Дисертації з теми "Kalman filter based tracking loop"
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Schrempp, Mark. "Tracking loop design." Thesis, Manhattan, Kan. : Kansas State University, 2009. http://hdl.handle.net/2097/1363.
Повний текст джерелаChen, Hao. "Kalman Filter Aided Tracking Loop In GPS Signal Spoofing Detection." University of Cincinnati / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1418909647.
Повний текст джерелаLashley, Matthew Bevly David M. Hung John Y. "Kalman filter based tracking algorithms for software GPS receivers." Auburn, Ala., 2006. http://repo.lib.auburn.edu/2006%20Fall/Theses/LASHLEY_MATTHEW_34.pdf.
Повний текст джерелаWeigang, Zhao, Yao Tingyan, Wu Jinpei, and Zhang Qishan. "SOFT SEAMLESS SWITCHING IN DUAL-LOOP DSP-FLL FOR RAPID ACQUISITION AND TRACKING." International Foundation for Telemetering, 2004. http://hdl.handle.net/10150/605319.
Повний текст джерелаFLL’s are extensively used for fast carrier synchronization. A common approach to meet the wide acquisition range and sufficiently small tracking error requirements is to adopt the wide or narrow band FLL loop in the acquisition and tracking modes and direct switching the loop. The paper analyze the influence of direct switching on performance, including the narrow band loop convergence, transition time etc. and propose applying the Kalman filtering theory to realize the seamless switching (SS) with time-varying loop gains between the two different loop tracking state. The SS control gains for the high dynamic digital spread spectrum receiver is derived. Simulation results for the SS compared to the direct switching demonstrate the improved performance.
Kanduri, Srinivasa Rangarajan Mukhesh, and Vinay Kumar Reddy Medapati. "Evaluation of TDOA based Football Player’s Position Tracking Algorithm using Kalman Filter." Thesis, Blekinge Tekniska Högskola, Institutionen för tillämpad signalbehandling, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-16433.
Повний текст джерелаIsaac, Benson. "Inverse Kinematics and Extended Kalman Filter based Motion Tracking of Human Limb." University of Cincinnati / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1406809906.
Повний текст джерелаVadde, Susheel Reddy. "Improving Tissue Elasticity Imaging Using A KALMAN Filter-Based Non-Rigid Motion Tracking Algorithm." Youngstown State University / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=ysu1310141393.
Повний текст джерелаVelmurugan, Rajbabu. "Implementation Strategies for Particle Filter based Target Tracking." Diss., Georgia Institute of Technology, 2007. http://hdl.handle.net/1853/14611.
Повний текст джерелаAparicio, Conrado. "Implementation of a quaternion-based Kalman filter for human body motion tracking using MARG sensors." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2004. http://library.nps.navy.mil/uhtbin/hyperion/04Sep%5FAparicio.pdf.
Повний текст джерелаJanga, Satyanarayana Reddy. "A Fast and Robust Image-Based Method for tracking Robot-assisted Needle Placement in Real-time MR Images." Digital WPI, 2014. https://digitalcommons.wpi.edu/etd-theses/106.
Повний текст джерелаGreen, Mark P. (Mark Peter) 1958. "Extended Kalman filter for integrating tracking data from ground-based radar and airborne global positioning system." Thesis, Massachusetts Institute of Technology, 1998. http://hdl.handle.net/1721.1/49627.
Повний текст джерелаFan, Zheyu Jerry. "Kalman Filter Based Approach : Real-time Control-based Human Motion Prediction in Teleoperation." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-189210.
Повний текст джерелаDetta arbete fokuserar på att undersöka prestandan hos två Kalman Filter Algoritmer, nämligen Linear Kalman Filter och Extended Kalman Filter som används i realtids uppskattningar av kontrollbaserad mänsklig rörelse i teleoperationen. Dessa Kalman Filter Algoritmer har används i stor utsträckning forskningsområden i rörelsespårning och GPS-navigering. Emellertid är potentialen i uppskattning av mänsklig rörelse genom att utnyttja denna algoritm sällan nämnas. Genom att kombinera med det kända problemet – fördröjningsproblem i dagens teleoperation tjänster beslutar författaren att bygga en prototyp av en enkel teleoperation modell vilket är baserad på Kalman Filter algoritmen i syftet att eliminera icke-synkronisering mellan användarens inmatningssignaler och visuella information, där alla data överfördes via nätverket. I den första delen av avhandlingen appliceras både Kalman Filter Algoritmer på prototypen för att uppskatta rörelsen av robotarmen baserat på användarens rörelse som anbringas på en haptik enhet. Jämförelserna i prestandan bland de Kalman Filter Algoritmerna har också fokuserats. I den andra delen fokuserar avhandlingen på att optimera uppskattningar av rörelsen som baserat på resultaten av Kalman-filtrering med hjälp av en utjämningsalgoritm. Den sista delen av avhandlingen undersökes begräsning av prototypen, som till exempel hur mycket fördröjningar accepteras och hur snabbt den haptik enheten kan vara, för att kunna erhålla skäliga uppskattningar med acceptabel felfrekvens. Resultaten visar att den Extended Kalman Filter har bättre prestandan i rörelse uppskattningarna än den Linear Kalman Filter under experimenten. Det icke-synkroniseringsproblemet har förbättrats genom att tillämpa de Kalman Filter Algoritmerna på både statliga och värderingsmodeller när latensen är inställd på under 200 millisekunder. Den extra utjämningsalgoritmen ökar ytterligare noggrannheten. Denna algoritm löser också det skakande problem hos de visuella bilder på robotarmen som orsakas av den vågiga egenskapen hos Kalman Filter Algoritmen. Dessutom effektivt synkroniserar den optimeringsmetoden tidpunkten när robotarmen berör objekten i uppskattningarna. Den metod som används i denna forskning kan vara en god referens för framtida undersökningar i kontrollbaserad rörelse- spåning och uppskattning.
Khajo, Gabriel. "Region Proposal Based Object Detectors Integrated With an Extended Kalman Filter for a Robust Detect-Tracking Algorithm." Thesis, Karlstads universitet, Fakulteten för hälsa, natur- och teknikvetenskap (from 2013), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-72698.
Повний текст джерелаMiezal, Markus [Verfasser]. "Models, methods and error source investigation for real-time Kalman filter based inertial human body tracking / Markus Miezal." München : Verlag Dr. Hut, 2021. http://d-nb.info/1232847631/34.
Повний текст джерелаOh, Seung-Min. "Nonlinear Estimation for Vision-Based Air-to-Air Tracking." Diss., Georgia Institute of Technology, 2007. http://hdl.handle.net/1853/19882.
Повний текст джерелаWang, Weiqi. "Towards real-time tissue surface tracking with a surface-based extended kalman filter for robotic-assisted minimally invasive surgery." Thesis, University of British Columbia, 2014. http://hdl.handle.net/2429/46992.
Повний текст джерелаOksar, Yesim. "Target Tracking With Correlated Measurement Noise." Master's thesis, METU, 2007. http://etd.lib.metu.edu.tr/upload/12608198/index.pdf.
Повний текст джерелаZuo, Tianyu. "An Efficient Vision-Based Pedestrian Detection and Tracking System for ITS Applications." Thesis, Université d'Ottawa / University of Ottawa, 2014. http://hdl.handle.net/10393/31778.
Повний текст джерелаDel, Favero Simone. "Analysis and Development of Consensus-based Estimation Schemes." Doctoral thesis, Università degli studi di Padova, 2010. http://hdl.handle.net/11577/3427027.
Повний текст джерелаGli ultimi decenni sono stati segnati dallo straordinario sviluppo di Internet e dalla pervasiva diffusione della tecnologia wireless, consentendo ad un numero sempre maggiore di dispositivi di scambiare tra loro informazioni. Questo fatto, assieme alla crescente disponibilità, a prezzi modici, di nodi equipaggiati con un'ampia varietà di dispositivi di misura, rende tecnologicamente concretizzabile l'idea di sviluppare grandi piattaforme di sensing, incaricate di monitorare qualsivoglia grandezza fisica. Tuttavia, queste grandi reti di dispositivi estremamente semplici hanno stringenti vincoli sul consumo energetico e sulla banda di comunicazione, che rendono criticamente necessario lo sviluppo di tecniche efficienti per la stima e la data-fusion, così da evitare carichi computazionali e di comunicazione insostenibili ai colli di bottiglia della rete. Questa tesi si propone di contribuire proprio in questo settore, presentando alcuni algoritmi per la soluzione distribuita di specifici problemi di stima ed analizzando le prestazioni di algoritmi recentemente proposti. Strumento chiave nella decentralizzazione della stima è la teoria del consensus, che propone algoritmi in grado di portare l'intera rete a concordare su una specifica quantità. L'utilizzo di algoritmi di consensus come elemento base nella costruzione di algoritmi di stima ci consente di sfruttare la solida comprensione di questo problema, affinata dai molti risultati recentemente proposti in letteratura, e di sfruttare degli strumenti di analisi ben consolidati. Nella tesi, motivati dal problema della localizzazione e del tracking di un oggetto, proponiamo un algoritmo per la compensazione degli offset ed un algoritmo per la stima ai minimi quadrati dei parametri caratterizzanti il canale wireless. Inoltre presentiamo un nuovo risultato di algebra lineare, utile nell'analisi di algoritmi randomizzati. Questo risultato giocherà un ruolo centrale nell'analisi qui proposta di un algoritmo distribuito per la stima alla Kalman. Infine, consideriamo l'interessante caso di una rete di sensori incaricata di stimare quantità diverse ma tra loro correlate e proponiamo un algoritmo per l'inferenza di un semplice campo di Gauss-Markov.
Mailhot, Nathaniel. "Pupil Tracking and Control of a Laser Based Power System for a Vision Restoring Retinal Implant." Thesis, Université d'Ottawa / University of Ottawa, 2019. http://hdl.handle.net/10393/38709.
Повний текст джерелаHuttunen, S. (Sami). "Methods and systems for vision-based proactive applications." Doctoral thesis, Oulun yliopisto, 2011. http://urn.fi/urn:isbn:9789514296536.
Повний текст джерелаTiivistelmä Ihmisen ja eri laitteiden välisellä vuorovaikutuksella on keskeinen osa nyky-yhteiskunnassa. Teknisten laitteiden lisääntymisen myötä vuorovaikutustavat ovat myös muuttumassa. Tulevaisuuden järjestelmien tulisi olla proaktiivisia, jotta ne voisivat sopeutua ihmisten liikkeisiin ja toimintoihin ilman tietoista ohjausta. Ilmaisuvoimansa ansiosta visuaalisella tiedolla on keskeinen rooli tällaisessa epäsuorassa ihminen-tietokone –vuorovaikutuksessa. Tämän vuoksi on selvää, että kamerat yhdessä laskentaresurssien ja konenäkömenetelmien kanssa tarjoavat huomaamattoman tavan ihmisten toiminnan analysointiin. Lukuisista eduistaan huolimatta konenäön soveltaminen ei ole aina suoraviivaista. Yleensä jokainen sovellus asettaa erikoisvaatimuksia käytettäville menetelmille. Tästä syystä väitöskirjassa on päämääränä kehittää uusia kuvatietoon perustuvia menetelmiä ja järjestelmiä, joita voidaan hyödyntää proaktiivisissa sovelluksissa. Tässä väitöskirjassa esitellään kaksi proaktiivista sovellusta, jotka molemmat hyödyntävät tietokonenäköä. Ensimmäinen sovellus on etäopetusjärjestelmä, joka valitsee ja vaihtaa kuvalähteen automaattisesti. Järjestelmään esitellään myös ohjattavaan kameraan perustava laajennus, jonka avulla opettajaa voidaan seurata hänen liikkuessaan eri puolilla luokkahuonetta. Toinen proaktiivisen tekniikan sovellus on tarkoitettu mobiililaitteisiin. Kehitetty järjestelmä kykenee tunnistamaan maisemakuvat, jolloin kameran kuvaustila voidaan asettaa automaattisesti. Monissa sovelluksissa on tarpeen käyttää useampia kameroita. Tämän seurauksena eri puolille ympäristöä sijoitettavat älykkäät kamerat ovat olleet viime vuosina erityisen kiinnostuksen kohteena. Suurin osa kehityksestä on kuitenkin keskittynyt lähinnä eri konenäköalgoritmeihin tai yksittäisiin sovelluksiin. Sen sijaan panostukset yleisiin ja helposti laajennettaviin ratkaisuihin, jotka mahdollistavat erilaisten menetelmien, sensoreiden ja tiedonvälityskanavien käyttämisen, ovat olleet vähäisempiä. Tilanteen parantamiseksi väitöskirjassa esitellään hajautettujen sensoriverkkojen kehitykseen tarkoitettu avoin ja laajennettavissa oleva ohjelmistorunko. Menetelmien osalta tässä väitöskirjassa keskitytään useiden kohteiden seurantaan. Kehitetty seurantamenetelmä yhdistää saadut paikkamittaukset seurattaviin kohteisiin siten, että jokaiselle mittaukselle lasketaan todennäköisyys, jolla se kuuluu jokaiseen yksittäiseen seurattavaan kohteeseen. Seurantaongelman lisäksi työssä esitellään kaksi erilaista tapaa, joilla kohteiden paikka kuvassa voidaan määrittää. Esiteltyä kokonaisuutta voidaan hyödyntää proaktiivisissa sovelluksissa, jotka tarvitsevat usean kohteen paikkatiedon tai kohteiden kulkeman reitin
Khan, Wasiq. "A Novel Approach for Continuous Speech Tracking and Dynamic Time Warping. Adaptive Framing Based Continuous Speech Similarity Measure and Dynamic Time Warping using Kalman Filter and Dynamic State Model." Thesis, University of Bradford, 2014. http://hdl.handle.net/10454/14802.
Повний текст джерелаEng, Tseng Lau. "Quantification of carbon emissions and savings in smart grids." Thesis, Brunel University, 2016. http://bura.brunel.ac.uk/handle/2438/12569.
Повний текст джерелаWijk, Olle. "Triangulation Based Fusion of Sonar Data with Application in Mobile Robot Mapping and Localization." Doctoral thesis, Stockholm : Tekniska högsk, 2001. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-3124.
Повний текст джерелаChen, Shih-Fan, and 陳時帆. "GPS Receiver Tracking Loop Designs Based on the ANFIS-aided Extended Kalman Filter." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/46473562571796711442.
Повний текст джерела國立臺灣海洋大學
導航與通訊系
93
Abstract The process of conventional code synchronization uses Delay-Locked Loop(DLL) structure most frequently. The conventional DLL loop uses a discriminator function constructed with a specific combination of its early, prompt, and late correlator to detect code tracking error. Multipath is one of the dominant error sources in GPS positioning. It is well known that conventional DLL tracking loop in GPS receiver would suffer from performance degradation due to multipath. When being serious, GPS receiver tracking loop lose lock that might caused by multipath. Extended Kalman Filter(EKF) can optimally combine multiple correlator branches to brtter estimate code tracking error as well as the other signal paratmeters, and to estimate the multipath components for mitigating the multipath problem. In this paper, an EKF based DLL tracking loop to GPS receiver. The I and Q correlator accumulator outputs are used as measurements for the EKF estimation. The EKF extracts and estimates parameters of the direct satellite signal component from the multipath corrupted signal for receiver tracking loop lose lock problem. Then , to apply Adaptive Network-Based Fuzzy Inference System(ANFIS) aid the EKF for reduce the tracking error. The purpose lies in making tracking error of signal is reduced, and verify the feasibility of this method by imitating the way. Keywords:1.GPS 2.Receiver Tracking Loop 3.Kalman Filter 4.ANFIS 5.Error Compensation
Lin, Yi-Cheng, and 林易澂. "Design and Analysis of Extended Kalman Filter Based GPS Tracking Loops." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/53612771928132359001.
Повний текст джерела國立臺灣大學
電機工程學研究所
99
Global Positioning System (GPS) is the most widely used Global Navigation Satellite System (GNSS) nowadays. Advantages such as open system, easy to use, and fast and accurate positioning have made it being applied to engineering surveying, vehicular navigation, personal navigation devices, and many other products and systems. In the mid-90s, the U.S. Federal Communication Committee (FCC) demanded the Emergency-911 (E-911) capability on all new generation mobile phones, which requires a return of user position even indoor. This has opened the research of indoor GPS. The main challenge is to process the weak satellite signals degraded by the attenuation due to buildings. In this thesis, tracking loops for weak GPS signals are investigated, which include the conventional tracking loop and the extended Kalman filter (EKF) based tracking loop. Simulation results show that for normal and weak GPS signals, the EKF-based tracking loop has smaller and identical mean squared code phase tracking error than the conventional tracking loop, and it can handle signal dynamics better too. However, the conventional tracking loop requires less accurate initial carrier frequency estimation than the EKF-based tracking loop. In addition, the arithmetic complexity of the two tracking loops are also analyzed and compared in this thesis, to provide a basic prediction of implementation costs.
Kuang, Shih-ku, and 廣士谷. "Kalman-Filter Based Player Tracking for Broadcast Tennis Video." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/07698681757629063394.
Повний текст джерела義守大學
資訊工程學系碩士班
97
For tennis video analysis, the technology of player detection and tracking is a very important issue. We can obtain the important features such as the location of the court, and the position, the trajectory and the velocity of players, etc. By these features, the semantics of tennis video can be further extracted. The necessary processing is to separate the foreground (the players) and background (the court), then the algorithm of player detection and tracking can be developed accordingly. Generally, the players in lower court can be detected easily. Because the camera is close to the players, therefore, in the court view, many features of players can be easily detected. However, to detect the players in upper court is very difficult due to the longer camera distance. Also, there exist many noises in the upper court, such as audience, court wall, line judges, ball boys, channel marks and scoreboard, those which make the detection more difficult. In this thesis, we developed an accurate court border method to reduce the noise interference, and then proposed an adaptive color extraction to detect the player. For player tracking, we developed a Kalman Filter based tracking algorithm to address the difficulty of player detection in upper court. The same idea can be also applied to double players tracking with a small modification. Experimential results show the new method can successfully apply to various tennis video.
Wang, Ting-Wei, and 汪廷瑋. "Dynamic Object Tracking based on CamShift and Kalman Filter." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/60735071047895855691.
Повний текст джерела中原大學
電機工程研究所
104
In the thesis project of object tracking, we propose the thesis combining the Cam Shift algorithm with Kalman filter which can provide the position of the target more accurately. The tracking algorithm of Cam Shift can only be used in simple background with few colors. By combining the Kalman filter, we can reduce the interference of the background color and make the tracking more accurate. In this thesis, we follow these steps: First, by converting our target image into the H.S.V. color space, we can get desired color information and adjust the contrast of the hue, saturation and brightness. Then we need an initial point to start our tracking process. The traditional Mean Shift theorem does not allow users to change its window size and may lose its target, so that we calculate the search window size and the position of the mass center based on the Cam Shift algorithm. The process is continued until the desired accuracy is met. Finally, due to the instability of the complex background, we add the Kalman filter to lower the noise and interference during the experiment. After the process, we can achieve higher accuracy. The experiments show that the Cam Shift algorithm with the Kalman filter can reduce the noise and instability much more effectively than using only the former. In this thesis, the contributions of the research are as follows: 1.Kalman filter improves and strengthens the stability of the Cam Shift algorithm execution in complex background. 2.It is difficult to detect the object with various colors using in Cam Shift algorithm. Combining it with the Kalman filter improves the object detection capability and make the result more precise. 3.The object tracking experiment helped us expand the measurement range from single color still object to dynamic background processing.
Chen, Chien-Chung, and 陳建仲. "The Vector Tracking Loop Design of GPS Receiver Using the Unscented Kalman Filter." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/58630400968047624563.
Повний текст джерела國立臺灣海洋大學
通訊與導航工程系
98
The tracking loops are used by traditional receivers to track the signals broadcast by the GPS satellites. This thesis applies the concept of vector tracking loop to GPS signal tracking design. The conventional vector tracking loop is based on the discriminators of DLL and FLL. For obtaining an improved tracking performance in the GPS receiver, several researchers have investigated the vector tracking loop, such as the vector delay lock loop (VDLL) and the vector frequency lock loop (VFLL). All the satellite signals are tracked and processed by a Kalman filter. The VDLL and VFLL combine the tracking of the different satellite PRN and carrier signals into a single algorithm. This algorithm can operate successfully when the independent parallel tracking loop fails. Furthermore, the VDLL can be implemented as part of an ultra-tightly coupled or a deeply integrated GPS receiver so that if the inertial system degrades or fails, the receiver has the interference benefits of VDLL in all of the tracking channels. Simulation results show that the tracking performance of vector tracking loop based on the local filter demonstrates noticeably improved high dynamic resistance capability than that based on the discriminator. Furthermore, use of the Unscented Kalman filter(UKF) as the local filter outperform that of Extended Kalman filter(EKF).
Carvalho, Guilherme de Sousa. "Kalman Filter-based Object Tracking Techniques for Indoor Robotic Applications." Master's thesis, 2021. http://hdl.handle.net/10316/98163.
Повний текст джерелаThe improvement of social robots have significantly increased, having in view an intelligent mobile robot system, that must be able to perform basic tasks, without compromising the human environment. Therefore, perception module has to be robust enough in object detection and tracking. Thus, the proposal of this dissertation, aims to integrate a multi-object tracking method in a mobile robotics context, mainly focusing on efficiency and performance, using the YOLOv3 object detector to acquire objects location in the image. This dissertation presents a study and exploitation of the SORT and the Deep-SORT Multi-Object Tracking by Detection methods. Aiming to increase robustness of assigning measurements to existing tracks, are introduced different conjugation of similarity metrics, regarding the data association module. Furthermore, to avoid the association between tracks and measurements of different classes, an object class based constraint is applied. These proposed data association techniques, were incorporated in the SORT and the Deep-SORT methods. The SORT, the Deep-SORT, and proposed data association techniques, were evaluated on the MOT17 training set and on the ISR Tracking Dataset (dataset labeled in this study). Moreover, an experiment for evaluating the performance of each method on a lower frame rate condition was performed, showing a decrease of performance. Nevertheless, experimental results attained without using object detector, shown an improvement of performance, when formulating the association problem with different similarity metrics. Throughout the development of this study, an indoor multi-class tracking dataset was labeled, providing useful conditions to validate the proposed framework. Therefore, a general evaluation of the SORT, the Deep-SORT and proposed data association techniques, using the YOLOv3 object detector, was performed in the referred labeled multi-class dataset.
A melhoria dos robôs sociais tem aumentado significativamente, tendo em vista um sistema robótico móvel "inteligente", que deve ser capaz de executar tarefas básicas, sem comprometer o ambiente humano. Portanto, o módulo de perceção tem de ser suficientemente robustos na deteção e rastreamento de objetos (rastreamento equivale à tradução portuguesa de "tracking"). Portanto, a proposta desta dissertação, pretende integrar um método de rastreamento de múltiplos objetos, num contexto de robótica móvel, focando-se em questões de eficiência e desempenho computacional, utilizando o detetor de objetos YOLOv3 para adquirir a localização de objetos na imagem.Esta dissertação apresenta um estudo e exploração dos métodos de rastreamento por deteção, o SORT e o Deep-SORT. Com o objetivo de reforçar a robustez da atribuição de objetos medidos a objetos rastreados, são introduzidas conjugações diferentes de métricas de similaridade, no módulo de associação de dados. Adicionalmente, para evitar a associação de objetos medidos com objetos rastreados de diferentes classes, é aplicada uma restrição baseada em classes de objetos. Estas técnicas propostas de associação de dados, foram incorporadas nos métodos SORT e Deep-SORT.O SORT, o Deep-SORT, e as técnicas de associação de dados propostas, foram avaliados nos dados de treino do MOT17 e no ISR Tracking Dataset (conjunto de dados etiquetado neste estudo). Foram realizados testes ao desempenho dos métodos em condições de taxa reduzida de imagens, evidenciando uma diminuição do desempenho. Contudo, os resultados experimentais obtidos sem utilizar o detetor de objetos, mostram uma melhoria do desempenho, ao formular o problema de associação com métricas de semelhança diferentes. Ao longo do desenvolvimento deste estudo, um conjunto de dados de ambientes multi-classe e de interiores, foi etiquetado com dados de rastreio, fornecendo condições úteis para validar a estrutura proposta. Consequentemente foi realizada uma avaliação geral dos métodos SORT, Deep-SORT e técnicas de associação propostas, utilizando o detetor de objetos YOLOv3, no referido conjunto de dados de rastreio multi-classe etiquetado.
FCT
Universidade de Coimbra - MATIS-CENTRO-01-0145-FEDER-000014, Portugal
WANG, RUI-HAO, and 王瑞皓. "Maneuvering Target Tracking using Unscented Kalman Filter based Interacting Multiple Model." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/j58ccd.
Повний текст джерела國立雲林科技大學
電機工程系
106
In this paper, we use an unscented Kalman filter for nonlinear motions in an interacting multiple model algorithm to track maneuvering target. The unsented transform (UT) is a method for calculating the statistics of a random variable which undergoes a nonlinear transformation. Consider propagating a random variable through a nonlinear function, and assume that the nonlinear function has mean and covariance. To calculate the statistics of the nonlinear function, we form a matrix of sampling points with corresponding weights. These sampling points are propagated through the nonlinear function and the mean and covariance are approximated using a weighted sample mean and covariance of the posterior sampling points. Through combining the new mean and covarianc of these new sampling points, the state estimation of the nonlinear system can be obtained to achieve accurate nonlinear maneuvering target tracking. When the measured value of the estimator becomes inaccurate due to the influence of high Gaussian distribution noise, the unscented Kalman filter based interacting multiple model (IMM-UKF) is less affected by noise interference than the Kalman filter based interacting multiple model (IMM-KF). Although IMM-UKF is not comparable to the anti-interference ability of the unscented particle pilter based interacting multiple model (IMM-UPF) for Gaussian noise, IMM-UKF owns streamlined computing architecture and computing process. The completion time of the IMM-UKF is much shorter than that of the IMM-UPF which increases the simulation time due to the number of particles. IMM-UKF is more suitable for applications that do not have sufficient time. According to the simulation results of this paper, the estimated time which spent on the IMM-UKF is abou 35 times faster than that of the IMM-UPF.
Chang, Shih Chi, and 張世其. "3-D Wideband Signal Tracking based on Predictive Bearing Algorithm with Kalman Filter." Thesis, 2000. http://ndltd.ncl.edu.tw/handle/83182025033796442217.
Повний текст джерела國立海洋大學
電機工程學系
88
For a long time, Taiwan was located in a frequently earthquakes area. Besides this, it''s also an important pivot not only to defend the safety of Asia-Pacific but also to keep the peace of international merchant vessels and the Strait of Taiwan. It''s of great urgency to track the sources bearing using the methods of such as seismology, sonar and radar.Therefore, this thesis mainly uses passive uniform sensor array to track the multiple sources localization in 3-D space, characterized by range, elevation and azimuth. In the underwater multipaths environment, the signal will encounter the coherent phenomenon. In addition, consider the wideband signal as the objective of the system processing for the purpose of high speed transmission. First, data association and high accuracy are the well known properties of narrowband signal Predictive Angle Tracking(PAT) Algorithm based on Kalman Filter. In the mean time, Spatial Smoothing method served as the prepositive processing can overcome coherent signal and using the limitary condition of minimum length to avoid bearing disjudgement caused by abnormally lager angular innovations when the taregts are at crossing point or near by. On the economic consideration, we take the model of Uniform Linear Array(ULA) to estimate accurately the position of the sources in 3-D space and generalize the concept of narrowband PAT algorithm to the conventional Coherent Signal Subspace(CSS) algorithm which is modified as adaptive wideband sources angle tracking algorithm. Finally, we can verify the feasibility and the performance of 3-D space bearing tracking of adaptive wideband sources by using computer simulation.
CHUNG, CHI-CHIANG, and 鍾志強. "Geometric Unknown Turn Rate Estimation for Maneuvering Target Tracking Based on Kalman Filter." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/z3g384.
Повний текст джерела國立雲林科技大學
電機工程系
107
This paper presents a simple and effective unknown turn rate estimation method formaneuvering target tracking. The inner product method is first used to find out the angle between the velocity vectors of two consecutive time points. This two velocity vectors does not need to be constant speed. The geometric proof shows that this angle is therotation angle of the target between two consecutive time points,so then the unknown turn rate of the target can be calculated directly through it. Besides, whether the heading direction is left or right can be simply figured out by the twovelocityvectors.A simple Kalman filter (KF) based simulation model is built to demonstrate the robustness of the proposed unknown turn rate estimation method.Simulation results are compared toresult of Multi-modelEstimator (IMM) and the Kalman Filter coordinated turn (CT) model with prior known turn rate to show the effectiveness of the proposed method. We tried to find out the limitation of best conditions and the worst cases by changing the measurement noise and different turn rates, then the 100 times Monte Carlo results of root-mean-square errors(RMSE) of each parameter at every time point is showed.Also, the measurement value is one of the check standards.We can see how much the difference magnitude is during the simulation, and we revised the step of correction by adjustment of the weights of the prediction values and measurement values. After numerous examinations, we finally obtain a ranged scale of which it can present the best result of target tracking. The process data is recorded and showed as a figure of trend. Again, the robustness is viewed by how much the method improved, the gap between revised results and measurement values is calculated as a percentage to show clearly how the tracking estimation can work under unknown turn rates situations.
Wong, Sio-Sun, and 黃少旋. "Multi-target Visual Tracking Based on Segmented Histograms and Kalman Filter with Occlusion Handling." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/72769446842083558704.
Повний текст джерела國立臺灣大學
電機工程學研究所
98
A multi-target visual tracking approach, which consists of segmented color histograms, position estimation by Kalman filter and occlusion handling, is proposed in this thesis. The moving object regions are extracted by using Su’s Two-Staged Background Subtraction approach. Connected components are located and those of small area are discarded. Color histograms are used as descriptors of an object’s appearance due to their intrinsic benefits of being relatively scale-invariant and posture-invariant. In order to resolve the problem of losing spatial information due to histogram, an object is segmented into the upper and lower parts. Thus, the objects’ appearances are described by six histograms, namely, R, G, B histograms corresponding to the abovementioned two parts. The appearance model is then updated through Exponentially Weighted Moving Average across time. Furthermore, Kalman filter is used for position estimation for each object. We combined the appearance model and position condition to implement the tracking approach. In view of the challenging occlusion problem, a novel approach consists of Merge, Split, Obstructed and Reappeared is proposed. Historical information is utilized such that severe and even full occlusions can be handled. By and large, this approach can handle long, short, full, partial occlusions efficiently for both inter-object occlusion and occlusion by obstructors. Various experiments verify the robustness of our approach.
Chen, Chun-hua, and 陳俊樺. "Smart Surveillance System Based on High Level Features and Co-tracking by Kalman Filter." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/51900462733041076436.
Повний текст джерела國立中央大學
電機工程研究所
98
Tracking multiple targets in complex situation is challenging. The difficulties are tackled multiple targets with occlusions, especially when multiple involved targets are grouped, moving together in appearance ,and target is static. These problems are still focused in recent years. In this paper, we present a multiple targets tracking system for the management of occlusion problem. The proposed algorithm introduces a geometric shape co-tracking strategy. It decomposes targets into geometric shapes located on body and head parts based on reasonable target geometry consideration. Features selected from the decomposed geometric shapes then can be used to track targets through intersections such as occlusion. Projection histogram and ellipsoid shape model are adopted to manage decomposed geometric shapes corresponding to each target. Tracking is done through Kalman filtering process with high efficient and low complexity issue. The problem of sleeping object is handled by mean shift with no foreground needed. Experimental results show that the occlusion of grouped targets can be tracked successfully on recent challenging benchmark sequences. The proposed method is also implemented in DM642. The input video is from a camera transfer to DM642, then the input video has been through tracking process and output the video in LCD. To verify the system, a realistic video has been shown also.
Chen, Yan-Chu, and 陳彥竹. "Tracking Loop Design Using the Two-Stage Extended Kalman Filter for the Ultra-Tightly Coupled GPS/INS Navigation System." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/48800488796746941848.
Повний текст джерела國立臺灣海洋大學
通訊與導航工程學系
100
In this paper, the two-stage Kalman filter (TKF) for the tracking loop design of the GPS receiver for the ultra-tightly coupled (UTC) GPS/INS integration is carried out. The primary advantage of the UTC configuration is a significant reduction of the tracking loops bandwidth, as the Doppler signal derived from INS aids the tracking loop to remove the dynamics from the GPS signals. The UTC structure reveals many benefits, e.g., disturbance and multipath rejection capability, improved tracking capability for dynamic scenarios and weak signals, and reduction of acquisition time. The unknown random biases degrade the tracking performance of the Kalman filter estimation. Multipath effect, ionospheric delay and tropospheric delay are the main contributing sources of bias errors in GPS position determination. In many practical situations, there are unknown random biases in the system model, essentially caused by the multipath, ionospheric delay and tropospheric delay. The GPS tracking loops may lose lock due to the signals being weak, subjected to excessive dynamics or completely blocked. Traditional GPS tracking loop can be replaced by the vector tracking loop (VTC) for solving some of the problems. In high dynamic situations, the Doppler frequency changes faster with time, and it is therefore the carrier tracking loop of GPS receiver requires a wide bandwidth to track a carrier signal in high dynamic situations. As a specific configuration of the VTC, The ultra-tightly coupled (UTC) GPS/INS integrated navigation integrates the signals from the tracking loops of the GPS receiver with the position and velocity obtained from the INS. To treat the biases of the measurement and system models, the TKF is employed to estimate the signal parameters in the GPS receiver’s signal tracking loop. The proposed method demonstrates the superior capability on improvement of the tracking performance as an alternative estimator for dealing with the low quality signal and high dynamic environments for the tracking loop design of the UTC integration system.
Shen, Yu-Ping, and 沈予平. "Kalman Filter Based Visual Soccer Ball Tracking and Localization for Teen-size Biped Humanoid Robots." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/46783992746288328064.
Повний текст джерела國立臺灣科技大學
電機工程系
103
This thesis proposes a Kalman filter (KF) based visual soccer ball tracking and localization approach for an autonomous teen-size biped humanoid robot. This approach is capable of dealing with the visual tracking function in the humanoid league of RoboCup 2015. The competition field was covered by a piece of green carpet painted with white lines in former RoboCup humanoid leagues. Moreover, two identical yellow soccer goals and an orange color ball were used. Therefore, color-based ball recognition is practically used in formers competitions because of uses of distinct colors of ball, goal and field lines. Nevertheless, RoboCup 2015 announced a significant alteration in the specification of ball and goal colors. The major colors of the ball and two goals have been altered as a white color which is the same as the field line. It would be a great challenge to the color recognition when compared to former events, and the approaches with only applying color attribute thresholds. To overcome the aforementioned challenge, this work initially filters out the green carpet color with a linear regressive color space model to precisely retrieve all foreground objects such as robots, ball, goals and filed lines. Subsequently, the soccer ball is identified from the retrieved foreground objects. Especially, a KF is used to predict the ball moving trajectory. The predicted ball moving trajectory is further used to identify the ball position of the next image sampling time. According to the predicted ball position, a dynamic region of interest (ROI) can be generated. Its adjustable ROI dimension is formed with respect to the predicted ball image size with multiplying a tolerance factor which depends on the tracking error range. The dynamic ROI is beneficial to significantly reduce the interference of other objects in the field as well as to improve the computational efforts. Furthermore, a floor localization approach is used to transform the pixel coordinate system to the floor coordinate system. Finally, all proposed approaches have been realized and evaluated in this paper. When compared to the system without employing KF; the computational time of ball tracking is reduced 49.03%. The proposed algorithm has keep applied to our humanoid teen size robot, HuroEvolution TN, and it participated in the soccer game of RoboCup 2015 to practically evaluate the performance. As a consequence, the HuroEvolution TN awarded the second place. The results also verified the feasibility of the proposed approach.
Bondugula, Srikant. "OPTIMAL CONTROL OF PROJECTS BASED ON KALMAN FILTER APPROACH FOR TRACKING & FORECASTING THE PROJECT PERFORMANCE." 2009. http://hdl.handle.net/1969.1/ETD-TAMU-2009-05-263.
Повний текст джерелаLin, Zih-Siang, and 林梓翔. "Extended Kalman Filter Based Fuzzy Decentralized Sliding-Mode Trajectory Tracking Control of Quadrotor Unmanned Aerial Vehicles." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/8y4mua.
Повний текст джерела國立臺灣科技大學
電機工程系
104
Due to advantages and disadvantages of inertia navigation system (INS) and global positioning system (GPS), it is not suitable for the only use of GPS or INS for the measured velocity and position of outdoor QUAV. Furthermore, the computation of the rotation described by Euler angle is inefficient; its description sometimes possesses the singularity problem. Hence, it is not suitable for the embedded single board computer to calculate the corresponding signals using the Euler angle based rotation description. In this thesis, the nonlinear mathematical model of sensors including GPS and INS is first established. Its linearized model around the GPS signal is constructed for the discrete version of extended Kalman filter (EKF). The estimated position and velocity from EKF are employed to correct the position and velocity of INS such that the controller design is more effective. The compared performances between GPS and INS, and GPS-aided INS confirm the effectiveness of the estimated signal through GPS-aided INS. Subsequently, the EKCF-based fuzzy decentralized path tracking control (FDPTC) is applied for the path tracking of an outdoor QUAV. The proposed control does not need the mathematical dynamic model of QUAV, it only needs its input/output data to construct the fuzzy rule table. After that, three factors and the coefficients of sliding surface for each subsystem are tuned to obtain the satisfactory control performance. Finally, the compared experiments of circular path confirm the effectiveness and robustness of the proposed method.
Chellal, Majd. "Experimental evaluation of Kalman filter based MPPT in grid-connected PV system." Master's thesis, 2022. http://hdl.handle.net/10198/25144.
Повний текст джерелаPhotovoltaic (PV) energy is becoming an important alternative energy source, since it is abundant in nature, non-polluting and requires low maintenance. However, it suffers from low energy conversion efficiency, which can be even lower if the photovoltaic generator does not operate around a so-called Maximum Power Point (MPP). Tracking this point, which changes its location depending on weather conditions, is a very important step in the design of a photovoltaic system. Several techniques have been investigated in the literature in the MPP context. However, some techniques such as the Kalman filter are steel unknown with a lack of information in real test conditions, since their evaluation is limited only in simulation and literature review. This work presents an experimental evaluation of the Kalman filter based on a comparison with two well-known maximum power point tracking (MPPT) algorithms, which are the Perturbation and observation (among the simplest techniques) and the Particle Swarm Optimization (among the most complex techniques). The experimental tests were carried out under real atmospheric conditions, using Matlab/Simulink and the 1103 dSPACE real-time controller board. The results show that the Kalman filter has a higher aptitude to operate closer to the MPP, with a low oscillation in steady-state compared to the other MPPT evaluated in this work. However, the technique’s flaw lies in the shadow situation where it can not differentiate between the local and global optimums, unlike the particle swarm optimization.
A energia fotovoltaica (PV) está a tornar-se uma importante fonte de energia alternativa, uma vez que é abundante na natureza, não poluente, e requer pouca manutenção. No entanto, sofre de uma baixa eficiência de conversão energética, que pode ser ainda mais baixa se o gerador PV não operar em torno do chamado Ponto de Potência Máxima (MPP). O rastreio deste ponto, que muda a sua localização dependendo das condições meteorológicas, é um passo muito importante na concepção de um sistema PV. Várias técnicas têm sido investigadas na literatura no contexto do MPP. No entanto, o desempenho de algumas técnicas, como o filtro Kalman, em condições reais de teste, ainda desconhecido, ou existe pouca informação, uma vez que a sua avaliação é limitada apenas na simulação e revisão da literatura. Este trabalho apresenta uma avaliação experimental do filtro de Kalman com base numa comparação com dois seguidores de ponto de potência máxima (MPPT) bem conhecidos, que são a Perturbação e observação e a Optimização do Enxame de Partículas. Os testes experimentais foram realizados em condições atmosféricas reais, utilizando o Matlab/Simulink e a carta de controlo em tempo real dSPACE. Os resultados mostram que o filtro de Kalman tem uma maior aptidão para operar mais perto do MPP, com uma baixa oscilação em regime permenente, comparativemente com os outros algoritmos MPPT avaliados neste trabalho. No entanto, a desvantagem ocorre aquando da ocorãncia de sombra, onde a técnica não consegue diferenciar entre os óptimos locais e global, ao contrário da optimização do enxame de partículas. Palavras-chave: Fotovoltaico (PV), Seguimento do Ponto de Potência Máxima (MPPT), Perturbação e Observação (PO), Optimização de enxame de partículas (PSO), Filtro de Kalman (KF), Sistema PV ligado à Rede, dSPACE 1103.
Chen, Yu-Min, and 陳育民. "Tracking and Attitude of Objects by Quaternion Based on Kalman Filter to Build an Attitude and Heading Reference System." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/89738916870349823382.
Повний текст джерела中原大學
電機工程研究所
105
In this thesis, we propose a scheme of tracking and attitude of objects by quaternion based on Kalman filter to build an attitude and heading reference system. At first the attitude of the object is calculated by the quaternion and the rotation matrix. To achieve the overall stability of the system, through the estimation to perform attitude and tracking applications. The thesis presents the detailed analysis of position tracking based on Inertial measurement unit. The Sparkfun Inertial measurement unit module contains 3-axis gyroscope, 3-axis accelerometer and 3-axis magnetometer. In the second part of our proposal, in order to overcome the low precision, easy divergence and other shortcomings, a Kalman filter algorithm based on quaternion is employed. The establishment of the state equation requires dynamic error and a gyroscope motion, attitude as a state variable. The measurement scheme is built to take the quaternion of attitude matrix among accelerometers, magnetometers and gyroscopes. Third, in order to measurement the object movement, an Attitude and Heading Reference System with Inertial measurement unit is considered to accurately estimate the attitude. Finally, we use the Bluetooth or XBee communication module to receive real-time attitudinal discrimination and trajectory tracking. The results of tests indicate that the accumulated errors are eliminated in static state and the errors in dynamic state are compensated. In this thesis, the contributions of our research are as follows: 1. Security:We present a wearable sensor system for human motion monitoring in recovery for infants at risk of Sleeping position and climbing. 2. Simplification:It mounted the inertial measurement unit on the human body for estimating trajectory tracking and attitude measuring. 3. Characterization:The quaternion based Kalman filter improves and strengthens the stability of the algorithm execution in wearable devices monitoring inertial device for measuring capability. 4. Trending: To fit the requirement of the increased safety knowledge level of people, we propose an algorithm to combine with a wearable device, an appear for sensor technologies and monitoring devices.
Ko, Tien-Wen, and 柯天文. "Real-Time Face Detection and Tracking Based on Kalman Filter and Color Information on Mobile Devices for Criminal Detection." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/64s7cx.
Повний текст джерелаAu, Anthea Wain Sy. "RSS-based WLAN Indoor Positioning and Tracking System Using Compressive Sensing and Its Implementation on Mobile Devices." Thesis, 2010. http://hdl.handle.net/1807/25413.
Повний текст джерелаZhou, Y., Qichun Zhang, H. Wang, P. Zhou, and T. Chai. "EKF-Based Enhanced Performance Controller Design for Nonlinear Stochastic Systems." 2017. http://hdl.handle.net/10454/17347.
Повний текст джерелаIn this paper, a novel control algorithm is presented to enhance the performance of the tracking property for a class of nonlinear and dynamic stochastic systems subjected to non-Gaussian noises. Although the existing standard PI controller can be used to obtain the basic tracking of the systems, the desired tracking performance of the stochastic systems is difficult to achieve due to the random noises. To improve the tracking performance, an enhanced performance loop is constructed using the EKF-based state estimates without changing the existing closed loop with a PI controller. Meanwhile, the gain of the enhanced performance loop can be obtained based upon the entropy optimization of the tracking error. In addition, the stability of the closed loop system is analyzed in the mean-square sense. The simulation results are given to illustrate the effectiveness of the proposed control algorithm.
This work was supported in part by the PNNL Control of Complex Systems Initiative and in part by the National Natural Science Foundation of China under Grants 61621004,61573022 and 61333007.
Wang, KeSheng. "Approaches to the improvement of order tracking techniques for vibration based diagnostics in rotating machines." Thesis, 2011. http://hdl.handle.net/2263/28747.
Повний текст джерелаThesis (PhD)--University of Pretoria, 2011.
Mechanical and Aeronautical Engineering
unrestricted
(8800964), Maria Nieves Brunet Avalos. "Stereo vision-based system for detection, track and capture of intruder flying drones." Thesis, 2020.
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