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.

A multiphase transformer rectifier unit

Abstract: The object of the present invention is to provide an inventive multiphase transformer rectifier unit (1) for converting a three-phase (R, S, T) alternating current (AC) supplied from a power distribution system (2) to direct current (DC) supplied to at least one load (3). The multiphase transformer rectifier unit (1) comprises a magnetic core (5) having a primary winding set (17) and secondary winding set (18), and a rectifier circuit (22). The secondary winding set (18) is arranged to generate N substantially equally distributed output phases, wherein N is an odd number multiple of 3, and N > 3, and the primary winding set (17) is arranged to provide a positive or negative phase shift equal substantially to 360/(8x N) degrees of said output phases. By connecting two such multiphase transformer rectifier units (1) to the three- phase power distribution system, one thereof with changed order of connection of the input phases, the number of output pulses from the combination of two multiphase transformer rectifier units (1) will appear as doubled compared with a single inventive multiphase transformer rectifier unit (1) due to interleaved pulses from the two multiphase transformer rectifier units (1), thus reducing current distortion. It is also the object of the present invention to provide a corresponding inventive method of an arrangement of two inventive multiphase transformer rectifier units (1) for reducing current distortion in the power distribution system (2).

Shielding effectiveness of energy saving windows and HPM effects on coated window panes: Measurements conducted 2014–2016 — Results and lessons learned

Abstract: The past few decades have shown a veritable explosion of new versions of energy-saving windows and coated window panes. In the wake of this, problems with radio communications into and from within buildings has arisen. However, this unexpected attenuation of radio signals may also be used to shield a facility from incoming intentional electromagnetic interference (IEMI). With the intention to investigate the shielding effectiveness (SE) of modern windows and window panes a two-year measurement campaign was launched mid-2014. Another, little investigated area is what happens to coated glass when irradiated by a high-power microwave (HPM) source. Shielding effectiveness has been measured for different types of energy saving windows and coated window panes both in a semi-anechoic chamber and in a reverberation chamber over the frequency range 1-18 GHz. The effects of HPM irradiation were studied by comparing SE measured before and after the pulsed 28 kV/m L-band irradiation. The main conclusion is that with the right choice of window the shielding effectiveness of a building can reach up 40-50 dB. In this paper we summarize these measurements and lessons learned from the measurement campaign.

Two-filter Gaussian mixture smoothing with posterior pruning

Abstract: In this paper, we address the problem of smoothing on Gaussian mixture (GM) posterior densities using the two-filter smoothing (TFS) strategy. The structure of the likelihoods in the backward filter of the TFS is analysed in detail. These likelihoods look similar to GMs, but are not proper density functions in the state-space since they may have constant value in a subspace of the state space. We present how the traditional GM reduction techniques can be extended to this kind of GMs. We also propose a posterior-based pruning strategy, where the filtering density can be used to make further approximations of the likelihood in the backward filter. Compared to the forward–backward smoothing (FBS) method based on N-scan pruning approximations, the proposed algorithm is shown to perform better in terms of track loss, normalized estimation error squared (NEES), computational complexity and root mean squared error (RMSE).