Self-alignment of full skewed RSINS: observability analysis and full-observable Kalman filter

Traditional orthogonal strapdown inertial navigation sys-tem （SINS） cannot achieve satisfactory self-alignment accuracy in the stationary base： taking more than 5 minutes and al the iner-tial sensors biases cannot get ful observability except the up-axis accelerometer. However, the ful skewed redundant SINS （RSINS） can not only enhance the reliability of the system, but also improve the accuracy of the system, such as the initial alignment. Firstly, the observability of the system state includes attitude errors and al the inertial sensors biases are analyzed with the global perspective method： any three gyroscopes and three accelerometers can be assembled into an independent subordinate SINS （sub-SINS）;the system state can be uniquely confirmed by the coupling connec-tions of al the sub-SINSs;the attitude errors and random constant biases of al the inertial sensors are observable. However, the ran-dom noises of the inertial sensors are not taken into account in the above analyzing process. Secondly, the ful-observable Kalman filter which can be applied to the actual RSINS containing random noises is established; the system state includes the position, ve-locity, attitude errors of al the sub-SINSs and the random constant biases of the redundant inertial sensors. At last, the initial self-alignment process of a typical four-redundancy ful skewed RSINS is simulated： the horizontal attitudes （pitch, rol ） errors and yaw error can be exactly evaluated within 80 s and 100 s respectively, while the random constant biases of gyroscopes and accelero-meters can be precisely evaluated within 120 s. For the ful skewed RSINS, the self-alignment accuracy is greatly improved, mean-while the self-alignment time is widely shortened.

Theoretical convergence analysis of complex Gaussian kernel LMS algorithm

With the vigorous expansion of nonlinear adaptive filtering with real-valued kernel functions,its counterpart complex kernel adaptive filtering algorithms were also sequentially proposed to solve the complex-valued nonlinear problems arising in almost all real-world applications.This paper firstly presents two schemes of the complex Gaussian kernel-based adaptive filtering algorithms to illustrate their respective characteristics.Then the theoretical convergence behavior of the complex Gaussian kernel least mean square（LMS） algorithm is studied by using the fixed dictionary strategy.The simulation results demonstrate that the theoretical curves predicted by the derived analytical models consistently coincide with the Monte Carlo simulation results in both transient and steady-state stages for two introduced complex Gaussian kernel LMS algonthms using non-circular complex data.The analytical models are able to be regard as a theoretical tool evaluating ability and allow to compare with mean square error（MSE） performance among of complex kernel LMS（KLMS） methods according to the specified kernel bandwidth and the length of dictionary.

An iterative Wiener filtering method based on the gravity gradient invariants

How to deal with colored noises of GOCE （Gravity field and steady - state Ocean Circulation Explorer） satellite has been the key to data processing. This paper focused on colored noises of GOCE gradient data and the frequency spectrum analysis. According to the analysis results, gravity field model of the optima] degrees 90-240 is given, which is recovered by COCE gradient data. This paper presents an iterative Wiener filtering method based on the gravity gradient invariants. By this method a degree-220 model was calculated from GOCE SGG （Satellite Gravity Gradient） data. The degrees above 90 of ITG2010 were taken as the prior gravity field model, replacing the low degree gravity field model calculated by GOCE orbit data. GOCE gradient colored noises was processed by Wiener filtering. Finally by Wiener filtering iterative calculation, the gravity field model was restored by space-wise harmonic analysis method. The results show that the model＇s accuracy matched well with the ESA＇s （European Space Agency） results by using the same data,

VIBRATION RESPONSE AND ITS CHARACTERISTICS OF CENTRIFUGAL COMPRESSOR WITH ROTATING STALL

Based on the beginning, propagating and ending mechanism of rotating-stallcell, the relation between the pressure history signal and the pressure distribution along rotorcircumference is proposed. The angular velocities of rotating-stall cell propagating are computedfrom time series picked by the pressure probes on a cross section. Self-relation calculatingfiltered the random noise of the pressure history data. The exciting load on rotor is computed byintegral of filtered pressure signal along rotor circumference. By Prohl-Myklestad method, dynamicalequations of rotor system are obtained. The dynamical response of rotor system is resolved by usingMatlab system. Further more, the situation of more than one of stall cells is discussed. Two casesrespectively from the natural gas compressor of some fertilizer plant and the CO_2 compressor ofsome nitrogenous fertilizer plant demonstrate that both methods of calculating the load exerted onrotor by pressure fluctuation and resolving the dynamic response of rotor are available and thecharacteristics of frequency spectrum of rotating stall are correct.

Earth orientation parameters from VLBI determined with a Kalman filter

This paper introduces the reader to our Kalman filter developed for geodetic VLBI（very long baseline interferometry） data analysis. The focus lies on the EOP（Earth Orientation Parameter） determination based on the Continuous VLBI Campaign 2014（CONT14） data, but also earlier CONT campaigns are analyzed. For validation and comparison purposes we use EOP determined with the classical LSM（least squares method） estimated from the same VLBI data set as the Kalman solution with a daily resolution. To gain higher resolved EOP from LSM we run solutions which yield hourly estimates for polar motion and dUTl = Universal Time（UT1）-Coordinated Universal Time（UTC）. As an external validation data set we use a GPS（Global Positioning System） solution providing hourly polar motion results.Further, we describe our approach for determining the noise driving the Kalman filter. It has to be chosen carefully, since it can lead to a significant degradation of the results. We illustrate this issue in context with the de-correlation of polar motion and nutation.Finally, we find that the agreement with respect to GPS can be improved by up to 50% using our filter compared to the LSM approach, reaching a similar precision than the GPS solution. Especially the power of erroneous high-frequency signals can be reduced dramatically, opening up new possibilities for highfrequency EOP studies and investigations of the models involved in VLBI data analysis.We prove that the Kalman filter is more than on par with the classical least squares method and that it is a valuable alternative, especially on the advent of the VLBI2010 Global Observing System and within the GGOS frame work.

Application of Monte Carlo filtering method in regional sensitivity analysis of AASHTOWare Pavement ME design

Since AASHTO released the Mechanistic-Empirical Pavement Design Guide （MEPDG） for public review in 2004, many highway research agencies have performed sensitivity ana- lyses using the prototype MEPDG design software. The information provided by the sensitivity analysis is essential for design engineers to better understand the MEPDG design models and to identify important input parameters for pavement design. In literature, different studies have been carried out based on either local or global sensitivity analysis methods, and sensitivity indices have been proposed for ranking the importance of the input parameters. In this paper, a regional sensitivity analysis method, Monte Carlo filtering （MCF）, is presented. The MCF method maintains many advantages of the global sensitivity analysis, while focusing on the regional sensitivity of the MEPDG model near the design criteria rather than the entire problem domain. It is shown that the information obtained from the MCF method is more helpful and accurate in guiding design engineers in pavement design practices. To demonstrate the proposed regional sensitivity method, a typical three-layer flexible pavement structure was analyzed at input level 3. A detailed procedure to generate Monte Carlo runs using the AASHTOWare Pavement ME Design software was provided. The results in the example show that the sensitivity ranking of the input parameters in this study reasonably matches with that in a previous study under a global sensitivity analysis. Based on the analysis results, the strengths, practical issues, and applications of the MCF method were further discussed,

Analysis of Strehl ratio limit with superresolution binary phase filters

Several pupil filtering techniques have been developed in the last few years to obtain transverse superresolution （a narrower point spread function core）. Such a core decrease entails two relevant limitations： a decrease of the peak intensity and an increase of the sidelobe intensity. Here, we calculate the Strehl ratio as a function of the core size for the most used binary phase filters. Furthermore, we show that this relation approaches the fundamental limit of the attainable Strehl ratio at the focal plane for any filter. Finally, we show the calculation of the peak-to-sidelobe ratio in order to check the system viability in every application.

A simple data assimilation method for improving the MODIS LAI time-series data products based on the object analysis and gradient inverse weighted filter

A simple data assimilation method for improving estimation of moderate resolution imaging spectroradiometer （MODIS） leaf area index （LAI） time-series data products based on the gradient inverse weighted filter and object analysis is proposed. The properties and quality control （QC） of MODIS LAI data products are introduced. Also, the gradient inverse weighted filter and object analysis are analyzed. An experiment based on the simple data assimilation method is performed using MODIS LAI data sets from 2000 to 2005 of Guizhou Province in China.

A subband excitation substitute based scheme for narrowband speech watermarking

We propose a new narrowband speech watermarking scheme by replacing part of the speech with a scaled and spectrally shaped hidden signal. Theoretically, it is proved that if a small amount of host speech is modified, then not only an ideal channel model for hidden communication can be established, but also high imperceptibility and good intelligibility can be achieved. Furthermore, a practical system implementation is proposed. At the embedder, the power normalization criterion is first imposed on a passband watermark signal by forcing its power level to be the same as the original passband excitation of the cover speech, and a synthesis filter is then used to spectrally shape the scaled watermark signal. At the extractor, a bandpass filter is first used to get rid of the out-of-band signal, and an analysis filter is then employed to compensate for the distortion introduced by the synthesis filter. Experimental results show that the data rate is as high as 400 bits/s with better bandwidth efficiency, and good imperceptibility is achieved. Moreover, this method is robust against various attacks existing in real applications.

Chemical composition and physical properties of filter fly ashes from eight grate-fired biomass combustion plants

For the handling, treatment and utilization of fly ash from biomass combustion its chemical composition and physical properties are important. In this study eight filter fly ashes from different grate-fired biomass combustion plants were investigated. In fly ash from straw combustion high concentrations of（K） were found, whereas in the fly ash from wood combustion the concentrations of Ca and Mg were higher. The average concentration of PO3-4was similar in both types of fly ashes. In all wood fly ashes some measured heavy metal concentrations were above the limits for utilization. The straw fly ashes were much less contaminated and can be utilized. For wood fly ash most parameters showed little variation, except from one fly ash where the dust pre-separator is in poor condition. The average values were： mass median diameter 4.3 ± 0.8 μm, spread of particle size distribution19 ± 11, particle density 2620 ± 80 kg/m^3 and angle of repose 50°± 1°. The density of the straw fly ashes is lower（2260 ± 80 kg/m^3） and the spread of the size distribution is higher（72 ± 24）.For one straw combustion fly ash the values of the mass median diameter and the angle of repose were similar to the values of wood combustion fly ash, for the other straw fly ash the values differed considerably. While the particle size of this fly ash was much smaller,surprisingly the angle of repose was also lower. This can be attributed to the formation of small agglomerates in this fly ash, which were not disintegrated without a certain stress.