UPDATING INTENSITIES IN A PHD FILTER BASED ON A SENSOR TRACK ID

In one embodiment, a method of tracking multiple objects with a probabilistic hypothesis density filter is provided. The method includes obtaining measurements corresponding to a first object with at least one sensor, the at least one sensor providing one or more first track IDs for the measurements...

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Bibliographic Details
Main Authors EUTENEUER, ERIC A, ELGERSMA, MICHAEL RAY, BAGESHWAR, VIBHOR L
Format Patent
LanguageEnglish
French
German
Published 03.02.2016
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Summary:In one embodiment, a method of tracking multiple objects with a probabilistic hypothesis density filter is provided. The method includes obtaining measurements corresponding to a first object with at least one sensor, the at least one sensor providing one or more first track IDs for the measurements. A T k+1 first predicted intensity is generated for the first object based on a T k first track intensity. A T k+1 measurement from a first sensor of the at least one sensors is obtained, the first sensor providing a second track ID for the T k+1 measurement. The second track ID is compared to the one or more first track IDs, and the T k+1 first predicted intensity is selectively updated with the T k+1 measurement based on whether the second track ID matches any of the one or more first track IDs to generate a T k+1 first measurement-to-track intensity for the first object.
Bibliography:Application Number: EP20150177590