Saab AB

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

Affordable Reconfigurable Tooling

Abstract: Since the early days of aircraft assembly, welded steel structures called Conventional Tooling has been used for positioning and holding parts in place during assembly. This paper presents a new tooling concept called Affordable Reconfigurable Tooling, where a robot is not only used for drilling and riveting but also for reconfiguring the tool itself. The concept consists of modular units that can either be reconfigured between products of the same family of assembly or rebuilt between product families. The research is part of an ongoing EU-founded aircraft industry project – ADFAST*.

Information fusion supporting team situation awareness for future fighting aircraft

Abstract: In the military aviation domain, the decision maker, i.e. the pilot, often has to process huge amounts of information in order to make correct decisions. This is further aggravated by factors such as time-pressure, high workload and the presence of uncertain information. A support system that aids the pilot to achieve his/her goals has long been considered vital for performance progress in military aviation. Research programs within the domain have studied such support systems, though focus has not been on team collaboration. Based on identified challenges of assessing team situation awareness we suggest an approach to future military aviation support systems based on information fusion. In contrast to most previous work in this area, focus is on supporting team situation awareness, including team threat evaluation. To deal with these challenges, we propose the development of a situational adapting system, which presents information and recommendations based on the current situation.

Using Deep Learning for Classifying Ship Trajectories

Abstract: In this paper we demonstrate how deep learning can be applied to the field of sea surveillance by classifying ship types from their trajectories. Commercial ships using AIS continually report information such as their ship type, e.g. fishing or cargo ship. A problem with AIS information however is that it can easily be modified and therefore deliberately or accidentally incorrect. In an attempt to address this we use a 1100 hours long AIS data set to teach 16 different neural networks to classify ships using only motion trajectories and without relying on the reported ship type. We also test three baseline methods using a more conventional1-nearest neighbor approach. The evaluation showed that the best performing classifier was the one based on deep learning.

Method for planning the velocity of a craft along a route

Abstract: A method for planning the velocity of a craft along a predetermined route, where said method comprises the step of transforming demands and limitations of said route and said craft into a time-distance domain. Said planning subsequently takes place in said domain. The method saves computational time.

Speedup and tracking accuracy evaluation of parallel particle filter algorithms implemented on a multicore architecture

Abstract: Four different parallel particle filters such as globally distributed particle filter (GDPF), resampling with proportional allocation filter (RPA), resampling with non-proportional allocation filter (RNA) and the Gaussian particle filter (GPF), are studied in terms of speedup and tracking accuracy in a bearings-only tracking problem. The filters are implemented on a shared memory multicore computer, where the speedup is measured using up to eight cores. The tracking accuracy is studied in a simulated BOT application where the GPF exhibits best tracking accuracy, and RNA, RPA and GDPF give tracking accuracy comparable to the sequential particle filter. Both GPF and RNA appear to be capable of achieving linear speedup in the number of cores used, while RPA shows somewhat less encouraging speedup and GDPF is found to have a speedup limited to about 3 times.