Using Dempster-Shafer Fusion for Personnel Intrusion Detection

New technique enables the use of ultrasonic micro-doppler and PIR sensors for improved security.

US Army RDECOM-ARDEC, Picatinny, New Jersey

The Dempster-Shafer (D-S) mass function is used in effect as a common representation of heterogeneous sensor data. In order to cast each data source in this form, first the raw data is reduced to points in a multi-dimensional feature space specific to each sensor. From there, an approach is outlined that uses a distance metric in the feature space to assign mass to each state in the class hierarchy. This hierarchy begins with the full frame of discernment which represents complete uncertainty. From there it proceeds as an n-array tree broken down into further subclasses until the finest granularity of classification for the specific sensor is reached.

For an input point to be classified, mass is assigned iteratively down the tree. In doing so, two key steps are taken. First, the uncertainty is estimated as a function of the ratio of the distance between the two closest child nodes. If the input point is deemed equidistant from the child nodes, there is a great deal of uncertainty and the mass function should reflect that. On the other hand, significant disparity indicates a much greater likelihood of one subclass. This distinction leads to the second step, where any mass not assigned to uncertainty is split between the child nodes as a function of the ratio of their distances.