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.

Energy-Efficient Synthetic-Aperture Radar Processing on a Manycore Architecture

Abstract: The next generation radar systems have high performance demands on the signal processing chain. Examples include the advanced image creating sensor systems in which complex calculations are to be performed on huge sets of data in real time. Many core architectures are gaining attention as a means to overcome the computational requirements of the complex radar signal processing by exploiting massive parallelism inherent in the algorithms in an energy efficient manner. In this paper, we evaluate a many core architecture, namely a 16-core Epiphany processor, by implementing two significantly large case studies, viz. an auto focus criterion calculation and the fast factorized back-projection algorithm, both key components in modern synthetic aperture radar systems. The implementation results from the two case studies are compared on the basis of achieved performance and programmability. One of the Epiphany implementations demonstrates the usefulness of the architecture for the streaming based algorithm (the auto focus criterion calculation) by achieving a speedup of 8.9x over a sequential implementation on a state-of-the-art general-purpose processor of a later silicon technology generation and operating at a 2.7x higher clock speed. On the other case study, a highly memory-intensive algorithm (fast factorized back projection), the Epiphany architecture shows a speedup of 4.25x. For embedded signal processing, low power dissipation is equally important as computational performance. In our case studies, the Epiphany implementations of the two algorithms are, respectively, 78x and 38x more energy efficient.

System for determining the target range for a laser guided weapon

Abstract: A system for determining the distance between a target (4) and a laser guided weapon traveling towards the target (4). The system (1) comprises a laser designator (5) on a remote platform (2) for radiating a first train of pulses (l1) on a set wavelength in the direction of the target (4). In the weapon (3) a receiver (6) is arranged to receive and detect pulses on the set wavelength reflected from the target (4). There is also a direction sensing means in the weapon (3) for determining the direction of the target (4). A transmitter (7) is arranged in the weapon (3) to periodically transmit a second train of pulses (l2) on the set wavelength in the direction of the target (4). There are means in the receiver (6) to extract a reflection from the target (4) of the second train of pulses (l2). There are further timing means to determine the period of time from transmitting the second train of pulses (l2) to receiving the reflection from the target (4) of the second train of pulses (l2). Computing means (8) are arranged for determining a distance corresponding to said period of time.

Chapter 4 : Anomaly Detection

Abstract: This chapter presents an extension of conformal prediction for anomaly detection applications. It includes the presentation and discussion of the Conformal Anomaly Detector (CAD) and the computationally more efficient Inductive Conformal Anomaly Detector (ICAD), which are general algorithms for unsupervised or semi-supervised and offline or online anomaly detection. One of the key properties of CAD and ICAD is that the rate of detected anomalies is well calibrated in the online setting under the randomness assumption. Similar to conformal prediction, the choice of Nonconformity Measure (NCM) is of central importance for the classification performance of CAD and ICAD. A novel NCM for examples that are represented as sets of points is presented. One of the key properties of this NCM, which is known as the directed Hausdorff kk-nearest neighbors (DH-kNN) NCM, is that the p-value for an incomplete test example monotonically decreases as more data points are observed. An instance of CAD based on DH-kNN NCM, known as the sequential Hausdorff nearest neighbor conformal anomaly detector (SHNN-CAD), is presented and discussed for sequential anomaly detection applications. We also investigate classification performance results for the unsupervised online SHNN-CAD on a public dataset of labeled trajectories.

Error control in a traffic management system

Abstract: A system for monitoring a traffic management system, such as an Air Traffic Management (ATM) system, which includes a position retrieval station, operable to retrieve position information for a traffic object, eg a radar station devised to collect radar echoes and generate radar image signals A computer system is connected to the position retrieval station for generating radar trace data from received position information An operator station is connected to the computer system for processing trace data for presentation A false position information source is connected to provide artificial information corresponding to a predetermined property of a false traffic object to the computer system A comparator unit is connected to the operator station for receiving trace data generated from the artificial information, and devised to detect correlation between the generated trace data and the predetermined property of the false traffic object

A fluid actuator arrangement

Abstract: The present invention regards a fluid actuator arrangement comprising a first cylinder (3, 3') and a first piston body (5, 5') symmetrically arranged along a longitudinal axis (X), wherein the first cylinder (3, 3') exhibits a cylindrical inner peripheral surface (7), a first end (9, 10) and a second end (11, 12) forming a first cylinder interior (13); the first piston body (5, 5') comprises a first portion (21, 21') and second portion (23, 23') and a radially protruding portion (15) therebetween,the radially protruding portion (15) is slidingly arranged in the first cylinder interior (13) and protrudes outwardly towards the cylindrical inner peripheral surface (7) dividing the first cylinder interior (13) into a first cylinder chamber (17) and a second cylinder chamber (19) The first portion (21, 21')of the first piston body (5, 5´) sealingly extends through a first opening (25) of the first end (9) and the second portion (23, 23')of the first piston body (5, 5´) sealingly extends through a second opening (27) of the second end (11);and the first portion (21, 21') of the first piston body (5, 5') exhibits a larger diameter than the second portion (23, 23') of the first piston body (5, 5') and comprises an open cavity (29)