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Alternatywny system nawigacji oparty na przetwarzaniu zobrazowania oraz fuzji danych z czujników inercyjnych

100%

Komorniczak W. , Zych C. , Kawalec A. , Wrońska-Zych A.

2010

tom Vol. 51, nr 10

61-63

W artykule przedstawiono jeden ze sposobów wykorzystania czujników inercyjnych oraz przetwarzania obrazu do zbudowania systemu nawigacyjnego. W dzisiejszych czasach głównym sposobem określania położenia stało się wykorzystanie systemów satelitarnych np. GPS. Jednak ze względu na swoje wady, w aplikacjach wojskowych stawia się wymóg posiadania drugiego (niezależnego od nawigacji satelitarnej) systemu pozycjonowania. Taki alternatywny system wyznaczania pozycji można zbudować w oparciu o czujniki inercyjne, magnetometry, czujniki ciśnienia oraz przetwarzanie zobrazowania z kamery umieszczonej na poruszającym się obiekcie. Dzięki temu można uzyskać dokładną, lokalizację obiektu w miejscach gdzie nawigacja satelitarna nie może zostać użyta.

The paper describes a way to use inertial sensors and digital image signal processing to build a navigation system. Nowadays, the main way in determining the position is using satellite systems such as GPS. However, due to its drawbacks there is a requirement of a second (independent from satellite navigation) positioning system in military applications. Such an alternative system for determining the position can be built based on inertial sensors, magnetometers, pressure sensors and processing the image signal of the camera placed on a moving object. This allows you to get the exact location of the object in places where satellite navigation can not be used.

Zastosowanie metod fuzji danych w zarządzaniu zasobami radaru wielofunkcyjnego

100%

Komorniczak W. , Kawalec A. , Pietrasiński J.

tom Vol. 55, nr 1

55-75

W referacie poruszono tematykę związaną z zarządzaniem zasobami radaru wielofunkcyjnego. Jako jeden z elementów tego procesu wyróżniono priorytetyzację (rangowanie) zadań realizowanych przez radar. Rangowanie jest wymuszone przez potencjalnie niedostateczne zasoby wymagane do realizacji wszystkich zadań radaru, stąd konieczność szeregowania obsługiwanych przezeń obiektów zgodnie z ich istotnością. W referacie scharakteryzowano dane źródłowe zasilające proces rangowania oraz przedstawiono algorytmy przetwarzania tych danych. Zaprezentowane algorytmy oparto na wybranych metodach fuzji danych. Przedstawiono przebieg i wyniki badań procesu rangowania oraz wyniki badań wpływu zastosowania rangowania na niektóre parametry zarządzania zasobami radaru wielofunkcyjnego.

The paper deals with the problem of the multifunction radar resources management (RRM). The objectives of RRM are: optimal (from the radar performance point of view) resources allocation and the device operation control. As a result of RRM, it is expected a matrix containing information for the execution systems: " what, when, and how to do. The main constraints to deal with in the radar work are: time and energy limitations. If it is enough resource to execute all the tasks, the tasks execution is feasible. But in real situation one should not expect such a comfort. Typically neither time nor energy is enough and the questions arises what to do in these circumstances. It is obvious that only selected tasks can be executed, the RRM should answer which of them and in what order. To answer these questions, the structure of the RRM was proposed. First of all it is necessary to rank the tasks in order of their priorities, then to select the most important of them and schedule their execution. RRM is decomposed into two sub-problems, e.g.: ranking and task scheduling. The ranking belongs to the identification problems class, while the scheduling can be treated as an optimization task. The paper presents the data fusion approach to the task ranking. There are numerous examples of utilization of the data fusion tools in order to solve the identification problems. The conclusions from these examples can be following: the neural networks which have the ability to learn from the presented examples have also disadvantage of impossibility of extraction of the gathered knowledge. The internal processes of reasoning are neither well described nor studied, so they are not a good tool for military application, which the multifunction radar is. Fuzzy logic systems (based on the fuzzy sets theory and fuzzy logic) have the advantage of good and clear knowledge representation and ability to relatively easy implementation of the expert knowledge. The good side of the fuzzy systems is their possibility of maintaining and fusion of the imperfect knowledge. The disadvantage is the lack of ability to learn whole the knowledge from the examples. Some hybrid solutions are necessary. Four solutions are presented in the paper: neural, fuzzy, fuzzy — neural and probabilistic — fuzzy. In order to implement data fusion tools, the base test platform was designed and implemented. In fact, the test platform is a complex process of multifunction radar resources management, as well as it deals with the task scheduling problem. In order to evaluate the algorithms presented in the paper, some factors of radar work performance were defined. Presented ranking algorithms have capability of learning with use of the registered data learning set. Algorithms with their knowledge bases were tested and compared. The conclusion is following: the use of ranking process gives approximately two times better performance in task removal/delay aspect. On the other hand, the quality of algorithm (its accuracy) has lower influence on the final result. It means that for the use in radar application the algorithm with the best convergence during learning process and stability should be recommended. It is also important that the algorithm should have clear knowledge representation. These requirements meet two of the presented algorithms: neural - fuzzy and probabilistic - fuzzy. The first one was used against the positional data, the second one gave the best results for identification data. It is important, that overall performance of the presented RRM and ranking algorithms was tested with the use of real registered data, what makes it very interesting from the application point of view.