A comparison of three non-linear filters
Automatica (Journal of IFAC)
Digital synthesis of non-linear filters
Automatica (Journal of IFAC)
Recursive bayesian estimation using gaussian sums
Automatica (Journal of IFAC)
A Bayesian approach to joint tracking and identification of geometric shapes in video sequences
Image and Vision Computing
Cost-function-based hypothesis control techniques for multiple hypothesis tracking
Mathematical and Computer Modelling: An International Journal
| Hi-index | 22.14 |
The joint problems of identification, tracking and prediction in a multi-target, multi-sensor environment are considered. Measurements giving information about the location of each target are to be processed in order to identify the type and to estimate the present state of each target. There is no a priori information relating a given measurement to a particular target. Once a target is properly identified its impact point is to be predicted. The previously developed Gaussian sum approach is used. The a posteriori density of the state of the target giving rise to the latest measurement is derived and an inherently parallel implementation of the algorithm is indicated.