This Masters Thesis considers tracking of ground targets. Since ground targets often are difficult to detect with sensors a track is easily lost in ground target tracking. The main question in this thesis is whether information on close targets and observations of them can be used to make the tracking more reliable. An algorithm using Kalman filters and JPDA-association to create a group track for vehicles travelling together has been implemented in Matlab. Using the state of the centre of the group the state of a vehicle in the group can be updated. The result of updating vehicles states with the state of the centre of the group is that the relative decrease in lost tracks is improved with up to 53 % in the studied case.

<p>This Masters Thesis considers tracking of ground targets. Since ground targets often are difficult to detect with sensors a track is easily lost in ground target tracking. The main question in this thesis is whether information on close targets and observations of them can be used to make the tracking more reliable. An algorithm using Kalman filters and JPDA-association to create a group track for vehicles travelling together has been implemented in Matlab. Using the state of the centre of the group the state of a vehicle in the group can be updated. The result of updating vehicles states with the state of the centre of the group is that the relative decrease in lost tracks is improved with up to 53 % in the studied case.</p>