Saab Automobile AB

About: Saab Automobile AB is a based out in . It is known for research contribution in the topics: Radar & Antenna (radio). The organization has 760 authors who have published 890 publications receiving 11811 citations.

A Fiber-Optic Coupled Telescope for Water Vapor DIAL Receivers

Abstract: A fiber-optic coupled telescope of low complexity was constructed and tested. The major loss mechanisms of the optical system have been characterized. Light collected by the receiver mirror is focused onto an optical fiber, and the output of the fiber is filtered by an interference filter and then focused onto an APD detector. This system was used in lidar field measurements with a 532-nm Nd:YAG laser beam. The results were encouraging. A numerical model used for calculation of the expected return signal agreed with the lidar return signal obtained. The assembled system was easy to align and operate and weighed about 8 kg for a 30 cm (12") mirror system. This weight is low enough to allow mounting of the fiber-optic telescope receiver system in a UAV. Furthermore, the good agreement between the numerical lidar model and the performance of the actual receiver system, suggests that this model may be used for estimation of the performance of this and other lidar systems in the future. Such telescopes are relatively easy to construct and align. The fiber optic cable allows easy placement of the optical detector in any position. These telescope systems should find widespread use in aircraft and space home DIAL water vapor receiver systems.

Experience from Introducing Systems Engineering in an Academic Environment Using an Industry Training Course

Abstract: Training and educating Systems Engineers is a key activity for any organization developing complex heterogeneous systems. Ideally, the regional/national academic community will providecourses and e ...

Method and device for detecting and firing a pyrotechnic charge in a multiple-charge system.

Abstract: The invention relates to a device which, upon receipt of a firing order in the form of a firing impulse, locates and fires a pyrotechnic charge connected in one of a plurality of firing circuits (171 - 1730) in a firing unit. A current switching unit connects a current which is insufficient for firing a charge, to a firing circuit. After that, a current detecting unit checks whether or not a current is flowing in the firing circuit, i.e. whether or not a charge is connected. This is repeated by a logic unit (15) until a connected charge is located, whereupon a firing current is connected to the firing circuit comprising the connected charge, and the charge is fired. The logic unit (15) controlling this course of events is supplied, like the device in its entirety, with its supply voltage from the said voltage pulse.

Neural-Network-Based Classification of Commercial Ships From Multi-Influence Passive Signatures

Abstract: Monitoring the underwater environment is important for maritime security, marine conservation, and mine countermeasures With developments in computation and artificial intelligence, it is increasingly important to measure and classify underwater ship signatures In this work, we design an artificial neural network that classifies commercial ships based on their multi-influence signature In total, 103 ship passages were included in the considered data set, with signatures recorded as the ship crossed a line of passive underwater sensors The multi-influence signature was formed by feature-level sensor fusion of the hydroacoustic signature, the underwater electric potential, and the static and alternating magnetic signatures Ships were classified according to size, or type, as broadcast on the AIS With feature-level fusion, the neural network will optimize the relationship between different types of signatures, emphasizing features with greater predictive power At the same time, weak features, even if not independently adequate for classification, can add information that improves accuracy further The developed neural network achieved a classification accuracy of 874% when classifying according to size With augmented data to balance the classes, 850% classification accuracy was achieved when classifying according to ship type This is a large improvement on the found classification accuracy when using only hydroacoustic or electromagnetic signatures This article verifies the value of feature-level sensor fusion in classification, and provides guidance on classifier design depending on the exact ship classification task

Image presentation method for driver of road vehicle, involves displaying artificial image of object using infrared camera of radar device within inner frame

Abstract: An infrared camera or radar device is used for displaying an artificial image of object to driver of vehicle within the inner frame (12) from the field of vision of the outer frame (11). The displayed image is changed with respect to corresponding section of original image within the inner frame. An Independent claim is also included for image presentation device.