Abstract
So far, all tests on Kalman filters have been performed in the time domain. However, it is shown that conventional signal-processing tools such as frequency response can be successfully applied for the performance analysis. The concept of frequency response as applied to Kalman filters is based on its variation with time. Consequently, it is defined with respect to a definite observation window. It is also shown that the ratio of the initial error covariance matrix terms to the measurement noise variance, not the absolute values, is the relevant statistical quantity. The same principle applies to the ratio of the process noise covariance matrix diagonal terms to the noise measurement variance.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
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