Object tracking is one of the most important tasks in computer vision. The unscented particle filter algorithm has been extensively used to tackle this problem and achieved a grea...
Qingdi Wei, Weiming Hu, Xi Li, Xiaoqin Zhang, Yang...
In this work the variance of the error of analyzed wind fields obtained from an ensemble Kalman filter is used as a criterion with which to optimize radar network scanning strat...
We consider state estimation of a Markov stochastic process using an ad hoc wireless sensor network (WSN) based on noisy linear observations. Due to power and bandwidth constraint...
Eric J. Msechu, Alejandro Ribeiro, Stergios I. Rou...
Abstract—The paper studies the convergence properties of the estimation error processes in distributed Kalman filtering for potentially unstable linear dynamical systems. In par...
Soummya Kar, Shuguang Cui, H. Vincent Poor, Jos&ea...
A novel region-based multiple object tracking framework based on Kalman filtering and elastic matching is proposed. The proposed Kalman filtering-elastic matching model is genera...