A forward prediction based out of sequence measurement processing method for Kalman and IMM filtering

Download

OZAN_EREL_THESIS.pdf

Date

2022-12-13

Author

Erel, Ozan

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

120
views

103
downloads

Processing measurements from the same target which arrive at the processing center not in the order they were obtained (i.e., out of sequence) due to delayed communications is a challenging (OOSM) problem in target-tracking applications. If this problem is not given special care, the quality of the tracking may degrade rather than improve. Therefore, this thesis is focused on the study of forward prediction based OOSM processing methods for linear Gaussian systems and their extension for jump Markov linear systems. The main idea of these methods is to fuse a forward-predicted version of a past target track which incorporates the OOSM, with the current track. Among the proposed methods for linear Gaussian systems, the best-performing one turns out to be a preferable option since it performs close to existing solutions and has similar computational cost and data storage requirements with them. In the case of jump Markov linear systems, as well, the best-performing proposed method seems to be a good option for practical applications when the optimization parameter used in its fusion step can be chosen smaller to reduce the computational cost without experiencing considerable performance degradation.

Subject Keywords

Out of sequence measurement, Track fusion, Interacting multiple filter, Kalman filter

URI

https://hdl.handle.net/11511/101350

Collections

Graduate School of Natural and Applied Sciences, Thesis

Suggestions

OpenMETU
Core

A Variational Measurement Update for Extended Target Tracking With Random Matrices Orguner, Umut (2012-07-01) This correspondence proposes a new measurement update for extended target tracking under measurement noise when the target extent is modeled by random matrices. Compared to the previous measurement update developed by Feldmann et al., this work follows a more rigorous path to derive an approximate measurement update using the analytical techniques of variational Bayesian inference. The resulting measurement update, though computationally more expensive, is shown via simulations to be better than the earlier...
An interactive ranking-based multi-criteria choice algorithm with filtering: Applications to university selection Karakaya, Gülşah (Orta Doğu Teknik Üniversitesi (Ankara, Turkey), 2019-6) In this study, we develop an interactive algorithm to converge to the most preferred alternative of a decision maker (DM) among a set of discrete alternatives. The algorithm presents a limited number of alternatives to the DM and collects preference ranking of them iteratively. The preferences are modeled by a flexible and realistic preference function. To improve the performance, the alternatives presented are determined by a filtering method. We compare our algorithm with benchmark algorithms on nume...
A PHD Filter for Tracking Multiple Extended Targets Using Random Matrices Granstrom, Karl; Orguner, Umut (2012-11-01) This paper presents a random set based approach to tracking of an unknown number of extended targets, in the presence of clutter measurements and missed detections, where the targets' extensions are modeled as random matrices. For this purpose, the random matrix framework developed recently by Koch et al. is adapted into the extended target PHD framework, resulting in the Gaussian inverse Wishart PHD (GIW-PHD) filter. A suitable multiple target likelihood is derived, and the main filter recursion is present...
A HEURISTIC PREPROCESSOR SUPPORTED ALGORITHM FOR THE CAPACITATED PLANT LOCATION PROBLEM YAGIZ, O (1991-03-01) The capacitated plant location problem is an example of a binary problem that is a special case of the mixed integer programming problem. General solution methods, which can be used to solve any mixed integer programming problem, prove to be inefficient when applied to the capacitated plant location problem. Heuristic procedures, on the other hand, are effective means to obtain good, possibly optimal, solutions, but their optimality cannot be guaranteed. In this paper we developed an exact algorithm for ...
A CAD environnnent for digital filters using a VerilogHDL based functional bit-serial compiler Akın, Tayfun (1998-12-16) This paper reports the development of a highly integrated CAD environment for area efficient implementation of digital filters using commercially available CAD tools. The environment establishes a plain interface between CADENCE (an IC design framework), MATLAB (a mathematical computation tool), and BITMAP (a new custom-developed filter compiler). The new compiler allows the functional description of the target filter in the Verilog hardware description language (VerilogHDL), generating technology independe...

Citation Formats

O. Erel, “A forward prediction based out of sequence measurement processing method for Kalman and IMM filtering,” M.S. - Master of Science, Middle East Technical University, 2022.