Track-to-track fusion with dissimilar sensors

@article{Saha1996TracktotrackFW,
  title={Track-to-track fusion with dissimilar sensors},
  author={R. K. Saha},
  journal={IEEE Transactions on Aerospace and Electronic Systems},
  year={1996},
  volume={32},
  pages={1021-1029}
}
  • R.K. Saha
  • Published 1996 in
    IEEE Transactions on Aerospace and Electronic…
An analysis is described of a kinematic state vector fusion algorithm when tracks are obtained from dissimilar sensors. For the sake of simplicity, it is assumed that two dissimilar sensors are equipped with nonidentical two-dimensional optimal linear Kalman filters. It is shown that the performance of such a track-to-track fusion algorithm can be improved if the cross-correlation matrix between candidate tracks is positive. This cross-correlation is introduced by noise associated with target… CONTINUE READING
Highly Cited
This paper has 42 citations. REVIEW CITATIONS

From This Paper

Figures, tables, and topics from this paper.

Citations

Publications citing this paper.
Showing 1-10 of 30 extracted citations

References

Publications referenced by this paper.
Showing 1-10 of 19 references

Fusion of sensors with dissimilar measurement/tracking accuracies

  • A. M. Haimovich, J. Yosko, R. J. Greenberg, M. A. Parisi, D. Becker
  • IEEE Transactions on Aerospace and Electronic…
  • 1993
1 Excerpt

Analytical evaluation of an ESM/radar track association

  • R. K. Saha
  • Proceedings of the SPIE Conference on Signal and…
  • 1992
1 Excerpt

Matrices: Methods and Applications

  • S. Barnett
  • 1990
1 Excerpt

The effect of the common process noise on the two-sensor fused-track covariance

  • Y. Bar-Shalom
  • IEEE Transactions on Aerospace and Electronic…
  • 1986
1 Excerpt

On the track-to-track correlation problem

  • Y. Bar-Shalom
  • IEEE Transactions on Automatic Control, AC-26,
  • 1981
2 Excerpts

Kronecker products and matrix calculus in system theory

  • J. W. Brewer
  • IEEE Transactions on Circuits and Systems,
  • 1978
1 Excerpt

Similar Papers

Loading similar papers…