Authors: Peter C. Niedfeldt and Randal W. Beard
Abstract:
Estimating the states of multiple dynamic targets is difficult due to noisy and spurious measurements, missed detections, and the interaction between multiple maneuvering targets. In this paper a novel algorithm, which we call the recursive random sample consensus (R-RANSAC) algorithm, is presented to robustly estimate the states of an unknown number of dynamic targets. R-RANSAC was previously developed to estimate the parameters of multiple static signals when measurements are received sequentially in time. The R-RANSAC algorithm proposed in this paper reformulates our previous work to track dynamic targets using a Kalman filter. Simulation results using synthetic data are included to compare R-RANSAC to the GM-PHD filter.
American Control Conference (ACC), 2014
Link:
http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6859273&tag=1
No comments:
Post a Comment