<?xml version="1.0" encoding="UTF-8"?><xml><records><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%">Kiril Alexiev</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Spatio-Temporal Data Visualization and Analysis for Multi-Target Tracking</style></title><secondary-title><style face="normal" font="default" size="100%">Data Fusion for Situation Monitoring, Incident Detection, Alert and Response Management</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2005</style></year></dates><edition><style face="normal" font="default" size="100%">Том 198 от Elisa Shahbazian,Galina Rogova, Pierre Valin</style></edition><pages><style face="normal" font="default" size="100%">235-252</style></pages><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%">Kiril Alexiev</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A MATLAB Tool for Development and Testing of Track Initiation and Multiple Target 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%">analysis tool</style></keyword><keyword><style  face="normal" font="default" size="100%">automated design</style></keyword><keyword><style  face="normal" font="default" size="100%">radar simulation and modeling</style></keyword><keyword><style  face="normal" font="default" size="100%">synthesis</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%">166-174</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Computer simulation is a valuable tool for design, analysis, and testing of complex systems whose behavior cannot be easily evaluated by means of analysis. The simulation includes input data generation, modeling of the system under examination and performance evaluation with proper visualization. The most complex algorithms can be easily coded by means of Matlab. The language of Matlab can be learnt quickly and, after that, the engineers can fully exploit its power with high productivity. The Matlab compiler translates *.m files into C code for real time implementation purposes. This article describes architecture and simulation tools for analysis and design of radar data processing systems, outlines the techniques used to generate the input data, and presents simulation results to analyze and evaluate the performance of various algorithms. The presented tool can be useful to practicing radar engineers for analysis and design purposes.</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>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kiril Alexiev</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Implementation of Hough Transform as Track Detector</style></title><secondary-title><style face="normal" font="default" size="100%">International Conference on Multisource Multisensor Information Fusion </style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2000</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>10</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%">Lubomir Bojilov</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Multiple Sensor Data Association Algorithm Using Hough Transform for Track Initiation</style></title><secondary-title><style face="normal" font="default" size="100%">First International Conference on Multisource-Multisensor Information Fusion - FUSION'98 </style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">1998</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%">Emanuil Djerassi</style></author><author><style face="normal" font="default" size="100%">Violeta Bogdanova</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%">Performance Evaluation of a Multiple Hypothesis Tracking Algorithm Using Hough Transform</style></title><secondary-title><style face="normal" font="default" size="100%">Compte rendus de l'Academie Bulgare des Sciences </style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">1996</style></year></dates><volume><style face="normal" font="default" size="100%">49</style></volume><pages><style face="normal" font="default" size="100%">51-54</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><issue><style face="normal" font="default" size="100%">4</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%">Kiril Alexiev</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Flight object modeling in radar surveillance volume</style></title><secondary-title><style face="normal" font="default" size="100%">Systems for automation of engineering and research SAER'92</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">1992</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language></record></records></xml>