A Research on the Weight of Interactive Multiple Model in Maneuvering Target Tracking

Abstract:

The establishment of the target model is the key of maneuvering target tracking. The previous research on interactive multiple model, which is applied on tracking extensively, focused on the design of the model set and fusion with other algorithms, while there is less study on change mechanisms of the model weight. In light of this, the impetus behind this paper is to do some analysis which based on the model weight of different trajectories, reveal the change rule. Finally, the validity of the proposed approach is demonstrated by simulation.

• Periodical: Applied Mechanics and Materials (Volumes 568-570)
• Pages: 1008-1011
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.568-570.1008
• Online since: June 2014
• Authors: Ming Yong Liu, Yang Li*, Xiao Jian Zhang
• Keywords: Interactive Multiple Model, Target Tracking, Weight

References

[1] Blom P. An efficient filter for abruptly changing systems. The 23rd IEEE Conference on Decision and Control. 1984, 23: 656-658.

DOI: 10.1109/cdc.1984.272089

[2] Blom H A P, Bar-Shalom Y. The interacting multiple model algorithm for systems with Markovian switching coefficients. Automatic Control, IEEE Transactions on, 1988, 33(8): 780-783.

DOI: 10.1109/9.1299

[3] Mazor E, Averbuch A, Bar-Shalom Y, et al. Interacting multiple model methods in target tracking: a survey. Aerospace and Electronic Systems, IEEE Transactions on, 1998, 34(1): 103-123.

DOI: 10.1109/7.640267

[4] Johnston L A, Krishnamurthy V. An improvement to the interacting multiple model (IMM) algorithm. Signal Processing, IEEE Transactions on, 2001, 49(12): 2909-2923.

DOI: 10.1109/78.969500

[5] Sastry S. Nonlinear systems: analysis, stability, and control. New York: Springer, (1999).

[6] Farmer M E, Hsu R L, Jain A K. Interacting multiple model (IMM) Kalman filters for robust high speed human motion tracking. Pattern Recognition, 2002. Proceedings. 16th International Conference on. IEEE, 2002, 2: 20-23.

DOI: 10.1109/icpr.2002.1048226

[7] Ronquist F, Huelsenbeck J P. MrBayes 3: Bayesian phylogenetic inference under mixed models. Bioinformatics, 2003, 19(12): 1572-1574.

DOI: 10.1093/bioinformatics/btg180

[8] Jo K, Chu K, Sunwoo M. Interacting multiple model filter-based sensor fusion of GPS with in-vehicle sensors for real-time vehicle positioning. Intelligent Transportation Systems, IEEE Transactions on, 2012, 13(1): 329-343.

DOI: 10.1109/tits.2011.2171033

[9] Cho T, Lee C, Choi S. Multi-sensor fusion with interacting multiple model filter for improved aircraft position accuracy. Sensors, 2013, 13(4): 4122-4137.

DOI: 10.3390/s130404122