Temat: radar network - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: 24 GHz radar sensors for automotive applications
Autorzy:: Klotz, M.
Rohling, H.
Powiązania:: https://bibliotekanauki.pl/articles/309076.pdf
Data publikacji:: 2001
Wydawca:: Instytut Łączności - Państwowy Instytut Badawczy
Tematy:: automotive radar
radar network
radar sensors
Opis:: Automotive radar systems using integrated 24 GHz radar sensor techniques are currently under development [1]. This paper describes a radar network consisting of four sensors distributed behind the front bumper of an experimental car. Each single sensor measures the target range with high accuracy. A multilateration technique is used in the radar network for precise azimuth angle estimation even in multiple-target situations. The system performance is shown in real traffic situations for parking aid, stop & go and blind spot applications.
Źródło:: Journal of Telecommunications and Information Technology; 2001, 4; 11-14
1509-4553
1899-8852
Pojawia się w:: Journal of Telecommunications and Information Technology
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: Comparison of passive and active radar systems
Autorzy:: Žáčik, N.
Novák, A.
Powiązania:: https://bibliotekanauki.pl/articles/253633.pdf
Data publikacji:: 2015
Wydawca:: Instytut Naukowo-Wydawniczy TTS
Tematy:: tracking system
passive radar system
active radar system
radar network
pasywny system radarowy
aktywny system radarowy
sieć radarowa
Opis:: This article presents the conclusion from my two theses, Comparison of tracking systems and Tracking systems. In the first part with title Comparison of tracking system, was my work focused to research of primary and secondary radar technology with very detailed description and principle of their use. This part of my research consists also from comparison of those two different types of technologies, their advantages and disadvantages. This research was the base stone for my second part of thesis with title: Tracking systems and conclusions, summarized in this article. The second part of thesis is more focused to civil and army passive radar and meteorological technology. The main topic is: how to build up the new radar network by using passive radar technology and what are the advantages and disadvantages of this concept, in comparison with actual primary and secondary radar network. I have chosen Slovak Republic for new network planning but this theory and research is applicable for all the other countries, with some minor changes. This topic is focused mainly to advantages of passive surveillance system and multilateration.
Źródło:: TTS Technika Transportu Szynowego; 2015, 12; 1709-1712, CD
1232-3829
2543-5728
Pojawia się w:: TTS Technika Transportu Szynowego
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 3.

Tytuł:: Improvement in accuracy of determining a vessel’s position with the use of neural networks ana robust M-estimation
Autorzy:: Czaplewski, K.
Wąż, M.
Powiązania:: https://bibliotekanauki.pl/articles/259852.pdf
Data publikacji:: 2017
Wydawca:: Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
Tematy:: navigation
neural network
radar
M-estimation
Opis:: In the 21st century marine navigation has become dominated by satellite positioning systems and automated navigational processes. Today, global navigation satellite systems (GNSS) play a central role in the process of carrying out basic navigational tasks, e.g. determining the coordinates of a vessel’s position at sea. Since satellite systems are being used increasingly more often in everyday life, the signals they send are becoming more and more prone to jamming. Therefore there is a need to search for other positioning systems and methods that would be as accurate and fast as the existing satellite systems. On the other hand, the automation process makes it possible to conduct navigational tasks more quickly. Due to the development of this technology, all kinds of navigation equipment can be used in the process of automating navigation. This also applies to marine radars, which are characterised by a relatively high accuracy that allows them to replace satellite systems in performing classic navigational tasks. By employing M-estimation methods that are used in geodesy as well as simple neural networks, a software package can be created that will aid in automating navigation and will provide highly accurate information about a given object’s position at sea by making use of radar in comparative navigation. This paper presents proposals for automating the process of determining a vessel’s position at sea by using comparative navigation methods that are based on simple neural networks and geodetic M-estimation methods.
Źródło:: Polish Maritime Research; 2017, 1; 22-31
1233-2585
Pojawia się w:: Polish Maritime Research
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 4.

Tytuł:: Neural networks as a tool for georadar data processing
Autorzy:: Szymczyk, P.
Tomecka-Suchoń, S.
Szymczyk, M.
Powiązania:: https://bibliotekanauki.pl/articles/330009.pdf
Data publikacji:: 2015
Wydawca:: Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:: neural network
artificial neural network
ground penetrating radar
geological structure
sinkhole
sieć neuronowa
sztuczna sieć neuronowa
georadar
penetracja gruntu
budowa geologiczna
zapadlisko górnicze
Opis:: In this article a new neural network based method for automatic classification of ground penetrating radar (GPR) traces is proposed. The presented approach is based on a new representation of GPR signals by polynomials approximation. The coefficients of the polynomial (the feature vector) are neural network inputs for automatic classification of a special kind of geologic structure—a sinkhole. The analysis and results show that the classifier can effectively distinguish sinkholes from other geologic structures.
Źródło:: International Journal of Applied Mathematics and Computer Science; 2015, 25, 4; 955-960
1641-876X
2083-8492
Pojawia się w:: International Journal of Applied Mathematics and Computer Science
Dostawca treści:: Biblioteka Nauki

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