Abstract:
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This paper describes an underwater mobile target
localization and tracking by using an autonomous surface vehicle
for which the successive ranges between the target and the
reference are the only information. In a dynamic system, such as
range-only single-beacon underwater target tracking, a statespace
model can be characterized, where the state vector may
include position, and velocity of the mobile underwater target.
Moreover, the range observations can come from a mobile
autonomous vehicle, which is used as a moving landmark. Then, a
nonlinear Bayesian filtering algorithm can be used to make
extrapolations on the state vector from the observations, in order
to obtain the target position at each instant of time. In this paper
we consider the use of Particle Filter (PF) to perform such
localization and tracking where its performance and
characterization is studied under different scenarios |