Thursday, November 06, 2014

Lab Meeting November 7th, 2014 (Jeff): Multiple Target Tracking using Recursive RANSAC

Title: Multiple Target Tracking using Recursive RANSAC

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








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