Volume 10, no. 3Pages 108 - 119 # Modelling and Estimation of a Moving Object Trajectory

I.V. Semushin, A.V. Tsyganov, Yu.V. Tsyganova, A.V. Golubkov, S.D. VinokurovA new linear discrete model of the left/right circular motion with the specified radius is constructed. A new algorithm for mathematical modelling of a moving object trajectory

consisting of straight line segments and circular motion under the conditions of incomplete noisy measurements is formulated and implemented. It is shown how to apply algorithms for discrete optimal filtering to the evaluation of such a trajectory. A software package 'Modelling and estimation of a moving object trajectory v1.0' is developed for modelling and estimation of a linear trajectory of a moving object on the basis of discrete models of uniform piecewise linear and circular motion. The results can be applied to solve practical problems of navigation, robotics, signal processing of scanning range finders and others.

Full text- Keywords
- maneuvering moving objects; discrete stochastic model; linear estimation; MATLAB.
- References
- 1. Grewal M.S., Andrews A.P. Kalman Filtering: Theory and Practice. New Jersey, Prentice Hall, 2001.

2. Maybeck P.S. Stochastic Models, Estimation and Control. N.Y., San Francisco, London, Academic Press, 1979.

3. Semushin I.V., Krolivetskaya Yu.M., Petrova E.S. Kalman Filter Oriented Mathematical Model of the Steady-Circle Path. Automation of Control Processes, 2013, no. 4 (34), pp. 14-20. (in Russian)

4. Semushin I.V., Tsyganova Yu.V., Zakharov K.V. Robust Filter Algorithms - Survey and New Results for Ship Navigation. Information Technology and Computing Systems, 2013, no. 4, pp. 90-112. (in Russian)

5. Semushin I.V. Computational Methods of Algebra and Estimation. Ulyanovsk, UlSTU Publishers, 2011.

6. Bierman G.J. Factorization Methods For Discrete Sequential Estimation. N.Y., Academic Press, 1977.