Fundamentals of Kalman Filtering and Applications to GNSS
Fundamentals of Kalman Filtering and Applications to GNSS
Fundamentals of Kalman Filtering and Applications to GNSS
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White Noise<br />
• Define white noise the limit <strong>of</strong> an exponential process<br />
as<br />
– Correlation time <br />
2s <br />
– <br />
2<br />
0 constant<br />
<br />
– In the limit<br />
<br />
<br />
<br />
<br />
<br />
<br />
– Comments<br />
2s<br />
<br />
<br />
2<br />
2s<br />
<br />
<br />
2<br />
<br />
<br />
1 0<br />
<br />
<br />
<br />
<br />
• White noise variance 0 <br />
2s 2<br />
• Parameter characterizing white noise is not dimensionally the same<br />
as s 2<br />
<br />
• True white noise does not exist in nature due <strong>to</strong> infinite variance<br />
3<br />
2<br />
<br />
<br />
<br />
<br />
<br />
<br />
1<br />
2<br />
s e<br />
<br />
<br />
2<br />
2s<br />
<br />
<br />
<br />
2 2<br />
<br />
<br />
1 2 3<br />
<br />
<strong>Kalman</strong> <strong>Filtering</strong> Consultant Associates © 2011<br />
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