发明名称 MERGING 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 generating a first intensity by combining a first one or more measurements, wherein a first set of track IDs associated with the first intensity includes track IDs corresponding to respective measurements in the first one or more measurements. A second intensity is generated by combining a second one or more measurements, wherein a second set of track IDs associated with the second intensity includes track IDs corresponding to respective measurements in the second one or more measurements. The first set of track IDs is compared to the second set of track IDs, and the first intensity is selectively merged 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.
申请公布号 US2016033276(A1) 申请公布日期 2016.02.04
申请号 US201414448808 申请日期 2014.07.31
申请人 Honeywell International Inc. 发明人 Bageshwar Vibhor L.;Elgersma Michael Ray;Euteneuer Eric A.
分类号 G01C21/00;G01B21/16 主分类号 G01C21/00
代理机构 代理人
主权项 1. A method of tracking multiple objects with a probabilistic hypothesis density filter, the method comprising: generating a first intensity by combining a first one or more measurements from a first one or more sensors, wherein a first set of track IDs includes one or more track IDs provided by the first one or more 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 sensors, wherein a second set of track IDs includes one or more track IDs provided by the second one or more 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 an 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.
地址 Morristown NJ US