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EN
This article presents the results of research on the sea bedding using a measuring set generating wide bandwidth. signals witli linearly modulated frequency - chirp signals. The measurements were conducted in the Gdansk Bay region at locations where geological cores had been drawn.
EN
Passive detection and localization of objects in the water environment is a desirable undertaking not only from the point of view of underwater defense technology but it is also associated with the military aspect of security, especially in respect to the protection of narrow passages. waterlines and ports. Observation of a specific region of the sea area, besides the technical means (hardware) that allow the data acquisition, requires also the application of a specific algorithm for the determination of ship's localization (software). This article presents the possibilities of ship's detection basing on the analysis of acoustic, magnetic, electric and pressure fields.
PL
Wykorzystanie systemu elektronicznej mapy w zautomatyzowanym systemie wspomagania dowodzenia rodzajem sił zbrojnych wymaga wypracowania i określenia dokładnych standardów wymiany danych zapewniających kompatybilność z innymi rodzajami sił. Wymusza to istnienie standardów umożliwiających interoperacyjność i niezakłócony przepływ danych. Artykuł w skrótowej formie przedstawia przegląd istniejących na świecie standardów wymiany danych stosowanych w systemach elektronicznej mapy będących zasadniczym elementem systemu wspomagania dowodzenia marynarką wojenną
EN
Using the electronic map in command and controll systems demand clear definition of standards for data exchange. Only this can assure full compatibility with other forces during national and international cooperation. The article shortly presents trends and standars used for digital geodetic data exchange for civilian and military aplications
4
Content available Dynamic normalization of hydroacoustic signals
100%
EN
Multidimensional analysis of hydroacoustic data is usually conducted by way of presentation of the signal information decomposed into dimensions of time and frequency using a short term Fourier transform inform of a spectrogram. Same shortfalls of such visual analysis come into place when studying a signal coming from a source changing its distance from the receiver set because of the variations in the signal strength. The proposed method suggests same ways of such normalization scheme that will diminish the influence of these variations by way multiplication of the spectra by a compensation function dependent of time.
EN
Artificial intelligence systems have been more and more used for the purposes of classification and identification. Recently, a lot of attention has been devoted to the exploration of such techniques in combination with the passive acoustic signals of vessels in the sea environment. Although some of the research imply optimistic results it seems necessary to apply the results of investigations regarding the sound propagation in the sea. This paper suggests was of improving the quality of neural classification by narrowing broadband frequency band to some specific narrow bands.
EN
An algorithm for detection/identification of underwater objects is proposed. The algorithm is based upon the classification ability of a simple multi-layer neural network, also called a Perceptron. A signal recorded by a hydrophone and preprocessed by a computer is supplied to the ANN, which classifies it according to the possessed information encoded within its structure and an array of weighs. Analysis of effectiveness is conducted depending on the variables pertaining to the neural network.
EN
The authors presented a technique for an optimal representation of acoustical signals for further object classification purposes using different statistical and neural methods. It is based on principal component analysis (PCA) which is a transformation of vectors localized in k-dimensional observation (feature) space into lower n-dimensional component space retaining majority of included information. The resulting improvement in classification efficiency by a chosen statistical classifier was verified by a numerical experiment.
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