Based on
the statistical characteristics analysis of random noise power and
autocorrelation function, this paper proposes a de-noising method for track
state detection signal by using Empirical Mode Decomposition (EMD). This method
is used to noise reduction refactoring for the first Intrinsic Mode Function
(IMF) component in accordance with the “random sort-accumulation-average-refactoring\"
order. Signal autocorrelation function characteristics are used to determine
the cut-off point of the dominant mode. This method was applied to test signals
and the actual inertial unit signals; the experimental results show that the
method can effectively remove the noise and better meet the precision
requirement.
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