A method comprising: determining, by a sensor-fusion system, a plurality of first candidate object-tracks according to first sensor data obtained from a first set of sensors; determining, by the sensor-fusion system, a set of second object-tracks according to second sensor data obtained from a second set of sensors; for each of the first candidate object-tracks: determining a respective matching error between the first candidate object-track and each of the second object-tracks; computing a respective weight for consideration of matching the first candidate object-track to each of the second object-tracks to be an inverse of the respective matching error between the first candidate object-track and the respective second object-track; applying the respective weight for each of the second object-tracks to the first candidate object-track; determining a respective distribution of all respective weights applied to the second object-tracks for the first candidate object-track; and determining a Kurtosis value of the respective distribution for the first candidate object-track; pruning at least one first candidate object-track from the first candidate object-tracks by: dividing the first candidate object-tracks into two sub-sets including a first subset of the first candidate object-tracks having higher Kurtosis values than a second subset of the first candidate object-tracks, the second subset including the at least one first candidate object-track; and discarding the second subset from the first candidate object-tracks; and matching, by the sensor-fusion system, each second object-track with one or more remaining first candidate object-tracks after the second subset is discarded and the at least one first candidate object-track is pruned. determining, by a sensor-fusion system, a plurality of first candidate object-tracks according to first sensor data obtained from a first set of sensors; determining, by the sensor-fusion system, a set of second object-tracks according to second sensor data obtained from a second set of sensors; for each of the first candidate object-tracks: determining a respective matching error between the first candidate object-track and each of the second object-tracks; computing a respective weight for consideration of matching the first candidate object-track to each of the second object-tracks to be an inverse of the respective matching error between the first candidate object-track and the respective second object-track; applying the respective weight for each of the second object-tracks to the first candidate object-track; determining a respective distribution of all respective weights applied to the second object-tracks for the first candidate object-track; and determining a Kurtosis value of the respective distribution for the first candidate object-track; determining a respective matching error between the first candidate object-track and each of the second object-tracks; computing a respective weight for consideration of matching the first candidate object-track to each of the second object-tracks to be an inverse of the respective matching error between the first candidate object-track and the respective second object-track; applying the respective weight for each of the second object-tracks to the first candidate object-track; determining a respective distribution of all respective weights applied to the second object-tracks for the first candidate object-track; and determining a Kurtosis value of the respective distribution for the first candidate object-track; pruning at least one first candidate object-track from the first candidate object-tracks by: dividing the first candidate object-tracks into two sub-sets including a first subset of the first candidate object-tracks having higher Kurtosis values than a second subset of the first candidate object-tracks, the second subset including the at least one first candidate object-track; and discarding the second subset from the first candidate object-tracks; and dividing the first candidate object-tracks into two sub-sets including a first subset of the first candidate object-tracks having higher Kurtosis values than a second subset of the first candidate object-tracks, the second subset including the at least one first candidate object-track; and discarding the second subset from the first candidate object-tracks; and matching, by the sensor-fusion system, each second object-track with one or more remaining first candidate object-tracks after the second subset is discarded and the at least one first candidate object-track is pruned.