Low complexity joint estimation of synchronization impairments in sparse channel for MIMO-OFDM system

Low complexity joint estimation of synchronization impairments and channel in a single-user MIMO-OFDM system is presented in this paper. Based on a system model that takes into account the effects of synchronization impairments such as carrier frequency offset, sampling frequency offset, and symbol timing error, and channel, a Maximum Likelihood (ML) algorithm for the joint estimation is proposed. To reduce the complexity of ML grid search, the number of received signal samples used for estimation need to be reduced. The conventional channel estimation techniques using Least-Squares (LS) or Maximum a posteriori (MAP) methods fail for the reduced sample under-determined system, which results in poor performance of the joint estimator. The proposed ML algorithm uses Compressed Sensing (CS) based channel estimation method in a sparse fading scenario, where the received samples used for estimation are less than that required for an LS or MAP based estimation. The performance of the estimation method is studied through numerical simulations, and it is observed that CS based joint estimator performs better than LS and MAP based joint estimator. (C) 2013 Elsevier GmbH. All rights reserved.

Multi-site downscaling of maximum and minimum daily temperature using support vector machine

Climate change impact assessment studies involve downscaling large-scale atmospheric predictor variables (LSAPVs) simulated by general circulation models (GCMs) to site-scale meteorological variables. This article presents a least-square support vector machine (LS-SVM)-based methodology for multi-site downscaling of maximum and minimum daily temperature series. The methodology involves (1) delineation of sites in the study area into clusters based on correlation structure of predictands, (2) downscaling LSAPVs to monthly time series of predictands at a representative site identified in each of the clusters, (3) translation of the downscaled information in each cluster from the representative site to that at other sites using LS-SVM inter-site regression relationships, and (4) disaggregation of the information at each site from monthly to daily time scale using k-nearest neighbour disaggregation methodology. Effectiveness of the methodology is demonstrated by application to data pertaining to four sites in the catchment of Beas river basin, India. Simulations of Canadian coupled global climate model (CGCM3.1/T63) for four IPCC SRES scenarios namely A1B, A2, B1 and COMMIT were downscaled to future projections of the predictands in the study area. Comparison of results with those based on recently proposed multivariate multiple linear regression (MMLR) based downscaling method and multi-site multivariate statistical downscaling (MMSD) method indicate that the proposed method is promising and it can be considered as a feasible choice in statistical downscaling studies. The performance of the method in downscaling daily minimum temperature was found to be better when compared with that in downscaling daily maximum temperature. Results indicate an increase in annual average maximum and minimum temperatures at all the sites for A1B, A2 and B1 scenarios. The projected increment is high for A2 scenario, and it is followed by that for A1B, B1 and COMMIT scenarios. Projections, in general, indicated an increase in mean monthly maximum and minimum temperatures during January to February and October to December.

Structural refinement, optical and electrical properties of Ba1-x Sm-2x/3](Zr0.05Ti0.95)O-3 ceramics

Samarium doped barium zirconate titanate ceramics with general formula Ba1-x Sm-2x/3](Zr0.05Ti0.95)O-3 x = 0, 0.01, 0.02, and 0.03] were prepared by high energy ball milling method. X-ray diffraction patterns and micro-Raman spectroscopy confirmed that these ceramics have a single phase with a tetragonal structure. Rietveld refinement data were employed to model BaO12], SmO12], ZrO6], and TiO6] clusters in the lattice. Scanning electron microscopy shows a reduction in average grain size with the increase of Sm3+ ions into lattice. Temperature-dependent dielectric studies indicate a ferroelectric phase transition and the transition temperature decreases with an increase in Sm3+ ion content. The nature of the transition was investigated by the Curie-Weiss law and it is observed that the diffusivity increases with Sm3+ ion content. The ferroelectric hysteresis loop illustrates that the remnant polarization and coercive field increase with an increase in Sm3+ ions content. Optical properties of the ceramics were studied using ultraviolet-visible diffuse reflectance spectroscopy.

Autonomous Star Camera Calibration and Spacecraft Attitude Determination

This paper presents two methods of star camera calibration to determine camera calibrating parameters (like principal point, focal length etc) along with lens distortions (radial and decentering). First method works autonomously utilizing star coordinates in three consecutive image frames thus independent of star identification or biased attitude information. The parameters obtained in autonomous self-calibration technique helps to identify the imaged stars with the cataloged stars. Least Square based second method utilizes inertial star coordinates to determine satellite attitude and star camera parameters with lens radial distortion, both independent of each other. Camera parameters determined by the second method are more accurate than the first method of camera self calibration. Moreover, unlike most of the attitude determination algorithms where attitude of the satellite depend on the camera calibrating parameters, the second method has the advantage of computing spacecraft attitude independent of camera calibrating parameters except lens distortions (radial). Finally Kalman filter based sequential estimation scheme is employed to filter out the noise of the LS based estimation.

Differential expression of estrogen receptor alpha in the embryonic adrenal-kidney-gonadal complex of the oviparous lizard, Calotes versicolor (Daud.)

Estrogen signalling is critical for ovarian differentiation in reptiles with temperature-dependent sex determination (TSD). To elucidate the involvement of estrogen in this process, adrenal-kidney-gonadal (AKG) expression of estrogen receptor (ER alpha) was studied at female-producing temperature (FPT) in the developing embryos of the lizard, Calotes versicolor which exhibits a distinct pattern of TSD. The eggs of this lizard were incubated at 31.5 +/- 0.5 degrees C (100% FPT). The torso of embryos containing adrenal-kidney-gonadal complex (AKG) was collected during different stages of development and subjected to Western blotting and immunohistochemistry analysis. The ER alpha, antibody recognized two protein bands with apparent molecular weight similar to 55 and similar to 45 kDa in the total protein extracts of embryonic AKG complex of C. versicolor. The observed results suggest the occurrence of isoforms of ER alpha. The differential expression of two different protein isoforms may reveal their distinct role in cell proliferation during gonadal differentiation. This is the first report to reveal two isoforms of the ER alpha in a reptile during development. Immunohistochemical studies reveal a weak, but specific, cytoplasmic ER alpha immunostaining exclusively in the AKG during late thermo-sensitive period suggesting the responsiveness of AKG to estrogens before gonadal differentiation at FPT. Further, cytoplasmic as well as nuclear expression of ER alpha in the medulla and in oogonia of the cortex (faint activity) at gonadal differentiation stage suggests that the onset of gonadal estrogen activity coincides with sexual differentiation of gonad. Intensity and pattern of the immunoreactions of ER alpha in the medullary region at FPT suggest endogenous production of estrogen which may act in a paracrine fashion to induce neighboring cells into ovarian differentiation pathway. (C) 2014 Elsevier Inc. All rights reserved.

Micro-satellite angular rate estimation using second-order sliding mode observer

Development of computationally efficient and accurate attitude rate estimation algorithm using low-cost commercially available star sensor arrays and processing unit for micro-satellite mission is presented. Our design reduces the computational load of least square (LS)-based rate estimation method while maintaining the same accuracy compared to other rate estimation approaches. Furthermore, rate estimation accuracy is improved by using recently developed fast and accurate second-order sliding mode observer (SOSMO) scheme. It also gives robust estimation in the presence of modeling uncertainties, unknown disturbances, and measurement noise. Simulation study shows that rate estimation accuracy achieved by our LS-based method is comparable with other methods for a typical commercially available star sensor array. The robustness analysis of SOSMO with respect to measurement noise is also presented in this paper. Simulation test bench for a practical scenario of satellite rate estimation uses moment-of-inertia variation and environmental disturbances affecting a typical micro-satellite at 500km circular orbit. Comparison studies of SOSMO with 1-SMO and pseudo-linear Kalman filter show that satisfactory estimation accuracy is achieved by SOSMO.