Abstract
At this point, we have derived the Kaiman filter, presented some of its important properties, and demonstrated some simple examples. In this chapter, we examine some applications employing the Kaiman filter. We first present the problem of tracking a single target based on noisy measurements. In this case, the SMM may be unstable, since the position of the target need not be zero-mean. We also consider three special cases of Kaiman filtering: the case of colored (non-white) process noise, the case of correlated process and measurement noises, and the case of colored measurement noise. The target tracking problem is revisited for the case of measurements in polar, rather than Cartesian, form. Finally, we show how the Kaiman filter can be used to estimate the parameters of a LTI system.
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© 1999 Springer-Verlag London
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Kamen, E.W., Su, J.K. (1999). Kalman Filter Applications. In: Introduction to Optimal Estimation. Advanced Textbooks in Control and Signal Processing. Springer, London. https://doi.org/10.1007/978-1-4471-0417-9_7
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DOI: https://doi.org/10.1007/978-1-4471-0417-9_7
Publisher Name: Springer, London
Print ISBN: 978-1-85233-133-7
Online ISBN: 978-1-4471-0417-9
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