In this section
@article{Clark:2006:10.1109/TSP.2007.894378,
author = {Clark, JMC and Robbiati, SA and Vinter, RB},
doi = {10.1109/TSP.2007.894378},
journal = {IEEE Trans Signal Processing},
pages = {3218--3226},
title = {The Shifted Rayleigh Mixture Filter for Bearings-only Tracking of Manoeuvering Targets},
url = {http://dx.doi.org/10.1109/TSP.2007.894378},
volume = {55},
year = {2006}
}
TY - JOUR
AB - This paper introduces the shifted Rayleigh mixture filter (SRMF), which is based on jump Markov linear systems. The formulation permits the presence of clutter. For bearings-only tracking problems involving maneuvering targets, the conditional density of the target state given the available measurements evolves as a growing mixture of probability density functions associated with a history of manoeuvre "modes." Similar to other "mixture" algorithms, the SRMF approximates this conditional density by a Gaussian mixture of fixed order. Unlike the extended or unscented Kalman filters,, the shifted Rayleigh filter incorporates an exact calculation of the posterior density, when the prior is assumed to be Gaussian, given the latest bearings measurement. Computer simulations are provided to demonstrate the performance of the algorithm.
AU - Clark,JMC
AU - Robbiati,SA
AU - Vinter,RB
DO - 10.1109/TSP.2007.894378
EP - 3226
PY - 2006///
SN - 1053-587X
SP - 3218
TI - The Shifted Rayleigh Mixture Filter for Bearings-only Tracking of Manoeuvering Targets
T2 - IEEE Trans Signal Processing
UR - http://dx.doi.org/10.1109/TSP.2007.894378
UR - http://hdl.handle.net/10044/1/4681
VL - 55
ER -