Conference
Spline Probability Hypothesis Density Filter for Nonlinear Maneuvering Target Tracking
Abstract
The Probability Hypothesis Density (PHD) filter is an efficient algorithm for multitarget tracking in the presence of nonlinearities and/or non-Gaussian noise. The Sequential Monte Carlo (SMC) and Gaussian Mixture (GM) techniques are commonly used to implement the PHD filter. Recently, a new implementation of the PHD filter using B-splines with the capability to model any arbitrary density functions using only a few knots was proposed. The …
Authors
Sithiravl R; Chen X; McDonald M; Kirubarajan T
Pagination
pp. 1743-1750
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Publication Date
November 1, 2013
DOI
10.1109/acssc.2013.6810600
Name of conference
2013 Asilomar Conference on Signals, Systems and Computers