<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>27</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Ljudmil  Bojilov</style></author><author><style face="normal" font="default" size="100%">Pavlina Konstantinova</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A Comparison study of two approaches for determining ranked set of assignments for multitarget tracking</style></title></titles><dates><year><style  face="normal" font="default" size="100%">2017</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Jean Dezert</style></author><author><style face="normal" font="default" size="100%">Albena Tchamova</style></author><author><style face="normal" font="default" size="100%">Tzvetan Semerdjiev</style></author><author><style face="normal" font="default" size="100%">Pavlina Konstantinova</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Multitarget Tracking in Clutter based on Generalized Data Association: Performance Evaluation of Fusion Rules</style></title><secondary-title><style face="normal" font="default" size="100%">Advances and Applications of DSmT for Information Fusion</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2006</style></year></dates><publisher><style face="normal" font="default" size="100%">American Research Press, Rehoboth</style></publisher><language><style face="normal" font="default" size="100%">eng</style></language><section><style face="normal" font="default" size="100%">12</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Jean Dezert</style></author><author><style face="normal" font="default" size="100%">Albena Tchamova</style></author><author><style face="normal" font="default" size="100%">Florentin Smarandache</style></author><author><style face="normal" font="default" size="100%">Pavlina Konstantinova</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Target Type Tracking</style></title><secondary-title><style face="normal" font="default" size="100%">Fusion 2006 conference</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2006</style></year></dates><pub-location><style face="normal" font="default" size="100%">Firenze, Italy</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Jean Dezert</style></author><author><style face="normal" font="default" size="100%">Albena Tchamova</style></author><author><style face="normal" font="default" size="100%">Pavlina Konstantinova</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Target Type Tracking with Different Fusion Rules: A Comparative Analysis</style></title><secondary-title><style face="normal" font="default" size="100%">Advances and Applications of DSmT for Information Fusion</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2006</style></year></dates><publisher><style face="normal" font="default" size="100%">American Research Press, Rehoboth</style></publisher><language><style face="normal" font="default" size="100%">eng</style></language><section><style face="normal" font="default" size="100%">13</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>6</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Albena Tchamova</style></author><author><style face="normal" font="default" size="100%">Tzvetan Semerdjiev</style></author><author><style face="normal" font="default" size="100%">Pavlina Konstantinova</style></author><author><style face="normal" font="default" size="100%">Jean Dezert</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Generalized Data Association for Multitarget Tracking in Clutter</style></title><secondary-title><style face="normal" font="default" size="100%">Collected works, vol. 1</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2004</style></year></dates><publisher><style face="normal" font="default" size="100%">American Research Press, Rehoboth</style></publisher><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Pavlina Konstantinova</style></author><author><style face="normal" font="default" size="100%">Milen Nikolov</style></author><author><style face="normal" font="default" size="100%">Tzvetan Semerdjiev</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A Study of Clustering Applied to Multiple Target Tracking Algorithm</style></title><secondary-title><style face="normal" font="default" size="100%">International Conference on Computer Systems and Technologies - CompSysTech’2004</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2004</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Ljudmil  Bojilov</style></author><author><style face="normal" font="default" size="100%">Kiril Alexiev</style></author><author><style face="normal" font="default" size="100%">Pavlina Konstantinova</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">An Accelerated IMM-JPDA Algorithm for Tracking Multiple Maneuvering Targets in Clutter</style></title><secondary-title><style face="normal" font="default" size="100%">Information &amp; Security: An International Journal</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">assignment</style></keyword><keyword><style  face="normal" font="default" size="100%">cluttered environment</style></keyword><keyword><style  face="normal" font="default" size="100%">multiple maneuvering targets</style></keyword><keyword><style  face="normal" font="default" size="100%">Tracking</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2002</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2002</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">9</style></volume><pages><style face="normal" font="default" size="100%">141-153</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Theoretically, the Multiple Hypothesis Tracking (MHT) method is the most powerful approach for tracking multiple targets. The MHT method, however, leads to combinatorial explosion and computational overload. By using an algorithm for finding the K-best assignments, the MHT approach can be considerably optimized in terms of computational load. A much simpler alternative of the MHT approach is provided by the Joint Probabilistic Data Association (JPDA) algorithm in combination with the Interacting Multiple Models (IMM) approach. Even though it is much more simple, this approach can also be computationally overwhelming. To overcome this drawback, an algorithm due to Murty and optimized by Miller, Stone and Cox is embedded in the IMM-JPDA algorithm in order to determine a ranked set of K-best hypotheses (instead of all feasible hypotheses). The presented algorithm assures continuous maneuver detection and adequate estimation of maneuvering targets in heavy clutter. This results in a good overall target tracking performance with moderate computational and memory requirements. The article further presents corresponding simulation results.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Emanuil Djerassi</style></author><author><style face="normal" font="default" size="100%">Pavlina Konstantinova</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Object-Oriented Environment for Assessing Tracking Algorithms</style></title><secondary-title><style face="normal" font="default" size="100%">Information &amp; Security: An International Journal</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Monte-Carlo analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Object-oriented programming</style></keyword><keyword><style  face="normal" font="default" size="100%">sensor data processing</style></keyword><keyword><style  face="normal" font="default" size="100%">tracking algorithms</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2002</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2002</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">9</style></volume><pages><style face="normal" font="default" size="100%">93-106</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Designing, implementing, and assessing tracking algorithms is an essential and complex problem in numerous defense and security related applications. One way to alleviate this problem is to provide the designer with an environment, facilitating the creation of various test scenarios, to propose aids for implementing algorithms, and to evaluate their measures of performance. Such an environment is a complex software program, which could be simplified by using object-oriented design and programming. By unifying data and functions that operate on the data, the overall program organization can be improved considerably. In this article the authors propose a set of classes that can be divided into three groups, considering respectively the modeling part, the processing part and the organization of the statistical analysis for measuring performance.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Ljudmil  Bojilov</style></author><author><style face="normal" font="default" size="100%">Pavlina Konstantinova</style></author><author><style face="normal" font="default" size="100%">Kiril Alexiev</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A particular programme realization of JPDAF algorithm</style></title><secondary-title><style face="normal" font="default" size="100%">Comptes rendus de l'Academie bulgare des Sciences</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2002</style></year></dates><volume><style face="normal" font="default" size="100%">55</style></volume><pages><style face="normal" font="default" size="100%">37-44</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><issue><style face="normal" font="default" size="100%">9</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Pavlina Konstantinova</style></author><author><style face="normal" font="default" size="100%">Kiril Alexiev</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A Comparison of Two Hypothesis Generation Algorithms in JPDAF Multiple Target Tracking</style></title><secondary-title><style face="normal" font="default" size="100%">International Conference on Computer System and Technologies</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2001</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Emil Semerdjiev</style></author><author><style face="normal" font="default" size="100%">Kiril Alexiev</style></author><author><style face="normal" font="default" size="100%">Emanuil Djerassi</style></author><author><style face="normal" font="default" size="100%">Pavlina Konstantinova</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Multiple Hypothesis Tracking Using Hough Transform Track Detector</style></title><secondary-title><style face="normal" font="default" size="100%">Information &amp; Security: An International Journal</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Hough Transform</style></keyword><keyword><style  face="normal" font="default" size="100%">Multiple Hypothesis Tracking</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">1999</style></year><pub-dates><date><style  face="normal" font="default" size="100%">1999</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">2</style></volume><pages><style face="normal" font="default" size="100%">113-121</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">A modification of the standard Multiple Hypothesis Tracking (MHT) measurement oriented algorithm version is proposed and evaluated in the paper. A Hough Transform track detector is implemented in MHT to filter false alarms. The measurements belonging to already detected tracks are arranged in MHT tracks by another standard MHT algorithm used asynchronously. At the cost of delayed track detection this MHT2-HT algorithm shows remarkable good performance and noise resistance.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Emil Semerdjiev</style></author><author><style face="normal" font="default" size="100%">Albena Tchamova</style></author><author><style face="normal" font="default" size="100%">Pavlina Konstantinova</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Multiple Hypothesis Tracking Using Demster-Shafer's Attribute Class Estimation</style></title><secondary-title><style face="normal" font="default" size="100%">Comptes rendus de l'Academie Bulgare des Sciences</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">1997</style></year></dates><volume><style face="normal" font="default" size="100%">50</style></volume><pages><style face="normal" font="default" size="100%">53-56</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><issue><style face="normal" font="default" size="100%">7</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Pavlina Konstantinova</style></author><author><style face="normal" font="default" size="100%">Tzvetan Semerdjiev</style></author><author><style face="normal" font="default" size="100%">Albena Tchamova</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Performance Evaluation of Attribute Data Association Algorithm Using Parallel Processing</style></title><secondary-title><style face="normal" font="default" size="100%">10th Intern. Conf. on Systems for Automation of Engineering &amp; Research (SAER'96)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">1996</style></year></dates><pub-location><style face="normal" font="default" size="100%">Varna, Bulgaria</style></pub-location><pages><style face="normal" font="default" size="100%">99-103</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record></records></xml>