Joint Bayesian component separation and CMB power spectrum estimation

We describe and implement an exact, flexible, and computationally efficient algorithm for joint component separation and CMB power spectrum estimation, building on a Gibbs sampling framework. Two essential new features are 1) conditional sampling of foreground spectral parameters, and 2) joint sampling of all amplitude-type degrees of freedom (e.g., CMB, foreground pixel amplitudes, and global template amplitudes) given spectral parameters. Given a parametric model of the foreground signals, we estimate efficiently and accurately the exact joint foreground-CMB posterior distribution, and therefore all marginal distributions such as the CMB power spectrum or foreground spectral index posteriors. The main limitation of the current implementation is the requirement of identical beam responses at all frequencies, which restricts the analysis to the lowest resolution of a given experiment. We outline a future generalization to multi-resolution observations. To verify the method, we analyse simple models and compare the results to analytical predictions. We then analyze a realistic simulation with properties similar to the 3-yr WMAP data, downgraded to a common resolution of 3 degree FWHM. The results from the actual 3-yr WMAP temperature analysis are presented in a companion Letter.Comment: 23 pages, 16 figures; version accepted for publication in ApJ -- only minor changes, all clarifications. More information about the WMAP3 analysis available at http://www.astro.uio.no/~hke under the Research ta

FPGA-based implementation of the back-EMF symmetric-threshold-tracking sensorless commutation method for brushless DC-machines

The operation of brushless DC permanent-magnet machines requires information of the rotor position to steer the semiconductor switches of the power-supply module which is commonly referred to as Brushless Commutation. Different sensorless techniques have been proposed to estimate the rotor position using current and voltage measurements of the machine. Detection of the back-electromotive force (EMF) zero-crossing moments is one of the methods most used to achieve sensorless control by predicting the commutation moments. Most of the techniques based on this phenomenon have the inherit disadvantage of an indirect detection of commutation moments. This is the result of the commutation moment occurring 30 electrical degrees after the zero-crossing of the induced back-emf in the unexcited phase. Often, the time difference between the zero crossing of the back-emf and the optimal current commutation is assumed constant. This assumption can be valid for steady-state operation, however a varying time difference should be taken into account during transient operation of the BLDC machine. This uncertainty degrades the performance of the drive during transients. To overcome this problem which improves the performance while keeping the simplicity of the back-emf zero-crossing detection method an enhancement is proposed. The proposed sensorless method operates parameterless in a way it uses none of the brushless dc-machine parameters. In this paper different aspects of experimental implementation of the new method as well as various aspects of the FPGA programming are discussed. Proposed control method is implemented within a Xilinx Spartan 3E XC3S500E board

A review of fade detection techniques

Several proposed propagation fade detection techniques are reviewed in light of general requirements presented for beacon fade characterization. The discussion includes an analysis of phase lock versus frequency lock beacon tracking loops and of excess noise injection type radiometers. The Advanced Communications Technology Satellite (ACTS) beacon fade detection schemes proposed by the Communications Satellite Corporation and the Jet Propulsion Laboratory are examined along with the fade detection technique used by Harris in the Advanced Communications Technology Satellite (ACTS) low burst rate (LBR) terminal

Large-Scale Polarized Foreground Component Separation for Planck

We use Bayesian component estimation methods to examine the prospects for large-scale polarized map and cosmological parameter estimation with simulated Planck data assuming simplified white noise properties. The sky signal is parametrized as the sum of the CMB, synchrotron emission, and thermal dust emission. The synchrotron and dust components are modelled as power-laws, with a spatially varying spectral index for synchrotron and a uniform index for dust. Using the Gibbs sampling technique, we estimate the linear polarisation Q and U posterior amplitudes of the CMB, synchrotron and dust maps as well as the two spectral indices in ~4 degree pixels. We use the recovered CMB map and its covariance in an exact pixel likelihood algorithm to estimate the optical depth to reionization tau, the tensor-to-scalar ratio r, and to construct conditional likelihood slices for the EE and BB spectra. Given our foreground model, we find sigma(tau)~0.004 for tau=0.1, sigma(r)~0.03 for a model with r=0.1, and a 95% upper limit of r<0.02 for r=0.0.Comment: 15 pages, 12 figures, submitted to MNRA

Charge-coupled device data processor for an airborne imaging radar system

Processing of raw analog echo data from synthetic aperture radar receiver into images on board an airborne radar platform is discussed. Processing is made feasible by utilizing charge-coupled devices (CCD). CCD circuits are utilized to perform input sampling, presumming, range correlation and azimuth correlation in the analog domain. These radar data processing functions are implemented for single-look or multiple-look imaging radar systems