Swedish Defence Research Agency

About: Swedish Defence Research Agency is a government organization based out in Stockholm, Sweden. It is known for research contribution in the topics: Radar & Laser. The organization has 1413 authors who have published 2731 publications receiving 56083 citations. The organization is also known as: Totalförsvarets forskningsinstitut.

Bioconda: sustainable and comprehensive software distribution for the life sciences.

Abstract: We present Bioconda (https://bioconda.github.io), a distribution of bioinformatics software for the lightweight, multi-platform and language-agnostic package manager Conda. Currently, Bioconda offers a collection of over 3000 software packages, which is continuously maintained, updated, and extended by a growing global community of more than 200 contributors. Bioconda improves analysis reproducibility by allowing users to define isolated environments with defined software versions, all of which are easily installed and managed without administrative privileges.

Synthetic-aperture radar processing using fast factorized back-projection

Abstract: Exact synthetic aperture radar (SAR) inversion for a linear aperture may be obtained using fast transform techniques. Alternatively, back-projection integration in time domain can also be used. This technique has the benefit of handling a general aperture geometry. In the past, however, back-projection has seldom been used due to heavy computational burden. We show that the back-projection integral can be recursively partitioned and an effective algorithm constructed based on aperture factorization. By representing images in local polar coordinates it is shown that the number of operations is drastically reduced and can be made to approach that of fast transform algorithms. The algorithm is applied to data from the airborne ultra-wideband CARABAS SAR and shown to give a reduction in processing time of two to three orders of magnitude.

Zero-Velocity Detection—An Algorithm Evaluation

Abstract: In this paper, we investigate the problem of detecting-time epochs when zero-velocity updates can be applied in a foot-mounted inertial navigation (motion-tracking) system. We examine three commonly used detectors: the acceleration-moving variance detector, the acceleration-magnitude detector, and the angular rate energy detector. We demonstrate that all detectors can be derived within the same general likelihood ratio test (LRT) framework, given the different prior knowledge about the sensor signals. Further, by combining all prior knowledge, we derive a new LRT detector. Subsequently, we develop a methodology to evaluate the performance of the detectors. Employing the developed methodology, we evaluate the performance of the detectors using leveled ground, slow (approximately 3 km/h) and normal (approximately 5 km/h) gait data. The test results are presented in terms of detection versus false-alarm probability. Our preliminary results show that the new detector performs marginally better than the angular rate energy detector that outperforms both the acceleration-moving variance detector and the acceleration-magnitude detector.