Representation of covariance matrices in track fusion problems

Download

index.pdf

Date

2007

Author

Günay, Melih

Metadata

Show full item record

Item Usage Stats

243
views

138
downloads

Covariance Matrix in target tracking algorithms has a critical role at multi- sensor track fusion systems. This matrix reveals the uncertainty of state es- timates that are obtained from diferent sensors. So, many subproblems of track fusion usually utilize this matrix to get more accurate results. That is why this matrix should be interchanged between the nodes of the multi-sensor tracking system. This thesis mainly deals with analysis of approximations of the covariance matrix that can best represent this matrix in order to efectively transmit this matrix to the demanding site. Kullback-Leibler (KL) Distance is exploited to derive some of the representations for Gaussian case. Also com- parison of these representations is another objective of this work and this is based on the fusion performance of the representations and the performance is measured for a system of a 2-radar track fusion system.

Subject Keywords

Electrical Engineering., Electronics., Nuclear Engineering.

URI

http://etd.lib.metu.edu.tr/upload/12609026/index.pdf
https://hdl.handle.net/11511/17416

Collections

Graduate School of Natural and Applied Sciences, Thesis

Suggestions

OpenMETU
Core

Dim target detection in infrared imagery Çifçi, Barış; Atalay, Aydın; Department of Electrical and Electronics Engineering (2006) This thesis examines the performance of some dim target detection algorithms in low-SNR imaging scenarios. In the past research, there have been numerous attempts for detection and tracking barely visible targets for military surveillance applications with infrared sensors. In this work, two of these algorithms are analyzed via extensive simulations. In one of these approaches, dynamic programming is exploited to coherently integrate the visible energy of dim targets over possible relative directions, where...
Investigation of music algorithm based and wd-pca method based electromagnetic target classification techniques for their noise performances Ergin, Emre; Sayan, Gönül; Department of Electrical and Electronics Engineering (2009) Multiple Signal Classification (MUSIC) Algorithm based and Wigner Distribution-Principal Component Analysis (WD-PCA) based classification techniques are very recently suggested resonance region approaches for electromagnetic target classification. In this thesis, performances of these two techniques will be compared concerning their robustness for noise and their capacity to handle large number of candidate targets. In this context, classifier design simulations will be demonstrated for target libraries con...
Advanced readout and control electronics for mems gyroscopes Temiz, Yüksel; Akın, Tayfun; Department of Electrical and Electronics Engineering (2007) This thesis reports the development of advanced readout and control electronics for MEMS gyroscopes developed at METU. These gyroscope electronics are separated into three main groups: high sensitive interface circuits, drive mode amplitude controlled self oscillation loops, and sense mode phase sensitive amplitude demodulators. The proposed circuits are first implemented with discrete components, and then integrated on CMOS chips. A self oscillation loop enabling constant amplitude drive mode vibrations in...
Lifetime analysis for wireless sensor networks Öğünlü, Bilal; Bazlamaçcı, Cüneyt Fehmi; Department of Electrical and Electronics Engineering (2004) Sensor technologies are vital today in gathering information about certain environments and wireless sensor networks are getting more widespread use everyday. These networks are characterized by a number of sensor nodes deployed in the field for the observation of some phenomena. Due to the limited battery capacity in sensor nodes, energy efficiency is a major and challenging problem in such power-constrained networks. Some of the network design parameters have a direct impact on the network̕s lifetime. The...
Improvements to neural network based restoration in optical networks Türk, Fethi; Bilgen, Semih; Department of Electrical and Electronics Engineering (2008) Performance of neural network based restoration of optical networks is evaluated and a few possible improvements are proposed. Neural network based restoration is simulated with optical link capacities assigned by a new method. Two new improvement methods are developed to reduce the neural network size and the restoration time of severed optical connections. Cycle based restoration is suggested, which reduces the neural network structure by restoring the severed connections for each optical node, iterativel...

Citation Formats

M. Günay, “Representation of covariance matrices in track fusion problems,” M.S. - Master of Science, Middle East Technical University, 2007.