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The training length is T=20.
It is notable that the bandwidth is wasted when the training length is increased.
In order to improve the performance of this estimator, the training length may be increased.
In the Rayleigh fading model, increasing the training length improves the normalized TMSE of the estimators.
Then, the training length can be reduced in the presence of the Rician channel model.
In the following, it is assumed that the channel is quasi time-invariant over the training length (block fading).
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The train length is typically L = 200 or 400 m.
The moment reference point is set to be located at ground level in the midway of the train length.
However, it does not change much along the train length except in a small region close to the nose.
The results show that the train length estimation model obtained good computation accuracy and the calibration method was effective in estimating the real train path trajectories.
User data would normally include but are not limited to Tractive effort values Rolling resistance values Load and weight of the train Length of train Length of the tracks Nature of tracks (for example bad or good adhesion) Power.
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