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In the field of maneuvering target tracking, the performance of Kalman filter and its improved algorithms depends on the accuracy of pre-designed process noise statistics. When the pre-designed process noise statistics do not match with the actual situation, it will be difficult to obtain a good filtering performance. But unbiased finite impulse response (UFIR) filter does not need the prior knowledge...
We study an unbiased finite impulse response (FIR) filter in applications to discrete-time state space models with polynomial representation of the states. The unique l-degree polynomial FIR filter gain and the estimate variance are found for a general case. The noise power gain (NG) is derived for white Gaussian noises in the model and in the measurement. The filter does not involve any knowledge...
An unbiased finite impulse response (FIR) filter is proposed to estimate the time interval error (TIE) K-degree polynomial model of a local clock in GPS-based timekeeping in presence of noise of arbitrary distribution.
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