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

摘要

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.