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See detailAiding Reflective Navigation in a Dynamic Information Landscape: A Challenge for Educational Psychology
Bobrowicz, Katarzyna UL; Han, Areum UL; Hausen, Jennifer UL et al

in Frontiers in Psychology (2022)

Open access to information is now a universal phenomenon thanks to rapid technological developments across the globe. This open and universal access to information is a key value of democratic societies ... [more ▼]

Open access to information is now a universal phenomenon thanks to rapid technological developments across the globe. This open and universal access to information is a key value of democratic societies because, in principle, it supports well-informed decision-making on individual, local, and global matters. In practice, however, without appropriate readiness for navigation in a dynamic information landscape, such access to information can become a threat to public health, safety, and economy, as the COVID-19 pandemic has shown. In the past, this readiness was often conceptualized in terms of adequate literacy levels, but the contemporarily observed highest-ever literacy levels have not immunized our societies against the risks of misinformation. Therefore, in this Perspective, we argue that democratisation of access to information endows citizens with new responsibilities, and second, these responsibilities demand readiness that cannot be reduced to mere literacy levels. In fact, this readiness builds on individual adequate literacy skills, but also requires rational thinking and awareness of own information processing. We gather evidence from developmental, educational, and cognitive psychology to show how these aspects of readiness could be improved through education interventions, and how they may be related to healthy work-home balance and self-efficacy. All these components of education are critical to responsible global citizenship and will determine the future direction of our societies. [less ▲]

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See detailA Large-scale Empirical Analysis of Ransomware Activities in Bitcoin
Wang, Kai; Pang, Jun UL; Chen, Dingjie et al

in ACM Transactions on the Web (2022), 16(2), 71-729

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See detailMASS: A tool for Mutation Analysis of Space CPS
Cornejo Olivares, Oscar Eduardo UL; Pastore, Fabrizio UL; Briand, Lionel UL

in 2022 IEEE/ACM 44st International Conference on Software Engineering (2022, May)

We present MASS, a mutation analysis tool for embedded software in cyber-physical systems (CPS). We target space CPS (e.g., satellites) and other CPS with similar characteristics (e.g., UAV). Mutation ... [more ▼]

We present MASS, a mutation analysis tool for embedded software in cyber-physical systems (CPS). We target space CPS (e.g., satellites) and other CPS with similar characteristics (e.g., UAV). Mutation analysis measures the quality of test suites in terms of the percentage of detected artificial faults. There are many mutation analysis tools available, but they are inapplicable to CPS because of scalability and accuracy challenges. To overcome such limitations, MASS implements a set of optimization techniques that enable the applicability of mutation analysis and address scalability and accuracy in the CPS context. MASS has been successfully evaluated on a large study involving embedded software systems provided by industry partners; the study includes an on-board software system managing a microsatellite currently on-orbit, a set of libraries used in deployed cubesats, and a mathematical library provided by the European Space Agency. A demo video of MASS is available at https://www.youtube.com/watch?v=gC1x9cU0-tU. [less ▲]

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See detailHUDD: A tool to debug DNNs for safety analysis
Fahmy, Hazem UL; Pastore, Fabrizio UL; Briand, Lionel UL

in 2022 IEEE/ACM 44st International Conference on Software Engineering (2022, May)

We present HUDD, a tool that supports safety analysis practices for systems enabled by Deep Neural Networks (DNNs) by automatically identifying the root causes for DNN errors and retraining the DNN. HUDD ... [more ▼]

We present HUDD, a tool that supports safety analysis practices for systems enabled by Deep Neural Networks (DNNs) by automatically identifying the root causes for DNN errors and retraining the DNN. HUDD stands for Heatmap-based Unsupervised Debugging of DNNs, it automatically clusters error-inducing images whose results are due to common subsets of DNN neurons. The intent is for the generated clusters to group error-inducing images having common characteristics, that is, having a common root cause. HUDD identifies root causes by applying a clustering algorithm to matrices (i.e., heatmaps) capturing the relevance of every DNN neuron on the DNN outcome. Also, HUDD retrains DNNs with images that are automatically selected based on their relatedness to the identified image clusters. Our empirical evaluation with DNNs from the automotive domain have shown that HUDD automatically identifies all the distinct root causes of DNN errors, thus supporting safety analysis. Also, our retraining approach has shown to be more effective at improving DNN accuracy than existing approaches. A demo video of HUDD is available at https://youtu.be/drjVakP7jdU. [less ▲]

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See detailPreventing Frame Fingerprinting in Controller Area Network Through Traffic Mutation
Buscemi, Alessio UL; Turcanu, Ion; Castignani, German UL et al

in Preventing Frame Fingerprinting in Controller Area Network Through Traffic Mutation (2022, May)

The continuous increase of connectivity in commercial vehicles is leading to a higher number of remote access points to the Controller Area Network (CAN) – the most popular in-vehicle network system. This ... [more ▼]

The continuous increase of connectivity in commercial vehicles is leading to a higher number of remote access points to the Controller Area Network (CAN) – the most popular in-vehicle network system. This factor, coupled with the absence of encryption in the communication protocol, poses serious threats to the security of the CAN bus. Recently, it has been demonstrated that CAN data can be reverse engineered via frame fingerprinting, i.e., identification of frames based on statistical traffic analysis. Such a methodology allows fully remote decoding of in-vehicle data and paves the way for remote pre-compiled vehicle-agnostic attacks. In this work, we propose a first solution against CAN frame fingerprinting based on mutating the traffic without applying modifications to the CAN protocol. The results show that the proposed methodology halves the accuracy of CAN frame fingerprinting. [less ▲]

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See detailA Deep Dive inside DREBIN: An Explorative Analysis beyond Android Malware Detection Scores
Daoudi, Nadia UL; Allix, Kevin UL; Bissyande, Tegawendé François D Assise UL et al

in ACM Transactions on Privacy and Security (2022), 25(2),

Machine learning (ML) advances have been extensively explored for implementing large-scale malware detection. When reported in the literature, performance evaluation of ML-based detectors generally ... [more ▼]

Machine learning (ML) advances have been extensively explored for implementing large-scale malware detection. When reported in the literature, performance evaluation of ML-based detectors generally focuses on highlighting the ratio of samples that are correctly or incorrectly classified, overlooking essential questions on why/how the learned models can be demonstrated as reliable. In the Android ecosystem, several recent studies have highlighted how evaluation setups can carry biases related to datasets or evaluation methodologies. Nevertheless, there is little work attempting to dissect the produced model to provide some understanding of its intrinsic characteristics. In this work, we fill this gap by performing a comprehensive analysis of a state-of-the-art Android Malware detector, namely DREBIN, which constitutes today a key reference in the literature. Our study mainly targets an in-depth understanding of the classifier characteristics in terms of (1) which features actually matter among the hundreds of thousands that DREBIN extracts, (2) whether the high scores of the classifier are dependent on the dataset age, (3) whether DREBIN's explanations are consistent within malware families, etc. Overall, our tentative analysis provides insights into the discriminatory power of the feature set used by DREBIN to detect malware. We expect our findings to bring about a systematisation of knowledge for the community. [less ▲]

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See detailThe IoT and the new EU cybersecurity regulatory landscape
Chiara, Pier Giorgio UL

in International Review of Law, Computers and Technology (2022), 36(2),

This article aims to cast light on how the fast-evolving European cybersecurity regulatory framework would impact the Internet of Things (IoT) domain. The legal analysis investigates whether and to what ... [more ▼]

This article aims to cast light on how the fast-evolving European cybersecurity regulatory framework would impact the Internet of Things (IoT) domain. The legal analysis investigates whether and to what extent existing and proposed sectoral EU legislation addresses the manifold challenges in securing IoT and its supply chain. It firstly takes into account the Cybersecurity Act, being the most recent and relevant EU legal act covering ICT products and cybersecurity services. Then, EU product legislation is scrutinised. The analysis focuses on the delegated act recently adopted by the Commission under the Radio Equipment Directive (RED), strengthening wireless devices’ cybersecurity, the Medical Devices Regulation, the Proposal for a General Product Safety Regulation and the Proposal for a Machinery Regulation. Lastly, the proposal for a revised Network and Information Systems Directive (NIS2) is assessed in terms of its potential impact on the field of IoT cybersecurity. Against this backdrop, the article concludes by advocating the need for a separate horizontal legislation on cybersecurity for connected products. To avoid fragmentation of the EU’s Single Market, a horizontal legal act should be based on the principles of the New Legislative Framework, with ex-ante and ex-post cybersecurity requirements for all IoT sectors and products categories. [less ▲]

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See detailFlight to Safety and Retail Investor Behavior
Lehnert, Thorsten UL

in International Review of Financial Analysis (2022), 81

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See detailThe COVID 19 pandemic as a fortuitous disruptor in physical education: the case of active homework
Bailey, Richard; Scheuer, Claude UL

in AIMS Public Health (2022), 9(2), 423-439

Measures devised to contain the COVID 19, including isolation, social distancing, and quarantine, have profoundly affected people’s lives around the world. One of the consequences of these actions has ... [more ▼]

Measures devised to contain the COVID 19, including isolation, social distancing, and quarantine, have profoundly affected people’s lives around the world. One of the consequences of these actions has been a general reduction in the habitual daily physical activity among children and young people for whom schools represent the major setting for the promotion of sports, physically active play, movement skills learning, and other activity supportive of healthy, active lifestyles. Whilst acknowledging the seriousness of these changes, and their concomitant health risks, we suggest that COVID 19 offers an opportunity to think again about important features of school based activity promotion in light of new lessons learnt during lockdown, emerging technologies, and adapted pedagogies. In these specific cases, COVID 19 could be judged a fortuitous disruptor to the extent that it has opened a window of opportunity to schools and teachers to reflect on their assumptions about the scope, content, and delivery of the curricula, and on the new professional knowledge that has emerged. Active Homework, or physical activity related tasks assigned to students by teachers that are meant to be carried out before, after and away from school, that students can do on their ow n or with family members, is not a new idea, but the enforced changes to school provision have made it considerably more common since the pandemic. Perhaps Active Homework is a concept worth retaining as schools start to return to normal ””? We offer a typo logy of Active Homework, and examine opportunities to expand, extend, and enhance physical education and physical activity opportunities by breaking down the presumed boundary between school and home. In conclusion, we suggest that Active Homework is worth exploring as a potentially valuable approach to enhancing the quantity and quality of students’ school based health related physical activity. If so, considerably more research and curriculum development is needed. [less ▲]

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See detailEvaluation of the Multipath Environment Using Electromagnetic-Absorbing Materials at Continuous GNSS Stations
Hunegnaw, Addisu UL; Teferle, Felix Norman UL

in Sensors (2022), 22(9), 1-23

o date, no universal modelling technique is available to mitigate the effect of site-specific multipaths in high-precision global navigation satellite system (GNSS) data processing. Multipaths affect both ... [more ▼]

o date, no universal modelling technique is available to mitigate the effect of site-specific multipaths in high-precision global navigation satellite system (GNSS) data processing. Multipaths affect both carrier-phase and code/pseudorange measurements, and the errors can propagate and cause position biases. This paper presents the use of an Eccosorb AN-W-79 microwave-absorbing material mounted around a GNSS antenna that reflects less than −17 dB of normal incident energy above a frequency of 600 MHz. To verify the feasibility and effectiveness of the Eccosorb, we installed two close stations by continuously operating multi-GNSS (BeiDou, GLONASS, Galileo and GPS) in a challenging location. One station is equipped with the Eccosorb AN-W-79, covering a square area of 3.35 m2 around the antenna, and the second station operates without it. The standard deviation reductions from single point positioning estimates are significant for all the individual GNSS solutions for the station equipped with microwave-absorbing material. The reductions are as follows: for GPS, between 15% and 23%; for Galileo, between 22% and 45%; for GLONASS, 22%; and for BeiDou, 4%. Furthermore, we assess the influence of multipaths by analysing the linear combinations of code and carrier phase measurements for various GNSS frequencies. The Galileo code multipath shows a reduction of more than 60% for the station with microwave-absorbing material. For GLONASS, particularly for the GLOM3X and GLOM1P code multipath combinations, the reduction reaches 50%, depending on the observation code types. For BeiDou, the reduction is more than 30%, and for GPS, it reaches between 20% and 40%. The Eccosorb AN-W-79 microwave-absorbing material shows convincing results in reducing the code multipath noise level. Again, using microwave-absorbing material leads to an improvement between 15% and 60% in carrier phase cycle slips. The carrier-phase multipath contents on the post-fit residuals from the processed GNSS solutions show a relative RMS reduction of 13% for Galileo and 9% for GLONASS and GPS when using the microwave-absorbing material. This study also presents power spectral contents from residual signal-to-noise ratio time series using Morlet wavelet transformation. The power spectra from the antenna with the Eccosorb AN-W-79 have the smallest magnitude, demonstrating the capacity of microwave-absorbing materials to lessen the multipath influence while not eliminating it. [less ▲]

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See detailHistory and Shared Authority
Cauvin, Thomas UL

in Understanding the World through History (2022)

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See detailProjet Approche Patient Partenaire de Soins (APPS) - Projekts Ansatz der Patienten-Partner-Betreuung
Odero, Angela UL; Baumann-Croisier, Pierre; Chauvel, Louis UL et al

Conference given outside the academic context (2022)

Notre projet a permis d’observer une volonté affichée d’évoluer vers davantage d’engagement du patient dans la relation de soin et dans les structures de soins de santé. Le développement attendu passera ... [more ▼]

Notre projet a permis d’observer une volonté affichée d’évoluer vers davantage d’engagement du patient dans la relation de soin et dans les structures de soins de santé. Le développement attendu passera par une approche systémique de l’engagement tant sur des aspects micro (de la relation de soin) méso (dans la coordination des structures de soins) et macro (avec l’engagement des politiques de santé). Le développement doit s’appuyer sur les initiatives existantes : en ce sens le projet Interreg est une belle façon de promouvoir les échanges de bonnes pratiques au service de cet engagement du patient. [less ▲]

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See detailTowards a Unified and Robust Data-Driven Approach. A Digital Transformation of Production Plants in the Age of Industry 4.0
Benedick, Paul-Lou UL

Doctoral thesis (2022)

Nowadays, industrial companies are engaging their global transition toward the fourth industrial revolution (the so-called Industry 4.0). The main objective is to increase the Overall Equipment ... [more ▼]

Nowadays, industrial companies are engaging their global transition toward the fourth industrial revolution (the so-called Industry 4.0). The main objective is to increase the Overall Equipment Effectiveness (OEE), by collecting, storing and analyzing production data. Several challenges have to be tackled to propose a unified data-driven approach to rely on, from the low-layers data collection on the machine production lines using Operational Technologies (OT), to the monitoring and more importantly the analysis of the data using Information Technologies (IT). This is all the more important for companies having decades of existence – as Cebi Luxembourg S.A., our partner in a Research, Development and Innovation project subsidised by the ministry of the Economy in Luxembourg – to upgrade their on-site technologies and move towards new business models. Artificial Intelligence (AI) now knows a real interest from industrial actors and becomes a cornerstone technology for helping humans in decision-making and data-analysis tasks, thanks to the huge amount of (sensors-based) univariate time-series available in the production floor. However, such amount of data is not sufficient for AI to work properly and to make right decisions. This also requires a good data quality. Indeed, good theoretical performance and high accuracy can be obtained when trained and tested in isolation, but AI models may still provide degraded performance in real/industrial conditions. In that context, the problem is twofold: • Industrial production systems are vertically-oriented closed systems that make difficult their communication and their cooperation with each other, and intrinsically the data collection. • Industrial companies used to implement deterministic processes. Introducing AI - that can be classified as stochastic - in the industry requires a full understanding of the potential deviation of the models in order to be aware of their domain of validity. This dissertation proposes a unified strategy for digitizing an industrial system and methods for evaluating the performance and the robustness of AI models that can be used in such data-driven production plants. In the first part of the dissertation, we propose a three-steps strategy to digitize an industrial system, called TRIDENT, that enables industrial actors to implement data collection on production lines, and in fine to monitor in real-time the production plant. Such strategy has been implemented and evaluated on a pilot case-study at Cebi Luxembourg S.A. Three protocols (OPC-UA, MQTT and O-MI/O-DF) are used for investigating their impact on the real-time performance. The results show that, even if these protocols have some disparity in terms of performance, they are suitable for an industrial deployment. This strategy has now been extended and implemented by our partner - Cebi Luxembourg S.A - in its production environment. In the second part of the thesis dissertation, we aim at investigating the robustness of AI models in industrial settings. We then propose a systematic approach to evaluate the robustness under perturbations. Assuming that i) real perturbations - in particular on the data collection - cannot be recorded or generated in real industrial environment (that could lead to production stops) and ii) a model would not be implemented before evaluating its potential deviations, limits or weaknesses, our approach is based on artificial injections of perturbations into the data sets, and is evaluated on state-of-the-art classifiers (both Machine-Learning and Deep-Learning) and data sets (in particular, public sensors-based univariate time series). First, we propose a coarse-grained study, with two artificial perturbations - called swapping effect and dropping effect - in which simple random algorithms are used. This already highlights a great disparity of the models’ robustness under such perturbations that industrial actors need to be aware of. Second, we propose a fine-grained study where instead of testing randomly some parameters' values, we used Genetic Algorithms to look for the models' limits. To do so, we define our multi-objectives optimisation problem with a fitness function as: maximising the impact of the perturbations (i.e. decreasing the most the model's accuracy), while minimising the changes in the time-series (with regards to our two parameters). This can be seen as an adversarial case, where the goal is not to exploit these weaknesses in a malicious way but to be aware of. Based on such a study, methods for making more robust the model and/or for observing such behaviour on the infrastructure could be investigated and implemented if needed. The tool developed in this latter study is therefore ready for being used in a real industrial case, where data sets and perturbations can now be fitted to the scenario. [less ▲]

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See detailThe Luxembourg Financial Ecosystem and the European Monetary Innovation. Cas Study on KBL, LuxSE and EIB (1957-1990)
Danescu, Elena UL; Cheng, Anqi

Scientific Conference (2022, April 26)

The Luxembourg international financial centre developed considerably during the 1960s, propelled by several factors including concerted government policy, flexible regulation and a willingness to harness ... [more ▼]

The Luxembourg international financial centre developed considerably during the 1960s, propelled by several factors including concerted government policy, flexible regulation and a willingness to harness opportunities at international level (such as the 1963 US interest equalisation tax and the Bundesbank provisions introduced in 1968 and 1974). The decision to establish various Community institutions (the ECSC High Authority in 1952) and European funding institutions (the European Investment Bank in 1968) in the country also had a decisive impact. The currency union with Belgium (BLEU, 1921) and the absence of a Luxembourg Central Bank made these developments all the more significant. Drawing on archives and oral history sources, this paper aims to illustrate the complexity and originality that characterised the development of the conceptual, political and regulatory context in Luxembourg in the 1960s-1990s, in what can be seen as a sui generis experiment and preparation for EMU. It will explore the changing financial ecosystem in Luxembourg and the collaborative efforts by its main stakeholders (banks, regulatory authorities, individuals, networks) - with a focus on KBL, LuxSE and EIB - to encourage financial and monetary innovation (via the EUA, ECU, and Eurco) before the introduction of the European single currency and to pave the way for the establishment and consolidation of the euro [less ▲]

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See detailUser Experience Design for Cybersecurity & Privacy: addressing user misperceptions of system security and privacy
Stojkovski, Borce UL

Doctoral thesis (2022)

The increasing magnitude and sophistication of malicious cyber activities by various threat actors poses major risks to our increasingly digitized and inter-connected societies. However, threats can also ... [more ▼]

The increasing magnitude and sophistication of malicious cyber activities by various threat actors poses major risks to our increasingly digitized and inter-connected societies. However, threats can also come from non-malicious users who are being assigned too complex security or privacy-related tasks, who are not motivated to comply with security policies, or who lack the capability to make good security decisions. This thesis posits that UX design methods and practices are necessary to complement security and privacy engineering practices in order to (1) identify and address user misperceptions of system security and privacy; and (2) inform the design of secure systems that are useful and appealing from end-users’ perspective. The first research objective in this thesis is to provide new empirical accounts of UX aspects in three distinct contexts that encompass security and privacy considerations, namely: cyber threat intelligence, secure and private communication, and digital health technology. The second objective is to empirically contribute to the growing research domain of mental models in security and privacy by investigating user perceptions and misperceptions in the afore-mentioned contexts. Our third objective is to explore and propose methodological approaches to incorporating users’ perceptions and misperceptions in the socio-technical security analyses of systems. Qualitative and quantitative user research methods with experts as well as end users of the applications and systems under investigation were used to achieve the first two objectives. To achieve the third objective, we also employed simulation and computational methods. Cyber Threat Intelligence: CTI sharing platforms Reporting on a number of user studies conducted over a period of two years, this thesis offers a unique contribution towards understanding the constraining and enabling factors of security information sharing within one of the leading CTI sharing platforms, called MISP. Further, we propose a conceptual workflow and toolchain that would seek to detect user (mis)perceptions of key tasks in the context of CTI sharing, such as verifying whether users have an accurate comprehension of how far information travels when shared in a CTI sharing platform, and discuss the benefits of our socio-technical approach as a potential security analysis tool, simulation tool, or educational / training support tool. Secure & Private Communication: Secure Email We propose and describe multi-layered user journeys, a conceptual framework that serves to capture the interaction of a user with a system as she performs certain goals along with the associated user beliefs and perceptions about specific security or privacy-related aspects of that system. We instantiate the framework within a use case, a recently introduced secure email system called p≡p, and demonstrate how the approach can be used to detect misperceptions of security and privacy by comparing user opinions and behavior against system values and objective technical guarantees offered by the system. We further present two sets of user studies focusing on the usability and effectiveness of p≡p’s security and privacy indicators and their traffic-light inspired metaphor to represent different privacy states and guarantees. Digital Health Technology: Contact Tracing Apps Considering human factors when exploring the adoption as well as the security and privacy aspects of COVID-19 contact tracing apps is a timely societal challenge as the effectiveness and utility of these apps highly depend on their widespread adoption by the general population. We present the findings of eight focus groups on the factors that impact people’s decisions to adopt, or not to adopt, a contact tracing app, conducted with participants living in France and Germany. We report how our participants perceived the benefits, drawbacks, and threat model of the contact tracing apps in their respective countries, and discuss the similarities and differences between and within the study groups. Finally, we consolidate the findings from these studies and discuss future challenges and directions for UX design methods and practices in cybersecurity and digital privacy. [less ▲]

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See detailMachine learning in Public Health: Relevant applications in ageing populations
Leist, Anja UL

Presentation (2022, April 25)

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See detailRKHS Based State Estimator for Radar Sensor in Indoor Application
Kumar Singh, Uday UL; Shankar, Bhavani; Alaee, Mohammad

Scientific Conference (2022, April 23)

For the estimation of targets’ states (location, velocity, and acceleration) from nonlinear radar measurements, usually, the improved version of well known Kalman filter: extended Kalman filter (EKF) and ... [more ▼]

For the estimation of targets’ states (location, velocity, and acceleration) from nonlinear radar measurements, usually, the improved version of well known Kalman filter: extended Kalman filter (EKF) and unscented Kalman filter (UKF) are used. However, EKF and UKF approximates the nonlinear measurement function either by Jacobian or using sigma points. Consequently, because of the approximation of the measurement function, the EKF and UKF cannot achieve high estimation accuracy. The potential solution is to replace the approximation of nonlinear measurement function with its estimate, obtained in high dimensional reproducing kernel Hilbert space (RKHS). An ample amount of research has been done in this direction, and the combined filter is termed RKHS based Kalman filter. However, there is a shortage of literature dealing with estimating the dynamic state of the target in an indoor environment using RKHS based Kalman filter. Therefore, in this paper, we propose the use of RKHS based Kalman filter for indoor application. Specifically, we validate the suitability of the RKHS based Kalman filtering approach using simulations performed over three different target motion models. [less ▲]

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