An executing of track fusion using various algorithms has been demonstrated.The sensor measurements of these targets are modeled using Kalman filter（KF）and interacting multiple models（IMM）filter.The joint probabilistic data association filter（JPDAF）and neural network fusion（NNF）algorithms were used for targets tracking.Track association and fusion algorithm are executed to get the fused track data for various scenarios

from two sensors tracking a single target to three sensors tracking three targets

to evaluate the effects of multiple and dispersed sensors for single target

two targets

and multiple targets.The targets chosen were distantly spaced

closely spaced and crossing.Performance of different filters was compared and fused trajectory is found to be closer to the true target trajectory as compared to that for any of the sensor measurements of that target.