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1

Kooperacyjny monitoring widma bazujący na fuzji danych z wielu sensorów

Mazuro Maciej

Biuletyn Wojskowej Akademii Technicznej

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2023

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Vol. 72, nr 1

69--77

PL

Technologia rozwija się coraz szybciej w każdym obszarze naszego życia. Wszyscy mamy urządzenia elektroniczne, które emitują energię elektromagnetyczną. Promieniowanie sygnałów radiowych jest podstawowym elementem komunikacji bezprzewodowej, nawigacji satelitarnej bądź monitoringu w czasie rzeczywistym. Nowoczesne armie posiadają rozwiązania technologiczne oparte na technologiach bezprzewodowych, które poprawiają skuteczność działania, zwiększają świadomość sytuacyjną oraz pozwalają na szybsze podejmowanie decyzji, ale równocześnie w spektrum elektromagnetycznym wyposażenie korzystające z energii elektromagnetycznej można porównać do latarki - przeciwnik może zaobserwować „świecące” punkty na spektrogramach oraz zobrazowaniach w dziedzinie częstotliwości. Pozwala to na łatwe wykrycie oraz lokalizację celu, a następnie jego eliminację. Jest to domena, w której świetnie sprawdzają się techniki rozpoznania radioelektronicznego - rodzaj rozpoznania wojskowego, w którym spektrum elektromagnetyczne wykorzystywane jest do zdobywania informacji na temat przeciwnika. Jedna z metod to monitoring widma oparty na analizie odbieranych sygnałów radiowych. Obecnie coraz częściej twierdzi się, że informacja z jednego sensora to zbyt mało. Konieczne jest zbieranie produktów rozpoznawczych z wielu urządzeń, a następnie skuteczna fuzja danych. Algorytmy DF (ang. Data Fusion) pozwalają na kooperacyjny sensing widma elektromagnetycznego, co przekłada się na większe prawdopodobieństwo detekcji sygnału. Warto rozważyć wprowadzanie rozwiązań radia definiowanego programowo i bezzałogowych statków powietrznych, co pozwala na miniaturyzację systemów rozpoznawczych i zwiększenie zasięgu przez wykorzystanie platform latających. Implementacja systemów bezzałogowych oraz algorytmów sztucznej inteligencji, zdolnej do podejmowania szybkich i trafnych decyzji, pozwoli na uniknięcie strat ludzkich.

EN

The development of technology is progressing in every area of our lives. Each of us has an electronic device that emits electromagnetic energy. Radiation of radio signals is an essential element of wireless communication, satellite navigation or real-time monitoring. Modern armies have technological solutions based on wireless technologies that improve operational efficiency, increase situational awareness and allow us for faster decision making, but at the same time, in the electromagnetic spectrum, equipment using electromagnetic energy can be compared to a flashlight - the enemy can observe “glowing” points on the spectrograms and frequency domain images. This enables us to easy detect and localise the target and then to eliminate it. This is a domain where radio-electronic reconnaissance techniques work well - a type of military reconnaissance that uses the electromagnetic spectrum to gather information about the enemy. One of the methods is spectrum sensing, based on the analysis of received radio signals. Currently, there is a tendency in which information from one sensor is not enough. It is necessary to collect reconnaissance products from many devices, and then to make effective data fusion. DF (Data Fusion) algorithms allow us for cooperative sensing of the electromagnetic spectrum, which translates into a higher probability of signal detection. It is worth considering the introduction of software-defined radio and unmanned aerial vehicle solutions in order to miniaturise reconnaissance systems and to increase a range through the use of flying platforms. Implementations of unmanned systems and artificial intelligence algorithms, capable of making quick and accurate decisions will help to avoid human losses.

2

Waveform and resistivity data fusion imaging method based on the refection coefficient

Su Maoxin, Han Min, Xue Yiguo, Zhao Ying, Wang Peng, Li Guangkun

Acta Geophysica

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2023

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Vol. 71, no. 1

175--192

EN

To achieve comprehensive analyses, the presentation of comprehensive geophysical results usually involves the use of separate imaging and the combination of various results. At present, few studies have considered the correlation degree and unified imaging of different types of geophysical data. We establish a set of data fusion imaging methods for multiple geophysical data based on their refection coefficients. As geophysical exploration results are primarily provided through waveform and resistivity sections, waveform and resistivity data were selected for fusion and were converted into refection coefficients, and ground-penetrating radar (GPR) and surface electrical resistivity tomography (ERT) were taken as examples. Re-sampling and feature reconstruction were performed to unify the data in space and resolution. Finally, principal component analysis was used to calculate the correlation of the reconstructed refection coefficient and to perform data fusion; this led to unified imaging based on the refection coefficient of the considered geophysical data. Numerical simulation analyses and field experiments proved the efficacy of this method for producing unified imaging of multiple geophysical data. In summary, we provide a novel method for the unified interpretation of multiple geophysical data and enhance the identification ability of geological interfaces and anomaly distribution.

3

Regional ionospheric model response of geomagnetic storm during March 2015 using data fusion mechanism: GPS, COSMIC RO and SWARM

Emmela Suneetha, Ratnam Devanaboyina Venkata

Acta Geophysica

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2023

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Vol. 71, no. 1

553--566

EN

The total electron content (TEC) maps are chosen as the elementary structures to provide ionospheric corrections for improving the positional accuracy for Global Navigational Satellite Systems (GNSS) users. Availability of total electron content data from a multi-constellation of satellite systems and various ground-based instruments possess an ability to monitor, nowcast and forecast the behavior of the ionosphere region. Conversely, combining ionospheric TEC data from different temporal and spatial scales is a difficult task to augment either ground or space-based ionospheric model's accuracy. And hence, a method like data fusion is essential to illustrate the ionospheric variability and to improve the accuracy of ionospheric models under equatorial ionization anomaly (EIA) conditions. This paper presented the weighted least square data fusion method with multi-instrument TEC data to analyze the EIA TEC structures in the low-latitude Indian region. Both ground-based (GPS TEC from 26 stations in the Indian region) and space-based (FORMOSAT-3/COSMIC RO and SWARM mini satellite constellation) observations are used for the analysis. The spherical harmonic function (SHF) model of order 2, which gives nine SHF coefficients, is implemented. The analysis illustrates that the SHF coefficients followed by TEC data fusion would be useful to investigate the entry, occupancy and exit TEC structures of EIA during geomagnetic storm conditions.

4

Information fusion method of multichannel nanosensors based on neural network

Li Chaoke

Bulletin of the Polish Academy of Sciences. Technical Sciences

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2022

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Vol. 70, nr 2

art. no. e140258

EN

Information fusion approaches have been commonly used in multi sensor environments for the fusion and grouping of data from various sensors which is used further to draw a meaningful interpretation of the data. Traditional information fusion methods have limitations such as high time complexity of fusion processes and poor recall rate. In this work, a new multi-channel nano sensor information fusion method based on a neural network has been designed. By analyzing the principles of information fusion methods, the back propagation based neural network (BP-NN) is devised in this work. Based on the design of the relevant algorithm flow, information is collected, processed, and normalized. Then the algorithm is trained, and output is generated to achieve the fusion of information based on multi-channel nano sensor. Moreover, an error function is utilized to reduce the fusion error. The results of the present study show that compared with the conventional methods, the proposed method has quicker fusion (integration of relevant data) and has a higher recall rate. The results indicate that this method has higher efficiency and reliability. The proposed method can be applied in many applications to integrate the data for further analysis and interpretations.

5

Dynamic location models of mobile sensors for travel time estimation on a freeway

Sun Weiwei, Shen Liang, Shao Hu, Liu Pengjie

International Journal of Applied Mathematics and Computer Science

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2021

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Vol. 31, no. 2

271--287

EN

Travel time estimation for freeways has attracted much attention from researchers and traffic management departments. Because of various uncertain factors, travel time on a freeway is stochastic. To obtain travel time estimates for a freeway accurately, this paper proposes two traffic sensor location models that consider minimizing the error of travel time estimation and maximizing the collected traffic flow. First, a dynamic optimal location model of the mobile sensor is proposed under the assumption that there are no traffic sensors on a freeway. Next, a dynamic optimal combinatorial model of adding mobile sensors taking account of fixed sensors on a freeway is presented. It should be pointed out that the technology of data fusion will be adopted to tackle the collected data from multiple sensors in the second optimization model. Then, a simulated annealing algorithm is established to find the solutions of the proposed two optimization models. Numerical examples demonstrate that dynamic optimization of mobile sensor locations for the estimation of travel times on a freeway is more accurate than the conventional location model.

6

Data fusion in the decision-making process based on artificial neural networks

Dudczyk Janusz, Rybak Łukasz, Jezierski Zdzisław

Zeszyty Naukowe. Organizacja i Zarządzanie / Politechnika Śląska

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2020

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z. 149

97--108

EN

Purpose: The term data fusion is often used in various technologies, where a significant element is the ability of combining data of different typology coming from diverse sources. Currently, the issue of DF is developing towards interdisciplinary field and is connected with 'agile' data (information) synthesis concerning phenomena and objects. Optimal environment to carry out data fusion are SN (Sensor Networks), in which DF process is carried out on a data stage, most often automatically with the use of probable association algorithms of this data. The purpose of this article was an implementation of a neural network and its adaptation in the process of data fusion and solving the value prediction problem. Design/methodology/approach: The conducted experiment was concerned with modelling artificial neural network to form radiation beam of microstrip antenna. In the research the MATLAB environment was used. Findings: The conducted experiment shows that depending on the type of output data set and the task for ANN, the effect of neural network's learning is dependent on the activation function type. The described and implemented network for different activation functions learns effectively, predicts results as well as has the ability to generalize facts on the basis of the patterns learnt. Research limitations/implications: Without doubts, it is possible to improve the model of a network and provide better results than these presented in the paper through modifying the number of hidden layers, the number of neurons, learning step value or modifying the learning algorithm itself. Originality/value: The paper presents the implementation of the sensor network in the context of the process of data fusion and solution prediction. The paper should be read by persons which research interests are focused at the decision support by the information and communication technologies.

7

Mathematical methods of signal analysis applied in medical diagnostic

Ciecierski Konrad A.

International Journal of Applied Mathematics and Computer Science

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2020

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Vol. 30, no. 3

449--462

EN

Digital signal processing, such as filtering, information extraction, and fusion of various results, is currently an integral part of advanced medical therapies. It is especially important in neurosurgery during deep-brain stimulation procedures. In such procedures, the surgical target is accessed using special electrodes while not being directly visible. This requires very precise identification of brain structures in 3D space throughout the surgery. In the case of deep-brain stimulation surgery for Parkinson’s disease (PD), the target area—the subthalamic nucleus (STN)—is located deep within the brain. It is also very small (just a few millimetres across), which makes this procedure even more difficult. For this reason, various signals are acquired, filtered, and finally fused, to provide the neurosurgeon with the exact location of the target. These signals come from preoperative medical imaging (such as MRI and CT), and from recordings of brain activity carried out during surgery using special brain-implanted electrodes. Using the method described in this paper, it is possible to construct a decision-support system that, during surgery, analyses signals recorded within the patient’s brain and classifies them as recorded within the STN or not. The constructed classifier discriminates signals with a sensitivity of 0.97 and a specificity of 0.96. The described algorithm is currently used for deep-brain stimulation surgeries among PD patients.

8

Radar data fusion in the STRADAR system

Blok Marek, Kaczmarek Sylwester, Młynarczuk Magdalena

Scientific Journal of Polish Naval Academy

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2019

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R. 60 nr 3 (218)

43--56

EN

The main task of the Polish Border Guard is protection of the country’s border which requires utilization of multimedia surveillance systems automatically gathering, processing and sharing various data. The paper presents such a system developed for the Maritime Division of the Polish Border Guard within the STRADAR project and the problem of fusion of radar data in this system. The system, apart from providing communication means, gathers data from AIS, GPS and radar receivers: ARPA and SCANTER 2001. In the paper the concept of the radar data gathering in STRADAR system is provided with detailed presentation of radar servers, Radar INT modules and a reduplication (fusion) module and the proposition of the algorithm for radar data fusio.

PL

Głównym zadaniem polskiej Straży Granicznej jest ochrona granicy kraju, która wymaga wykorzystania multimedialnych systemów nadzoru umożliwiającychautomatyczne gromadzenie,przetwarzanie i udostępnianie różnego rodzaju danych. W artykule przedstawiono taki system opracowany dla Morskiego Oddziału Straży Granicznej w ramach projektu STRADAR oraz problem fuzji danych radarowych w tym systemie. System STRADAR, oprócz zapewnienia komunikacji pomiędzy elementami systemu, gromadzi i udostępniania dane z AIS, GPS i odbiorników radarowych: ARPA i SCANTER 2001. W artykule zaprezentowano koncepcjęgromadzenia danych adarowych w systemie STRADAR, przedstawiono serwery radarowe, moduł radar INT i moduł reduplikacjioraz zaproponowano algorytm fuzji danych radarowych.

9

Rozpoznawanie twarzy z wykorzystaniem technik głębokiego uczenia i fuzji danych obrazowych

Jakubowski Jacek, Chmielińska Jolanta

Przegląd Elektrotechniczny

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2019

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R. 95, nr 11

150--154

PL

W artykule przedstawiono wyniki oryginalnych badań nad zastosowaniem sieci neuronowej wykorzystującej techniki głębokiego uczenia w zadaniu identyfikacji tożsamości na podstawie obrazów twarzy zarejestrowanych w zakresie widzialnym i w podczerwieni. W badaniach użyte zostały obrazy twarzy eksponowanych w zmiennych ale kontrolowanych warunkach. Na podstawie uzyskanych wyników można stwierdzić, że oba badane zakresy spektralne dostarczają istotnych ale różnych informacji o tożsamości danej osoby, które się wzajemnie uzupełniają.

EN

The paper presents the results of the original research on the application of a neural network using deep learning techniques in the task of identity recognition on the basis of facial images acquired in both visual and thermal radiation ranges. In the research, the database containing images acquired in various but controlled conditions was used. On the basis of the obtained results it can be established that both investigated spectral ranges provide distinctive and complementary details about the identity of an examined person.

10

IoT sensing networks for gait velocity measurement

Chou Jyun-Jhe, Shih Chi-Sheng, Wang Wei-Dean, Huang Kuo-Chin

International Journal of Applied Mathematics and Computer Science

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2019

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Vol. 29, no. 2

245--259

EN

Gait velocity has been considered the sixth vital sign. It can be used not only to estimate the survival rate of the elderly, but also to predict the tendency of falling. Unfortunately, gait velocity is usually measured on a specially designed walk path, which has to be done at clinics or health institutes. Wearable tracking services using an accelerometer or an inertial measurement unit can measure the velocity for a certain time interval, but not all the time, due to the lack of a sustainable energy source. To tackle the shortcomings of wearable sensors, this work develops a framework to measure gait velocity using distributed tracking services deployed indoors. Two major challenges are tackled in this paper. The first is to minimize the sensing errors caused by thermal noise and overlapping sensing regions. The second is to minimize the data volume to be stored or transmitted. Given numerous errors caused by remote sensing, the framework takes into account the temporal and spatial relationship among tracking services to calibrate the services systematically. Consequently, gait velocity can be measured without wearable sensors and with higher accuracy. The developed method is built on top of WuKong, which is an intelligent IoT middleware, to enable location and temporal-aware data collection. In this work, we present an iterative method to reduce the data volume collected by thermal sensors. The evaluation results show that the file size is up to 25% of that of the JPEG format when the RMSE is limited to 0.5º.

11

Fusion of clinical data: A case study to predict the type of treatment of bone fractures

Haq Anam, Wilk Szymon, Abelló Alberto

International Journal of Applied Mathematics and Computer Science

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2019

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Vol. 29, no. 1

51--67

EN

A prominent characteristic of clinical data is their heterogeneity—such data include structured examination records and laboratory results, unstructured clinical notes, raw and tagged images, and genomic data. This heterogeneity poses a formidable challenge while constructing diagnostic and therapeutic decision models that are currently based on single modalities and are not able to use data in different formats and structures. This limitation may be addressed using data fusion methods. In this paper, we describe a case study where we aimed at developing data fusion models that resulted in various therapeutic decision models for predicting the type of treatment (surgical vs. non-surgical) for patients with bone fractures. We considered six different approaches to integrate clinical data: one fusion model based on combination of data (COD) and five models based on combination of interpretation (COI). Experimental results showed that the decision model constructed following COI fusion models is more accurate than decision models employing COD. Moreover, statistical analysis using the one-way ANOVA test revealed that there were two groups of constructed decision models, each containing the set of three different models. The results highlighted that the behavior of models within a group can be similar, although it may vary between different groups.

12

Fast multispectral deep fusion networks

Osin V., Cichocki A., Burnaev E.

Bulletin of the Polish Academy of Sciences. Technical Sciences

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2018

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Vol. 66, nr 6

875--889

EN

Most current state-of-the-art computer vision algorithms use images captured by cameras, which operate in the visible spectral range as input data. Thus, image recognition systems that build on top of those algorithms can not provide acceptable recognition quality in poor lighting conditions, e.g. during nighttime. Another significant limitation of such systems is high demand for computational resources, which makes them impossible to use on low-powered embedded systems without GPU support. This work attempts to create an algorithm for pattern recognition that will consolidate data from visible and infrared spectral ranges and allow near real-time performance on embedded systems with infrared and visible sensors. First, we analyze existing methods of combining data from different spectral ranges for object detection task. Based on the analysis, an architecture of a deep convolutional neural network is proposed for the fusion of multi-spectral data. This architecture is based on the single shot multi-box detection algorithm. Comparison analysis of the proposed architecture with previously proposed solutions for the multi-spectral object detection task shows comparable or better detection accuracy with previous algorithms and significant improvement of the running time on embedded systems. This study was conducted in collaboration with Philips Lighting Research Lab and solutions based on the proposed architecture will be used in image recognition systems for the next generation of intelligent lighting systems. Thus, the main scientific outcomes of this work include an algorithm for multi-spectral pattern recognition based on convolutional neural networks, as well as a modification of detection algorithms for working on embedded systems.

13

Integrated attitude and navigation system for small airplane

Topczewski S., Żugaj M., Narkiewicz J.

Journal of KONES

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2017

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Vol. 24, No. 1

339--348

EN

Navigation system is one of the most important aircraft systems. Accuracy and precision of position and attitude is extremely important for safe aircraft operations. The integrated INS/GNSS systems are commonly used as autonomous on-board devices for fulfilling this task. The INS sensors like accelerometers and gyroscopes are mainly affected by drift. The GNSS encounter stochastic disturbances with no tendency to grow in time but as each radio navigation system may be jammed or its signal can just be not available. These base properties of errors make these two systems well suited for integration. These were the main motivations for development of integrated navigation and attitude determination system, presented in this article. In the developed system, data is integrated from all available sensors, particularly INS, GPS, and air data computer. Navigation information from these sensors is combined using Kalman filtering algorithms to obtain robust solution, effective also in a case of failure/inaccessibility of GPS. Position calculated using the accelerations from INS is corrected by position from GPS and optionally by position calculated using the true airspeed (TAS) from ADC. Navigation system is modelled and programmed in MATLAB environment. The system was tested using the data from real experiments, proving efficiency of the method.

14

Integracja wyników badania aktywną termografią i techniką terahercową na potrzeby oceny defektów w materiałach kompozytowych

Łopato P., Szymanik B., Psuj G.

Przegląd Spawalnictwa

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2016

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R. 88, nr 10

97--103

PL

W niniejszym artykule prezentowana jest technika wykrywania i oceny wad w materiałach kompozytowych, bazująca na integracji aktywnej termografii i metody terahercowej. W badaniach eksperymentalnych została wykorzystana próbka wykonana z kompozytu szklanego z szeregiem nawierceń symulujących rzeczywiste wady. W związku z faktem, iż aktywna termografia i technika terahercowa są wrażliwe na zmiany różnych parametrów fizycznych materiału, połączenie wyników uzyskanych za pomocą obydwu metod pozwoli na otrzymanie możliwie pełnej informacji o badanej próbce.

EN

In this paper the technique of defects evaluation in composite materials based on a combination of active thermography method and terahertz technique is presented. The composite glass fiber sample with arifitial cirindlical defects having different depths was chosen for the tests. Active Infrared thermography with halogen lamps and terahertz technique are sensitive to changes in different physical parameters of the tested material. The combination of these techniques, performed by the data fusion of obtained measurements results allows to obtain the more complete on the detected material’s defect.

15

Badanie możliwości zastosowania dwusensorycznej fuzji danych w skanowaniu powierzchni po obróbce przyrostowej

Nieciąg H., Dudek P.

Przegląd Mechaniczny

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2016

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nr 12

45--48

PL

Skanowanie wyrobów kształtowanych w technologii przyrostowej na bazie materiałów polimerowych wymaga odtworzenia pełnej geometrii z zachowaniem tekstury i kolorów. W artykule rozważono możliwość zastosowania fuzji danych pozwalającej na łączenie informacji pochodzącej z dwóch przyrządów pomiarowych, różniących się charakterystyką metrologiczną, właściwościami i specyfiką pracy. Przedstawiono fragment badań mających na celu ocenę wpływu wybranych czynników zewnętrznych kształtujących warunki pracy konkretnych modeli skanerów na jakość otrzymanych wyników. Wnioski z przeprowadzonych badań będą mogły być uwzględnione podczas dokonywania pomiarów tymi przyrządami, w celu wypracowania odpowiednio korzystnych wyników fuzji.

EN

Scanning the parts manufactured additive technique based on polymer materials requires to recreate the full geometry while maintaining the texture and colors. In the article analyzed the possibility of using data fusion technology that allows to combine Information coming from two measuring Instruments with metrological different characteristics, different properties, as well different specification of working. The authors show a part of research on the influence of some external factors forming the working conditions of concrete scanner models on the quality of their results. It is assumed that the conclusions of this study can be taken into account while measuring of these Instruments, In order to develop the favorable results of the data fusion.

16

A Navigation and Control System for a Mobile Robot for Patrolling Buildings

Głębocki R., Kicman P., Kopyt A.

Problemy Mechatroniki : uzbrojenie, lotnictwo, inżynieria bezpieczeństwa

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2016

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Vol. 7, Nr 3 (25)

35--45

EN

This paper presents the work completed under a research project titled „Design of a mobile platform for the support of forensic testing of scenes with potential CBRN hazards”. The study focuses on operation of the mobile platform control algorithm, determination of the mobile platform position and preparation of the mobile platform system for integration with a video navigation system. The sensors installed on the mobile platform are intended as emergency backup systems in the event of loss of communication between the platform and its operator. The results of the test drive sessions completed to verify the control algorithm performance are also given.

PL

Artykuł prezentuje prace wykonane w ramach projektu badawczego „Zaprojektowanie mobilnej platformy do wsparcia badań kryminalistycznych miejsc zdarzeń, w których może występować zagrożenie CBRN”. W artykule przedstawiono sposób działania algorytmu sterowania platformą, wyznaczania pozycji oraz przygotowanie systemu do integracji z nawigacją wizyjną. Czujniki, jakie zostały zamontowane na platformie, mają służyć za systemy awaryjne w razie utraty łączności pomiędzy platformą a operatorem. W artykule przedstawione zostały wyniki z przejazdów próbnych weryfikujących działanie algorytmu.

17

RGB-DD: metody łączenia obrazów głębi oraz intensywości przez interpolację i fuzję danych w zadaniu SLAM

Walas K., Nowicki M., Skrzypczyński P.

Prace Naukowe Politechniki Warszawskiej. Elektronika

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2016

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z. 195, t. 2

417--426

PL

Praca dotyczy zagadnienia identyfikacji danych głębi z danymi intensywności w zastosowaniu do zadania jednoczesnej samolokalizacji i budowy mapy otoczenia (ang. Simultaneous Localization and Mapping – SLAM). Integracja danych przeprowadzona została dla czujnika głębi o rozdzielczości obrazu znacząco mniejszej od rozdzielczości obrazu RGB. W artykule sprawdzono dwie metody zwiększania rozdzielczości. Jedna z nich wykorzystuje interpolację biliniową obrazu głębi podczas jego przeskalowywania, a druga opiera się na fuzji danych głębi oraz intensywności. Przetestowano jakość działanie obu metod podwyższania rozdzielczości w zadaniu SLAM. Porównanie podejść nastąpiło na podstawie eksperymentu, w którym zebrano dane z dwóch czujników głębi wraz z kamerą RGB oraz zarejestrowano trajektorię przemieszczenia czujników.

EN

In this paper the method of combining depth data with intensity images in the Simultaneous Localization and Mapping (SLAM) task is described. Data integration was performed for the depth sensor with substantially lower resolution than the RGB image. In this paper two methods of upsampling were tested. First one is using pure interpolation during upsampling, and the second one is based on data fusion guided by RGB image. The quality of selected methods was examined in a SLAM task. The comparison of these two methods was done experimentally, where data from depth and RGB sensors were gathered and the trajectory of the sensor movement was recorded.

18

SLAM aided Inertial Navigation System

Naus K., Marchel Ł.

Zeszyty Naukowe Akademii Marynarki Wojennej

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2015

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R. 56 nr 1 (200)

15--28

EN

The interdisciplinary nature of navigation leads us to drawing on knowledge contained in solutions used in related technical fields. An example of this trend is combining it with elements of robotics, in which SLAM (Simultaneous Localization And Mapping) is commonly used for positioning a vehicle. To calculate position changes, the location of characteristic objects on a continuously updated map of an environment is used. The attractiveness of the implementation of this technology in connection with marine navigational aids, stems from the possibility of enhancing positioning accuracy in harbor, off-shore or narrow areas. That is in the areas where there is a built up hydro-technical infrastructure, such as breakwaters, waterfronts or navigational infrastructure in the form of marked water fairways and anchorages. In this article an analysis of SLAM combined with INS (Inertial Navigation System) is carried out. It focuses on the possibilities of enhancing accuracy in fixing position coordinates for a submarine. The first part of the article presents a mathematical base for combining INS and SLAM using the Extended Kalman Filter. The second part describes a study on the accuracy in positioning a mobile robot (in this instance a wheeled vehicle) which employs a navigation system based on INS and INS aided SLAM. The final part of the article includes the results of the study and their analysis. It also contains generalized conclusions indicating advantages and disadvantages of the proposed solution.

PL

Interdyscyplinarność nawigacji skłania do czerpania wiedzy z rozwiązań stosowanych w pokrewnych dziedzinach nauk technicznych. Przykładem jest połączenie z elementami robotyki, w której do pozycjonowania pojazdu powszechnie wykorzystywana jest technika SLAM (Simultaneous Localization And Mapping). Polega ona na pozycjonowaniu pojazdu na podstawie zmian położenia obiektów charakterystycznych znajdujących się na stale aktualizowanej mapie otoczenia. Implementacja tej technologii w połączeniu z morskimi urządzeniami nawigacyjnymi zwiększa dokładność pozycjonowania w obszarach portowych, przybrzeżnych lub ścieśnionych, gdzie istnieje rozbudowana infrastruktura hydrotechniczna, np. falochrony, nabrzeża, oraz infrastruktura nawigacyjna w postaci oznakowanych torów wodnych i kotwicowisk. W artykule przeprowadzono analizę technologii SLAM w połączeniu z INS (Inertial Navigation System) pod kątem możliwości zwiększenia dokładności wypracowywania współrzędnych pozycji na okręcie podwodnym. W pierwszej części przedstawiono podstawę matematyczną zespolenia INS ze SLAM przy użyciu rozszerzonego filtru Kalmana (Extended Kalman Filter), w drugiej opisano badanie dokładności pozycjonowania robota mobilnego (pojazdu kołowego) wykorzystującego system nawigacyjny oparty na INS i INS wspomagany SLAM, na zakończenie przedstawiono wyniki badania oraz ich analizę, a także uogólnione wnioski ukazujące zalety i wady zaproponowanego rozwiązania.

19

Zastosowanie tanich czujników inercyjnych w układzie regulacji kąta pochylenia pojazdu balansującego

Chudzik S.

Przegląd Elektrotechniczny

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2015

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R. 91, nr 6

177-180

PL

W pracy przedstawiono wyniki badań związanych z możliwością wykorzystania niskokosztowych sensorów inercyjnych w układzie stabilizacji pozycji pionowej oraz zadanego kierunku jazdy robota balansującego. Testowany układ sterowania zbudowano w oparciu o płytkę uruchomieniową mikrokontrolera serii STM32F3 z rdzeniem Cortex-M4 wyposażoną w trójosiowy akcelerometr, magnetometr i żyroskop. Do określenia dokładności estymacji kąta nachylenia, przeprowadzono testy porównawcze na stanowisku z enkoderem impulsowym.

EN

The paper presents results of research related to the potential use of low-cost sensors, inertial stabilization system vertical position and specified direction balancing robot. Tested control system was built based on the start up board microcontroller series STM32F3 Cortex-M4 equipped with a triaxial accelerometer, magnetometer and gyroscope. To determine the accuracy of the estimation of the angle of inclination, comparative tests were carried out on a bench with a pulse encoder.

20

ANN as justified granular computing mechanism for medical data classification

Bernas M.

Journal of Medical Informatics & Technologies

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2015

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Vol. 24

85--90

EN

The medical data and its classification have to be treated in particular way. The data should not be modified or altered, because this could lead to false decisions. Most state-of-the-art classifiers are using random factors to produce higher overall accuracy of diagnosis, however the stability of classification can vary significantly. Medical support systems should be trustworthy and reliable, therefore this paper proposes fusion of multiple classifiers based on artificial Neural Network (ANN). The structure selection of ANN is performed using granular paradigm, where granulation level is defined by ANN complexity. The classification results are merged using voting procedure. Accuracy of the proposed solution was compared with state-of-the-art classifiers using real medical data coming from two medical datasets. Finally, some remarks and further research directions have been discussed.