Use of IFS for track fusion
Jingyun Li, Patrick C. Y. Yip, Henry Leung, Éloi Bossé · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1996
In a multiple radar tracking environment, measurements form different sensors observing the same target or track are required to be combined optimally in order to provide accurate information. One problem that has to be overcome before a weighted combination of the measurements can be made is the possible difference in scanning periods used by the sensors. The different scanning periods produce different resolutions that must be reconciled before the data are fused. Iterated function systems (IFS) have been used successfully for interpolation and data compression. When a measured track is to be fused with another of different resolution, the underlying problem is one of accurate interpolation. Tracks, be they linear or curvilinear, have certain amount of self-similarity as a geometrical object, just as natural coastlines are found to be fractal. Linear and piece-wise linear IFS have been shown to provide excellent interpolation and compression even for non-fractal objects. In this work, we report two interpolation schemes based on liner IFS for tracks measured at different resolutions. Simulations using linear and curvilinear tracks are performed and the results are compared to those using linear interpolations.