electronically scanned array resource management through multisensor integration , 1997, Optics & Photonics.

[2]  J. J. Sudano.  A least square algorithm with covariance weighting for computing the translational and rotational errors between two radar sites , 1993, Proceedings of the IEEE 1993 National Aerospace and Electronics Conference-NAECON 1993.

[3]  Arthur Gelb,et al.  Applied Optimal Estimation , 1974 .

[4]  Analytical solution for a steady-state Kalman filter tracker with random power spectral density process noise , 1995, Proceedings of the IEEE 1995 National Aerospace and Electronics Conference. NAECON 1995.