Resampling using Random Networks

  • FUSION1.avi: This figure show the simulation of various filters for the 1D linear Gaussian model. The blue line is the ground truth. The red solid line is the filter estimate. The magenta dots are the particles. The sensor noise variance is 8m.

  • FUSION2.avi: This figure corresponds to the non-linear image sensing model. The figure shows the 30 sensor images fed to the filters. The target is present all the time. The noise standard deviation at each pixel of the 20x20 frame is 4.

  • FUSION3.avi: This figure shows the simulation of various filters for the image sensing model. The noisy image fed to the filters at each time step can be seen in the above video. The blue line is the ground truth. The red solid line is the filter estimate. The magenta dots are the particles.

  • FUSION4.avi: This figure show the simulation of various filters for the 1D linear Gaussian model in a cluttered environment. The probability of missing a target is 0.2. The red solid line is the filter estimate which is the mean of the particles. The cyan circles are the observations (target detections as well as false alarms). The actual target position (is not shown in the video) moves in a straight line fashion from 15m to 82m in 80 seconds.