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Nowadays established companies use Corporate Entrepreneurship (CE) as a means to create discontinuous innovations. Many companies thereby even implement multiple CE units that typically involve several entrepreneurial activities. This explorative study aimed to identify the reasons why established companies implement multiple CE units concurrently. In conducting a comparative case study with eight companies from different industries, valuable insights for science and practice were gained. We provide an overview of different 11 reasons for implementing multiple CE units. This shows that the combination of CE units used by companies differs depending on the reason. It further allowed to derive general approaches of established companies to the implementation of CE units. Last, we identify the concept of co-specialization to be a central driver explaining the creation of the need to set up multiple units. We conclude by indicating implications and subjects for future research.
The cornerstone of cognitive systems is environment awareness which enables agile and adaptive use of channel resources. Whitespace prediction based on learning the statistics of the wireless traffic has proven to be a powerful tool to achieve such awareness. In this paper, we propose a novel Hidden Markov Model (HMM) based spectrum learning and prediction approach which accurately estimates the exact length of the whitespace in WiFi channels within the shared industrial scientific medical ISM) bands. We show that extending the number of hidden states and formulating the prediction problem as a maximum likelihood (ML) classification leads to a substantial increase in the prediction horizon compared to classical approaches that predict the immediate (short-term) future. We verify the proposed algorithm through simulations which utilize a model for WiFi traffic based on extensive measurement campaigns.
Visualization-Assisted Development of Deep Learning Models in Offline Handwriting Recognition
(2018)
Deep learning is a field of machine learning that has been the focus of active research and successful applications in recent years. Offline handwriting recognition is one of the research fields and applications were deep neural networks have shown high accuracy. Deep learning models and their training pipeline show a large amount of hyper-parameters in their data selection, transformation, network topology and training process that are sometimes interdependent. This increases the overall difficulty and time necessary for building and training a model for a specific data set and task at hand. This work proposes a novel visualization-assisted workflow that guides the model developer through the hyper-parameter search in order to identify relevant parameters and modify them in a meaningful way. This decreases the overall time necessary for building and training a model. The contributions of this work are a workflow for hyper-parameter search in offline handwriting recognition and a heat map based visualization technique for deep neural networks in multi-line offline handwriting recognition. This work applies to offline handwriting recognition, but the general workflow can possibly be adapted to other tasks as well.
Motion estimation is an essential element for autonomous vessels. It is used e.g. for lidar motion compensation as well as mapping and detection tasks in a maritime environment. Because the use of gyroscopes is not reliable and a high performance inertial measurement unit is quite expensive, we present an approach for visual pitch and roll estimation that utilizes a convolutional neural network for water segmentation, a stereo system for reconstruction and simple geometry to estimate pitch and roll. The algorithm is validated on a novel, publicly available dataset recorded at Lake Constance. Our experiments show that the pitch and roll estimator provides accurate results in comparison to an Xsens IMU sensor. We can further improve the pitch and roll estimation by sensor fusion with a gyroscope. The algorithm is available in its implementation as a ROS node.
When mobile devices at the network edge want to communicate with each other, they too often depend on the availability of faraway resources. For direct communication, feasible user-friendly service discovery is essential. DNS Service Discovery over Multicast DNS (DNS-SD/mDNS) is widely used for configurationless service discovery in local networks, due inno small part to the fact that it is based on the well establishedDNS, and efficient in small networks. In our research, we enhance DNS-SD/mDNS providing versatility, user control, efficiency, and privacy, while maintaining the deployment simplicity and backward compatibility. These enhancements are necessary to make it a solid, flexible foundationfor device communication in the edge of the Internet. In this paper, we focus on providing multi-link capabilities and scalable scopes for DNS-SD while being mindful of both user-friendliness and efficiency. We propose DNS-SD over StatelessDNS (DNS-SD/sDNS), a solution that allows configurationless service discovery in arbitrary self-named scopes - largely independentof the physical network layout - by leveraging ourStateless DNS technique and the Raft consensus algorithm.
Ballistocardiography (BCG) can be used to monitor heart rate activity. Besides, the accelerometer should have high sensitivity and minimal internal noise; a low-cost approach was taken into consideration. Several measurements have been executed to determine the optimal positioning of a sensor under the mattress to obtain a signal strong enough for further analysis. A prototype for an unobtrusive accelerometer-based measurement system has been developed and tested in a conventional bed without any specific extras. The influence of the human sleep position for the output accelerometer data was tested. The obtained results indicate the potential to capture BCG signals using accelerometers. The measurement system can detect heart rate in an unobtrusive form in the home environment.
This article describes a research project that aims at investigating individual entrepreneurial founders concerning their shift tendencies of decision-making logics - especially during the respective phases of the venture creating process. Prior studies found that team founders show a hybrid perspective on strategic decision-making. They not only combine causation (planning-based) and effectuation (flexible) logics but also show logic shifts and also re-shifts over time. Due to the fact, that founders' social identity shapes early structuring processes, this article describes the necessity of elimination of in-group influences of multi-founding ventures and focus on individuals in order to make specific assessments on logic shifts and re-shifts. Based on an extensive literature review, a pre-selection-test and a qualitative case study design from the empirical body of the paper. Insofar, this study applies a qualitative design of a process research approach to investigate shifts of decision-making logics of individual founders in new venture creation over time.
Corporate Entrepreneurship (CE) has now evolved into an imperative innovation practice of established companies. Despite organizational design models for CE activities and companies' frequent initiation of new activities, effectively managing them remains a challenging endeavor which results in disappointment about the outcomes of CE and its early termination. We assume specific types of goals for CE as one element of this unresolved management issue. While both practice and literature address goals in different contexts, no uniform picture has emerged so far. Although goals are commonly used to categorize CE activities, they seldomly seem to be the core subject of investigation. Based on this preliminary analysis and consolidation, we put the goals of CE in focus. In a systematic literature review, we reveal aspects of goals to unmask the different types of goals and their underlying dimensions and characteristics. Our review contributes to a better understanding of goals by (1) organizing relevant literature on goals of CE in a specific classification process, (2) describing dimensions and attributes for a systematic classification of CE goals; and (3) providing a framework showing differences of goals for the CE context. We conclude with a discussion and hints for future research paths.
Low-Code Development Platforms (LCDPs) enable non-information technology (IT) personnel to develop applications and workflows independently of the IT department. Consequently, these digital platforms help to overcome the growing need for software development. However, science and practice warn of several barriers that slow down or hinder the usage of LCDPs. This publication scientifically identifies, analyzes, and discusses challenges during implementation and application of LCDPs from both perspectives in a holistic manner. Therefore, we conduct an exploratory study (data from scientific literature, expert interviews, and practical studies) and assign the challenges to the socio-technical system model. The results show that the scientific and practical communities recognize common challenges (especially knowledge transfer) but also perceive differences related to technological (science) and social (practice) aspects. This paper proposes future research directions for academia, such as governance, culture change, and value evaluation of LCDPs. Additionally, practitioners can prepare for possible challenges when using LCPDs.
TU Darmstadt HUMVIB-Bridge
(2016)
The simulation of the human-induced vibrations of lightweight footbridges is in general a complex problem where the dynamics of the pedestrian system meets the structural dynamics of the bridge. However, standard methods for numerical analysis of pedestrian bridges deal with this issue by using simplified approaches. The structure is mostly represented either by discretised multi mass systems or through a formulation in modal coordinates, while the excitation is typically described by a moving load.
Positive effects of the interaction between the two systems (pedestrian and structure) are usually completely neglected. This paper, which is partially
extracted from an actual research report of the Institute of Structural Mechanics and Design (TU Darmstadt), presents an experimental set-up developed for investigations of the human-structure interaction (HSI), as well as results of the preliminary investigations carried out in the same context.
This paper summarizes the trends in metallization and interconnection technology in the eyes of the participants of the 8th Metallization and Interconnection Workshop. Participants were asked in a questionnaire to share their view on the future development of metallization technology, the kind of metal used for front side metallization and the future development of interconnection technology. The continuous improvement of the screen-printing technology is reflected in the high expected percentage share decreasing from 88% in three years to still 70% in ten years. The dominating front side metal in the view of the participants will be silver with an expected percentage share of nearly 70% in 2029. Regarding interconnection technologies, the experts of the workshop expect new technologies to gain significant technology shares faster. Whereas in three years soldering on busbars is expected to dominate with a percentage share of 71% it will drop in ten years to 35% in the eyes of the participants. Multiwire and shingling technologies are seen to have the highest potential with expected percentage shares of 33% (multiwire) and 16% (shingling) in ten years.
The trajectory tracking problem for a real-scaled fully-actuated surface vessel is addressed in this paper. A nonlinear model predictive control (NMPC) scheme was designed to track a reference trajectory, considering state and input constraints, and environmental disturbances, which were assumed to be constant over the prediction horizon. The controller was tested by performing docking maneuvers using the real-scaled research vessel from the University of Applied Sciences Konstanz at the Rhine river in Germany. A comparison between the experimental results and the simulated ones was analyzed to validate the NMPC controller.
Trajectory Tracking of a Fully-actuated Surface Vessel using Nonlinear Model Predictive Control
(2021)
The trajectory tracking problem for a fully-actuated real-scaled surface vessel is addressed in this paper. The unknown hydrodynamic and propulsion parameters of the vessel’s dynamic model were identified using an experimental maneuver-based identification process. Then, a nonlinear model predictive control (NMPC) scheme is designed and the controller’s performance is assessed through the variation of NMPC parameters and constraints tightening for tracking a curved trajectory.
This paper presents the integration of a spline based extension model into a probability hypothesis density (PHD) filter for extended targets. Using this filter the position and extension of each object as well as the number of present objects can jointly be estimated. Therefore, the spline extension model and the PHD filter are addressed and merged in a Gaussian mixture (GM) implementation. Simulation results using artificial laser measurements are used to evaluate the performance of the presented filter. Finally, the results are illustrated and discussed.
Virtual measurement models (VMM) can be used to generate artificial measurements and emulate complex sensor models such as Lidar. The input of the VMM is an estimation and the output is the set of measurements this estimation would cause. A Kalman filter with extension estimation based on random matrices is used to filter mean and covariance of the real measurements. If these match the mean and covariance of the artificial measurements, then the given estimation is appropriate. The optimal input of the VMM is found using an adaptation algorithm. In this paper, the VMM approach is expanded for multi-extended object tracking where objects can be occluded and are only partially visible. The occlusion can be compensated if the extension estimation is performed for all objects together. The VMM now receives as input an estimation for the multi-object state and the output are the measurements that this multi-object state would cause.
Corporate entrepreneurship (CE) is experiencing continuously increasing interest from scholars and practitioners. One reason for this seems to be rooted in the organizational structures of established companies, which are cumbersome for implementing organizational agility and for developing radical innovations. In view of the advancing digitalization, however, exactly this is required in order to be successful in the long-term. CE is a promising managerial tool that offers a wide range of options to pursue the creation of new businesses and to support the companies' transformation in order to adapt to changes in the environment. Even though CE offers a broad range of opportunities, the effective management is a challenge. One reason for this is the ambiguity when it comes to the differences between the various CE forms and the objectives that can be achieved by those. This study, which is based on 13 in-depth interviews from eight high-tech companies, contributes to a better understanding of CE by offering a first harmonized set of CE objectives that is suitable to compare and differentiate across the different forms. In addition to that, three CE types, offering a new perspective on how to differentiate CE forms, are identified and give implications for a more effective management.
Realistic traffic modeling plays a key role in efficient Dynamic Spectrum Access (DSA) which is considered as enabler for the employment of wireless technologies in critical industrial automation applications (IAA). The majority of models of spectrum usage are not suitable for this specific use case as they are based on measurement campaigns conducted in urban or controlled laboratory environments. In this work we present a time-domain traffic model for industrial communication in the 2.4 GHz industrial, scientific, medical (ISM) band based on measurements in an industrial automotive production site. As DSA is usually implemented on Software Defined Radios (SDR), our measurement campaign is based on SDR platforms rather than sophisticated spectrum analyzers. We show through the estimation of the Hurst parameter that industrial wireless traffic possesses inherent self-similarity that could be exploited for efficient DSA. We also show that wireless traffic could be modeled as a semi-Markov model with channel on and off durations Log-normally and Pareto distributed, respectively. We finally estimate the parameters of the derived models using Maximum Likelihood estimation.
Nowadays, information technology (IT) is a strategic asset for organizations. As a result, the IT costs are rising and there is a need for transparency about their root causes. Cost drivers as an instrument in IT cost management enable a better transparency and understanding of costs. However, there is a lack of IT cost driver research with a focus on the strategic position of IT within organizations. The goal of this paper is to develop a comprehensive overview of strategic drivers of IT costs. The Delphi study leads to the identification and validation of 17 strategic drivers. Hence, this paper builds a base for cost driver analysis and contributes to a better understanding of the causes of costs. It facilitates future research regarding cost behavior and the business value of IT. Additionally, practitioners gain awareness of levers to influence IT costs and consequences of managerial decisions on their IT spend.
Business units are increasingly able to fuel the transformation that digitalization demands of organizations. Thereby, they implement Shadow IT (SIT) to create flexible and innovative solutions. However, the individual implementation of SIT leads to high complexities and redundancies. Integration suggests itself to meet these challenges but can also eliminate the described benefits. In this emergent research, we develop propositions for a conceptual decision framework, that balances the benefits and drawbacks of an integration of SIT using a literature review as well as a multiple-case study. We thereby integrate the perspective of the overall organization as well as the specific business unit. We then pose six propositions regarding SIT integration that will serve to evaluate our conceptual framework in future research.
Tourist tracking
(2015)
Adjusting the friction response of the wheel-rail interface is a key factor in the mitigation of wear and rollingcontact fatigue (RCF) in rails. The use of top-of-rail (TOR) friction conditioners has the potential to reduce maintenance costs significantly. Unfortunately, conflicting results on the use of commercial TOR conditioners have been presented in the literature. In this work, the performance of commercial TOR conditioners and a laboratory-made formulation were tested, both on the lab scale and in field measurements. Friction results are discussed together with the structural and chemical analysis of the tested materials.
Think BIQ: Gender Differences, Entrepreneurship Support and the Quality of Business Idea Description
(2023)
Entrepreneurship support, its influencing factors and female entrepreneurship are recently discussed topics with great relevance for society and politics. However, research on the subject has been divergent in its results and lacks a focus on the impact of support programs’ characteristics concerning different types of entrepreneurs. Thus, we conduct a fuzzy-set Qualitative Comparative Analysis on entrepreneurship support characteristics aiming to shed light on possible gender differences occurring in respective programs. We investigate the quality of business idea descriptions, as a predecessor for a high-potential business model, operationalized using inter alia causation and effectuation theory and social role theory as possible explanations. In our fuzzy-set Qualitative Comparative Analysis on a sample of 911 Norwegian ventures, we find a variety of differences related to the entrepreneurs’ gender. For instance, that financial support combined with a well described key contribution or careful planning seem to be more important antecedents for female entrepreneurs’ business idea quality than for males. Moreover, it seems a well-described key contribution has a positive effect on the outcome variable in most cases. Another interesting finding concerns the entrepreneurs’ network partners, where we found evident gender differences in our combinations. Female entrepreneurs seemingly benefitted from rather small networks, and males from big networks, although the former possess larger networks in the sample. In conclusion, we find that gender differences in combinations of entrepreneurship support for high business idea quality still occur even in a country like Norway, calling for an adaption of the provided support and environment.
Dissipation of heat can be a major challenge when applying sensor systems outdoors under varying environmental conditions. Typically, complex software and knowledge is needed to optimize thermal management. In this paper it is shown how the thermal optimization of a LiDAR (light detection and ranging) sensor can be performed efficiently. This approach uses standard CAD (computer aided design) software, which is readily available, and saves time and cost as the thermal design can be optimized before experimental realisation. A four-step process was developed and realized: (i) Measurement of the thermal energy distribution of the current sensor design; (ii) Simulation of the time-dependant thermal behaviour using standard CAD software; (iii) Simulation of a thermally optimized design. This was compared quantitatively with the original design and was also used for verification of sufficient increase in heat dissipation; (iv) Experimental realisation and verification of the optimized design. It could be shown that the optimized prototype shows significantly improved thermal behaviour in accordance with the predictions from the simulations. The new LiDAR sensor shows lower heat generation and optimized dissipation of thermal energy which proofs the applicability of the approach to complex sensors.
The aim of the paper is to present the simulation of the sweeping process based on a mathematical model that includes the drag force, the lift force, the sideway force, and the gravity. At the beginning, it is presented a short history of the street sweepers, some considerations about the sweeping process and the parameters of the sweeping process. Considering the developed model, in Matlab there is done some simulation for the trajectory of a spherical pebble. The obtained results are presented in graphical shape.
Due to the rising need for palliative care in Russia, it is crucial to provide timely and high-quality solutions for patients, relatives, and caregivers. A methodology for remote monitoring of patients in need of palliative care and the requirements will be developed for a hardware-software complex for remote monitoring of patients' health at home.
The Role of Support-Activities for the successful Implementation of Internal Corporate Accelerators
(2018)
The digital twin concept has been widely known for asset monitoring in the industry for a long time. A clear example is the automotive industry. Recently, there has also been significant interest in the application of digital twins in healthcare, especially in genomics in what is known as precision medicine. This work focuses on another medical speciality where digital twins can be applied, sleep medicine. However, there is still great controversy about the fundamentals that constitute digital twins, such as what this concept is based on and how it can be included in healthcare effectively and sustainably. This article reviews digital twins and their role so far in what is known as personalized medicine. In addition, a series of steps will be exposed for a possible implementation of a digital twin for a patient suffering from sleep disorders. For this, artificial intelligence techniques, clinical data management, and possible solutions for explaining the results derived from artificial intelligence models will be addressed.
Digitization extends to all areas of people's lives and processes, including public administration and government technology (GovTech for short). However, there are various problems here, such as the inappropriate development of new application systems, that are to be solved efficiently by combining two aspects: methodical digitization according to the process-driven approach and the idea of an app store for processes. This simultaneously fuels a process competition to advance methodical process digitization in the EU. Furthermore, this study explains the target-oriented use of this “firing” within the EU and concludes with a proposal of a new 3-schema architecture standard for successful process digitization within the EU.
Shadow information technology systems (SITS) coexist with formal enterprise systems in organisations. SITS pose risks but also increase flexibility of business units. Practice shows that SITS emerge, despite that Enterprise Architecture Management (EAM) aims at controling all IT systems in an organization. Studies acknowledge this problem in general. However, they neither show the specific influencing areas of SITS nor provide approaches to address them. To close this gap, we use a literature review to analyse examples of practical SITS and their interference with EAM concerns. Thus, we find that they hinder especially transparency, reduction of EA complexity and governance. Research has focused on achieving transparency, governing the evolution of the EA but lacks strategies for reducing complexity. This study contributes to research and practice by uncovering the main influencing areas of SITS on EAM, as well as by laying a foundation for future research on this topic.
This paper examines the corporate organisational aspects of the implementation of Industry 4.0. Industry 4.0 builds on new technologies and appears as a disruptive innovation to manufacturing firms. Although we do have a good understanding of the technical components, the implementation of the management and organisational aspects of Industry 4.0 is under-researched. It is challenging to find qualitative empirical evidence which provides comprehensive insights about real implementation cases. Based on a case study in a German high value manufacturing firm, we explore the corporate organisation and implementation of Industry 4.0. By using the framework of Complex Adaptive System (CAS), we have identified three key factors which facilitate the implementation of Industry 4.0 namely 1.) Organisational structure changes such as the foundation of a central department for digital transformation, 2.) The election of a Chief Digital Officer as a personnel change, and 3.) Corporate opening up towards cooperating with partners as a cultural change. We have furthermore found that Lean Management is an important enabler that ensures readiness for the adoption of Industry 4.0.
Business coaching is believed to effectively improve survival and success chances of new technology-based firms (NTBFs). However, not much empirical evidence on the support measure's effectiveness is available. Therefore, a pragmatic two-armed Randomized Controlled Trial (RCT) to test the effect of tactical business coaching on NTBF survival capabilities was designed and, for the most part, carried out. However, due to a lower than expected sample size and great attrition between groups, the RCT reveals deviations from the trial design that impede a thorough data assessment. Based on the data given, a first data analysis does not reveal significant differences in survival capability between the two groups. Thus, to provide guidance for future RCTs in business contexts, lessons learned about how to deal with trickle samples and experiment constellations with third parties carrying out the intervention are drawn.
The corporate entrepreneur
(2016)
Corporate entrepreneurship is one tool for established companies to strengthen their capabilities for strategic renewal and innovativeness. The question, however, which factors are influencing the success of a corporate entrepreneurship initiative requires further attention. The corporate entrepreneur who is acting as both the leader of embedded entrepreneurial teams and linking pin to the corporate, is providing one possible perspective. Based on 6 interviews conducted in 6 German organizations this study contributes to the understanding of the role of the corporate entrepreneur and how this role can be distinguished from other roles in the context of innovation.
In order to support entrepreneurs in the Business Model Innovation (BMI) process, practice-oriented frameworks such as the St. Gallen Business Model NavigatorTM (BMN) are considered to be a powerful tool. The aim of this paper is to identify strengths and limitations of the BMN when applied to start-ups in their early stages and to contribute to the optimization of the BMN in terms of applicability for start-ups. Furthermore, the paper aims to emphasize the importance of BMI for start-ups and the relevance of a supporting framework as well as formulating a unified catalogue of requirements of BMI frameworks for start-ups.
At the University of Applied Sciences Konstanz, Germany, a modern electronically controlled dynamometer and several cars are available for tests. Numerous studies have been carried out, and the latest results will be presented. The paper is intended to explain different tests under load. One focus is the driving cycle WLTC (Worldwide harmonized Light vehicles Test Cycle) and the requirements for the proper conduct of investigation with this driving cycle. Two and three wheelers have a great importance for mobility in various Asian countries. But also in other countries, this segment is very important for the so-called First or Last Mile Vehicles. Because of this, a short explanation of the driving cycle WMTC (Worldwide harmonized Motorcycle Emissions Certification/Test Procedure) is given. The various possibilities for the operation of the dynamometer and for carrying out various experiments are shown.
Other important figures that can be determined on a dynamometer are the wheel power, the power losses and eventually the engine performance. With the brake specific torque, the traction force at the propelled wheels, the maximum acceleration or maximum gradeability of a car can be determined.
As well the slippage related to load can be measured on the dynamometer. The dynamic wheel radius of the driven wheels has a significant influence on the slippage. Because of the temperature increase of the tires during the tests the tire pressure increases. A rise of tire temperature, tire pressure, and wheel speed results in an increase of the dynamic wheel radius and slippage. Equations for the determination of the dynamic wheel radius are presented.
As fish farming is becoming more and more important worldwide, this ongoing project aims at the simulation and test-based analysis of highly stressed wire contacts, as they are found in off-shore fish farm cages in order to make them more reliable. The quasi-static tensile test of a wire mesh provides data for the construction of a finite element model to get a better understanding of the behavior of high-strength stainless steel from which the cages are made. Fatigue tests provide new insights that are used for an adjustment of the finite element model in order to predict the probability of possible damage caused by heavy mechanical loads (waves, storms, predators (sharks)).
Autism spectrum disorders (ASD) affect a large number of children both in the Russian Federation and in Germany. Early diagnosis is key for these children, because the sooner parents notice such disorders in a child and the rehabilitation and treatment program starts, the higher the likelihood of his social adaptation. The difficulties in raising such a child lie in the complexity of his learning outside of children's groups and the complexity of his medical care. In this regard, the development of digital applications that facilitate medical care and education of such children at home is important and relevant. The purpose of the project is to improve the availability and quality of healthcare and social adaptation at home of children with ASD through the use of digital technologies.
Targetless Lidar-camera registration is a repeating task in many computer vision and robotics applications and requires computing the extrinsic pose of a point cloud with respect to a camera or vice-versa. Existing methods based on learning or optimization lack either generalization capabilities or accuracy. Here, we propose a combination of pre-training and optimization using a neural network-based mutual information estimation technique (MINE [1]). This construction allows back-propagating the gradient to the calibration parameters and enables stochastic gradient descent. To ensure orthogonality constraints with respect to the rotation matrix we incorporate Lie-group techniques. Furthermore, instead of optimizing on entire images, we operate on local patches that are extracted from the temporally synchronized projected Lidar points and camera frames. Our experiments show that this technique not only improves over existing techniques in terms of accuracy, but also shows considerable generalization capabilities towards new Lidar-camera configurations.
Small vessels or unmanned surface vehicles only have a limited amount of space and energy available. If these vessels require an active sensing collision avoidance system it is often not possible to mount large sensor systems like X-Band radars. Thus, in this paper an energy efficient automotive radar and a laser range sensor are evaluated for tracking surrounding vessels. For these targets, those type of sensors typically generate more than one detection per scan. Therefore, an extended target tracking problem has to be solved to estimate state end extension of the vessels. In this paper, an extended version of the probabilistic data association filter that uses random matrices is applied. The performance of the tracking system using either radar or laser range data is demonstrated in real experiments.