Volume 12, no. 1Pages 156 - 162

Adaptive Estimation of a Moving Object Trajectory Using Sequential Hypothesis Testing

A.V. Tsyganov, Yu.V. Tsyganova, A.V. Golubkov, I.O. Petrishchev
The present paper addresses the problem of adaptive estimation of a moving object trajectory and detection of changes in the motion mode. It is supposed that an object moves along a complex trajectory and at known discrete-time instants it may change its motion to one of three possible modes: a uniform straight line motion or a uniform anticlockwise/clockwise circular motion. We propose a new algorithm for adaptive trajectory estimation that combines a hybrid linear stochastic model of an object trajectory with a bank of competitive Kalman filters and a decision rule based on a sequential hypothesis testing. A detailed description of the decision rule and pseudocode of the proposed algorithm are given. The software implementation of the algorithm is made in Matlab. A numerical example of adaptive estimation of the motion of an object along a complex trajectory consisting of nine different pieces is considered. We have conducted computational experiments with different levels of noise in the measurements. The results confirm the effectiveness of the proposed algorithm.
Full text
adaptive estimation; moving object; sequential hypothesis testing.
1. Kim S., Park J., Lee J. Implementation of Tracking and Capturing a Moving Object Using a Mobile Robot. International Journal of Control, Automation, and Systems, 2005, vol. 3, no. 3, pp. 444-452.
2. Hassani V., Pascoal A.M., Sorensen A.J. A Novel Methodology for Adaptive Wave Filtering of Marine Vessels: Theory and Experiments. Proceedings of the 52nd Annual Conference on Decision and Control (CDC), Florence, Italy, 2013, pp. 6162-6167. DOI: 10.1109/CDC.2013.6760863
3. Bar-Shalom Y., Li X.R., Kirubarajan T. Estimation with Applications to Tracking and Navigation: Theory, Algorithms and Software. New Jersey, John Wiley and Sons, 2002.
4. Semushin I.V., Tsyganov A.V., Tsyganova Yu.V., Golubkov A.V., Vinokurov S.D. Modelling and Estimation of a Moving Object Trajectory. Bulletin of the South Ural State University. Series: Mathematical Modelling, Programming and Computer Software, vol. 10, no. 3, pp. 108-119. DOI: 10.14529/mmp170309
5. Wald A. Sequential Analysis. N.Y.: John Wiley and Sons, 1947.
6. Golubkov A.V., Tsyganov A.V., Tsyganova Yu.V. Adaptive Estimation of an Object Motion Parameters Based on the Hybrid Stochastic Model. Journal of Physics: Conferences Series, 2018, vol. 1096, no. 1, 012166 p. DOI: 10.1088/1742-6596/1096/1/012166