1. A system for fusing data from a plurality of LiDAR sensors with object data from another sensor, said system comprising: the plurality of LiDAR sensors configured to detect one or more of a plurality of objects in proximity to a host entity; a radar sensor or a vision system configured to detect one or more of the plurality of objects in proximity to the host entity; and a processor in communication with the LiDAR sensors and the radar sensor or the vision system, said processor being configured with an algorithm including steps of; receiving data from the LiDAR sensors at a previous sample time, including object models that identify a position, orientation and velocity of the one or more of the plurality of objects detected by the LiDAR sensors; tracking the object models of the plurality of objects detected by the LiDAR sensors to provide tracked object models; projecting the tracked object models from the previous sample time to provide predicted object models; receiving a plurality of scan returns from the one or more of the plurality of objects detected in a field-of-view of the LiDAR sensors at a current sample time; constructing a scan point cloud from the scan returns; segmenting a plurality of scan points in the scan point cloud into predicted scan clusters where each predicted scan cluster initially identifies an object detected by the LiDAR sensors; matching the predicted scan clusters with the predicted object models to provide matched predicted scan clusters; reading the object data from one or more of the plurality of objects detected by the radar sensor or the vision system; registering the object data to a coordinate frame designated for the scan points of the LiDAR sensors; matching the object data with the predicted object models to provide matched object data; merging the predicted object models that have been identified as separate scan clusters in the previous sample time but are now identified as a single scan cluster in the current sample time using the matched predicted scan clusters and the matched object data; and splitting the predicted object models that have been identified as a single scan cluster in the previous sample time but are now identified as separate scan clusters in the current sample time using the matched predicted scan clusters and the matched object data.