Heterogeneous track-to-track fusion

@article{Yuan2011HeterogeneousTF,
  title={Heterogeneous track-to-track fusion},
  author={Ting Yuan and Yaakov Bar-Shalom and Xin Tian},
  journal={14th International Conference on Information Fusion},
  year={2011},
  pages={1-8}
}
Track-to-track fusion using estimates from multiple sensors can achieve better estimation performance than a single sensor. If the local sensors use different system models in different state spaces, the problem of heterogeneous track-to-track fusion arises. Compared with homogeneous track-to-track fusion that assumes the same system model for different sensors, the heterogeneous case poses two major challenges. First, the model heterogeneity problem, namely, that we have to fuse estimates from… CONTINUE READING

Citations

Publications citing this paper.
Showing 1-10 of 17 extracted citations

References

Publications referenced by this paper.
Showing 1-10 of 12 references

Tracking and Data Fusion

  • Y. Bar-Shalom, P. K. Willett, X. Tian
  • YBS Publishing,
  • 2011
Highly Influential
19 Excerpts

Estimation with Applications to Tracking and Navigation: Algorithms and Software for Information

  • Y. Bar-Shalom, X. R. Li, T. Kirubarajan
  • 2001
Highly Influential
9 Excerpts

Heterogeneous Track-to-Track Fusion

  • T. Yuan, Y. Bar-Shalom, X. Tian
  • J. of Advances in Information Fusion, submitted…
  • 2011
2 Excerpts

Impact Point Prediction for Short Range Thrusting Projectiles

  • T. Yuan, Y. Bar-Shalom, P. K. Willett, D. Hardiman
  • Proc. SPIE conference Signal and Data Processing…
  • 2010
1 Excerpt

Kalman filter versus IMM estimator: when do we need the latter?

  • T. Kirubarajan, Y. Bar-Shalom
  • IEEE Trans. Aerosp. Electronic Systems,
  • 2003

Similar Papers

Loading similar papers…