By Lawrence D Stone
This moment variation has passed through colossal revision from the 1999 first version, spotting lot has replaced within the a number of goal monitoring box. essentially the most dramatic alterations is within the common use of particle filters to enforce nonlinear, non-Gaussian Bayesian trackers. This publication perspectives a number of goal monitoring as a Bayesian inference challenge. inside this framework it develops the speculation of unmarried goal monitoring. as well as supplying an in depth description of a easy particle filter out that implements the Bayesian unmarried aim recursion, this source offers a variety of examples that contain using particle filters.
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Additional info for Bayesian Multiple Target Tracking
E. high rate of peaks in the radar return that “look like” targets). The statistical behavior of this spiky clutter is described by a two-scale model. In this model the received radar signal is represented as a compound process where a fast speckle process is modulated by a slower process describing the scattering features in a radar cell. Over short time intervals (up to approximately 250 ms) the intensity observed in a fixed-range cell is Rayleighdistributed. Over longer times, the mean of the Rayleigh component follows a gamma distribution whose shape parameter is a function of the radar and ocean parameters such as grazing angle, resolution cell size, frequency, look direction, and sea state.
The actual comparison of peak values to a threshold is performed on the likelihood ratios as a function of both position and velocity. 15 are striking. 15. 15. 15, it will appear as a straight line. The line will slant to the right if range is increasing and to the left if it is decreasing. The likelihood peaks line up very well along the target path to form an almost straight line. The peaks disappear when the periscope submerges. 16(a). Here we can see the buildup of the log likelihood ratio along the target track.
1 hr over a period of two hours. At each time only one measurement is generated; the measurements alternate between the two targets, first on target 1 then on target 2. ) The values of the measurements are obtained by adding an offset drawn from the measurement error distribution to the actual target position at the time of the measurement. 17 Tracks and prior position distributions for targets 1 and 2. The circles show the 95% containment ellipses for the prior distributions on the locations of the targets.