Konferenzbeitrag
Adaptive state multiple-hypothesis tracking
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Text/Conference Paper
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Datum
2006
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Verlag
Gesellschaft für Informatik e.V.
Zusammenfassung
In tracking algorithms where measurements from various sensors are combined the track state representation is usually dependent on the type of sensor information that is received. When a multi-hypothesis tracking algorithm is used the probabilities of the different hypotheses containing tracks in different representations need to be re-evaluated when track state representations are changed. For the particular case of trilateration a method is presented to adapt the state representation as more information becomes available. A discussion is given on how to re-evaluate the probabilities of the hypotheses leading to a method for the trilateration case. This is illustrated by a simple example.