A tracking system, comprising: one or more processing devices within a vehicle; a plurality of sensors within the vehicle and coupled to the one or more processing devices; and one or more data storage devices within the vehicle and including instructions which, when executed by the one or more processing devices, cause the one or more processing devices to track multiple objects in an environment around the vehicle with a probabilistic hypothesis density filter, wherein the instructions cause the one or more processing devices to perform a method comprising: generating a first intensity by combining a first one or more measurements from a first one or more of the sensors, wherein a first set of track identifiers, IDs, includes one or more track IDs provided by the first one or more of the sensors corresponding to their respective measurement in the first one or more measurements, wherein the first intensity includes a weight, a state mean vector, and a state covariance matrix of statistics of a track of an object at a first time; generating a second intensity by combining a second one or more measurements from a second one or more of the sensors, wherein a second set of track IDs includes one or more track IDs provided by the second one or more of the sensors corresponding to their respective measurement in the second one or more measurements, wherein the second intensity includes a weight, a state mean vector, and a state covariance matrix of statistics of a track of the object at the first time; comparing the first set of track IDs to the second set of track IDs; and selectively merging the first intensity with the second intensity based on whether any track IDs in the first set of track IDs match any track IDs in the second set of track IDs. one or more processing devices within a vehicle; a plurality of sensors within the vehicle and coupled to the one or more processing devices; and one or more data storage devices within the vehicle and including instructions which, when executed by the one or more processing devices, cause the one or more processing devices to track multiple objects in an environment around the vehicle with a probabilistic hypothesis density filter, wherein the instructions cause the one or more processing devices to perform a method comprising: generating a first intensity by combining a first one or more measurements from a first one or more of the sensors, wherein a first set of track identifiers, IDs, includes one or more track IDs provided by the first one or more of the sensors corresponding to their respective measurement in the first one or more measurements, wherein the first intensity includes a weight, a state mean vector, and a state covariance matrix of statistics of a track of an object at a first time; generating a second intensity by combining a second one or more measurements from a second one or more of the sensors, wherein a second set of track IDs includes one or more track IDs provided by the second one or more of the sensors corresponding to their respective measurement in the second one or more measurements, wherein the second intensity includes a weight, a state mean vector, and a state covariance matrix of statistics of a track of the object at the first time; comparing the first set of track IDs to the second set of track IDs; and selectively merging the first intensity with the second intensity based on whether any track IDs in the first set of track IDs match any track IDs in the second set of track IDs. generating a first intensity by combining a first one or more measurements from a first one or more of the sensors, wherein a first set of track identifiers, IDs, includes one or more track IDs provided by the first one or more of the sensors corresponding to their respective measurement in the first one or more measurements, wherein the first intensity includes a weight, a state mean vector, and a state covariance matrix of statistics of a track of an object at a first time; generating a second intensity by combining a second one or more measurements from a second one or more of the sensors, wherein a second set of track IDs includes one or more track IDs provided by the second one or more of the sensors corresponding to their respective measurement in the second one or more measurements, wherein the second intensity includes a weight, a state mean vector, and a state covariance matrix of statistics of a track of the object at the first time; comparing the first set of track IDs to the second set of track IDs; and selectively merging the first intensity with the second intensity based on whether any track IDs in the first set of track IDs match any track IDs in the second set of track IDs.