The basic problem with angle-only or bearings-only tracking is to estimate the
trajectory of a target (i.e., position and velocity) by using noise corrupted sensor
angle data. In this thesis, the tracking platform is an Aerial Vehicle and the target
is simulated as another Aerial Vehicle. Therefore, the problem can be defined as
a single-sensor bearings only tracking. The state consists of relative position and
velocity between the target and the platform. In the case where both the target
and the platform travel at constant velocity, the angle measurements do not
provide any information about the range between the target and the platform. The
platform has to maneuver to be able to estimate the range of the target. Two
problems are investigated and tested on simulated data. The first problem is
tracking non-maneuvering targets. Extended Kalman Filter (EKF), Range
Parameterized Kalman Filter and particle filter are implemented in order to track
non-maneuvering targets. As the second problem, tracking maneuvering targets
are investigated. An interacting multiple model (IMM) filter and different particle
filter solutions are designed for this purpose. Kalman filter covariance matrix
initialization and regularization step of the regularized particle filter are discussed
in detail.
Identifer | oai:union.ndltd.org:METU/oai:etd.lib.metu.edu.tr:http://etd.lib.metu.edu.tr/upload/12613048/index.pdf |
Date | 01 February 2011 |
Creators | Bingol, Haluk Erdem |
Contributors | Demirekler, Mubeccel |
Publisher | METU |
Source Sets | Middle East Technical Univ. |
Language | English |
Detected Language | English |
Type | M.S. Thesis |
Format | text/pdf |
Rights | To liberate the content for public access |
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