<?xml version="1.0" encoding="UTF-8"?><xml><records><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%">Ludmila Mihaylova</style></author><author><style face="normal" font="default" size="100%">X. Rong-Li</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">An Adaptive IMM Filter for Aircraft Tracking</style></title><secondary-title><style face="normal" font="default" size="100%">2nd Intern. Conf. on Multisource-Multisensor Information Fusion (Fusion’99)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">1999</style></year></dates><pub-location><style face="normal" font="default" size="100%">Sunnyvale, California</style></pub-location><pages><style face="normal" font="default" size="100%">770-777</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>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Ludmila Mihaylova</style></author><author><style face="normal" font="default" size="100%">Emil Semerdjiev</style></author><author><style face="normal" font="default" size="100%">X. Rong-Li</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Detection and Localization of Faults in System Dynamics by IMM Estimator</style></title><secondary-title><style face="normal" font="default" size="100%">2nd Intern. Conf. on Multisource-Multisensor Information Fusion (Fusion’ 99)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">1999</style></year></dates><pub-location><style face="normal" font="default" size="100%">Sunnyvale, California</style></pub-location><pages><style face="normal" font="default" size="100%">937-943</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%">Donka Angelova</style></author><author><style face="normal" font="default" size="100%">Emil Semerdjiev</style></author><author><style face="normal" font="default" size="100%">Ludmila Mihaylova</style></author><author><style face="normal" font="default" size="100%">X. Rong Li</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">An IMMPDAF Solution to Benchmark Problem for Tracking in Clutter and Stand-off Jammer</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%">hybrid system estimation</style></keyword><keyword><style  face="normal" font="default" size="100%">radar data processing</style></keyword><keyword><style  face="normal" font="default" size="100%">target 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%">55-68</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">An IMMPDA filtering algorithm is presented for radar management and tracking maneuvering targets in the presence of false alarms and Standoff Jammer. The performance of the designed algorithm is evaluated by Monte Carlo simulation. The results obtained over six benchmark test scenarios demonstrate that the tracking filter satisfy the performance restriction on  a maximum allowed track loss of 4 %, posed by the benchmark problem. The achieved average sampling interval is approximately 2.85 sec and the average power is about 8.24 W. The paper reports preliminary results of an ongoing study and further investigation is under way</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%">Ludmila Mihaylova</style></author><author><style face="normal" font="default" size="100%">Emil Semerdjiev</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">An Interacting Multiple Model Algorithm for Stochastic Systems Control</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%">adaptive control</style></keyword><keyword><style  face="normal" font="default" size="100%">Bayesian algorithms</style></keyword><keyword><style  face="normal" font="default" size="100%">multiple model estimation and control</style></keyword><keyword><style  face="normal" font="default" size="100%">parameter uncertainty</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%">102-112</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">During the last years the multiple-model approach has become very popular and widely applied for estimation and control of stochastic systems under different uncertainties - unknown model structure or parameters. In the engineering applications different multiple model algorithms for system control have been proposed. The greatest number of them are of Bayesian nature. Their common feature is the bank of estimators providing separate state estimates required for the overall control synthesis.  
In the paper an Interacting Multiple Model (IMM) algorithm for stochastic systems control in the presence of parametric model uncertainty is designed. It is based on the cost-effective IMM estimator. The overall system control is synthesized as a probabilistically weighted sum of the control processes from separate regulators working in parallel. These regulators are synthesised for each model from the uncertainty domain. The regulators are based on linear system, quadratic cost function and Gaussian noise assumptions. The overall control process is computed as a state feedback. The cost effective IMM filter is used for partial state estimates generation. The algorithm presented is compared to other MM Bayesian algorithm for control through Monte Carlo simulation experiments. The simulation results demonstrate that the IMM control algorithm provides better results in the presence of abrupt changes in the parameters than the MMAC algorithm. The performance of both algorithms is comparable in a stationary mode.</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%">Ludmila Mihaylova</style></author><author><style face="normal" font="default" size="100%">Tzvetan Semerdjiev</style></author><author><style face="normal" font="default" size="100%">Violeta Bogdanova</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Interacting Multiple Model Algorithms for Manoeuvring Ship Tracking Based On New Ship Models</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%">adaptive hybrid estimation</style></keyword><keyword><style  face="normal" font="default" size="100%">marine targets tracking</style></keyword><keyword><style  face="normal" font="default" size="100%">model identification</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%">122-137</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Tracking of manoeuvring targets is a problem of a great practical and theoretical interest. The real-world tracking applications meet a number of difficulties caused by the presence of different kinds of uncertainty due to the unknown or not precisely known system model and random processes’ statistics or because of their abrupt changes. These problems are especially complicated in the marine navigation practice, where the commonly used simple models of rectilinear or curvilinear target motions do not match to the highly non-linear dynamics of the manoeuvring ship motion. A solution of these problems is to derive more adequate descriptions of the real ship dynamics and to design adaptive estimation algorithms. In the paper a new ship model is derived after an analysis of the basic hydrodynamic models. This model is implemented in a new version of the Interacting Multiple Model (IMM) tracking algorithm - the most cost-effective multiple model algorithm for hybrid estimation. The proposed new IMM uses extended state vector and model to compensate the difference between the fixed control parameter of the currently used IMM model and its real value. The performed Monte Carlo simulations, show excellent model fit and estimation performance.</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%">Ludmila Mihaylova</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">IMM Algorithm for Manoevring Ship Tracking</style></title><secondary-title><style face="normal" font="default" size="100%">Intern. Conf. on Multisource-Multisensor Inf. Fusion - FUSION'98 </style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">1998</style></year></dates><pub-location><style face="normal" font="default" size="100%">Las Vegas, Nevada</style></pub-location><pages><style face="normal" font="default" size="100%">974-979.</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>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%">Tzvetan Semerdjiev</style></author><author><style face="normal" font="default" size="100%">Ludmila Mihaylova</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Maneuvering Ship Model Identification and IMM Tracking Algorithm Design </style></title><secondary-title><style face="normal" font="default" size="100%">First International Conference on Multisource-Multisensor Information Fusion’98</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">1998</style></year></dates><pub-location><style face="normal" font="default" size="100%">Las Vegas, Nevada</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record></records></xml>