Spatial voting with data modeling for behavior based tracking and discrimination of human from fauna from GMTI radar tracks
Holger M. Jaenisch · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2012
We introduce a novel method of using ground track indicators in conjunction with our Spatial Voting (SV) algorithm and data fusing Data Models to distinguish target types from motion signatures alone. We simulate 3 different types of behaviors: rabbit, coyote, and human. We then apply SV to combine individual position reports obtained via radar track indicators into object tracks that are then characterized using the methods shown in this paper. The features obtained from this characterization are then used as input into a Data Model equation classifier or a look-up table classifier to label the track behavior as either rabbit, coyote, or human. Our results and methods show promise and are presented here.