Saab AB

About: Saab AB is a company organization based out in Thun, Switzerland. It is known for research contribution in the topics: Signal & Antenna (radio). The organization has 862 authors who have published 928 publications receiving 8807 citations. The organization is also known as: Saab AB & Svenska Aeroplan AB.

Time Budget Management in Multifunction Radars Using Reinforcement Learning

Abstract: An adaptive revisit interval selection (RIS) in multifunction radars is an integral part of efficient time budget management (TBM). In this paper, the RIS problem is formulated as a Markov decision process (MDP) with unknown state transition probabilities and reward distributions. A reward function is proposed to minimize the tracking load (TL) while maintaining the track loss probability (TLP) at a tolerable level. The reinforcement learning (RL) problem is solved using the Q-learning algorithm with an epsilon-greedy policy. Compared to a baseline algorithm, the RL approach was capable of maintaining the tracks while reducing the tracking load significantly.

Method and arrangement for positioning of an object in a warehouse

Abstract: The present invention relates to an Object Identification and Tracking System (OITS) and a method in a OITS for associating an object identity with a position for an object in a warehouse, wherein the OITS comprises a number of pairs of video cameras, and the position of an object is determined on basis of images from said pairs of video cameras.

Low latency disturbance detection using distributed optical fiber sensors

Abstract: Distributed optical fiber sensors based on phase-sensitive optical time domain reflectometry (Φ-OTDR) are feasible options to detect perturbations in kilometric security perimeters or mechanical structures. This technique takes advantage of electromagnetic interference immunity, small dimensions, lightweight, flexibility, and capability. Moreover, this technique can be combined with dedicated hardware architectures, in order to improve its performance and reliability. This work proposes the use of parallel hardware architectures to implement real-time detecting and locating perturbations in a Φ-OTDR distributed optical fiber vibration sensor. Hardware architectures of the iterative moving average filter and the Sobel filter were mapped on field programmable gate arrays, exploring the intrinsic parallelism in order to achieve real-time requirements. A performance comparison between the proposed solutions was addressed in terms of hardware cost, latency and power consumption.

A method and arrangement for recording a media stream

Abstract: The present invention relates to the field of digital media recording such as video or audio, where compression is used to reduce the amount of data to save onto a data storage In particular the invention relates to recording media, wherein the memory area required to store the media is unknown The invention discloses a method for recording digital streamed media with a number of media frames in a memory by encoding each media frame into an encoded frame comprising a first number of sets of data, representing different characteristics of the media stream The invention further relates to detecting if the data storage is full and if the data storage is full, storing new frames in the data storage previously occupied by the data sets representing the least prioritized characteristics of the previously stored encoded frames The invention also relates to a corresponding media recorder and computer program

Rebalancing of underwater vehicles

Abstract: The present disclosure relates to a rebalancing device (100) for rebalancing of an underwater vehicle comprising at least one thruster and at least one storage space. The rebalancing device (100) comprises control circuitry (140). The control circuitry (140) is configured to receive sensor data comprising information relating to a depth and an attitude of the underwater vehicle, and thruster data comprising information relating to thrust and orientation of thrust of the at least one thruster. The control circuitry (140) is further configured to determine a difference between a centre of gravity, CoG, of the underwater vehicle and a centre of buoyancy, CoB, of the underwater vehicle based on the sensor data and the thruster data, and to determine a difference between a gravitational force acting on the underwater vehicle and a buoyancy of the underwater vehicle based on the sensor data and the thruster data. The control circuitry (140) is also configured to generate rebalancing information relating to a deviation of a current load distribution from an ideal load distribution based on the determined differences. The present disclosure also relates to corresponding underwater vehicles, methods and computer programs.