Oxygen line mapping of SN 1006 with Suzaku

SN 1006 is one of the supernova remnants (SNRs) with relatively low-temperature electrons, considering the young age of just 1000 years. We carried out SN 1006 mapping observations with the X-ray Imaging Spectrometers (XIS) and the Hard X-ray Detector (HXD) onboard Suzaku, the fifth Japanese X-ray satellite. Thanks to the excellent spectral resolution of XIS in the soft X-ray band, H-like and He-like oxygen emission lines were clearly detected, and we could make a map of the line intensity, and as well as a flux and the photon index of nonthermal component. We found that these parameters have spatial dependences from region to region in the SNR; the north region is bright in nonthermal, while dim in thermal; the east region is bright in both nonthermal and thermal; the inner region shows dim nonthermal and bright thermal emission. The photon index is the smallest in the north region.     

Interpretation of data on laser sensing of aerosol atmosphere from space

A single-frequency lidar, using aerosol scattering as an informative component, is the simplest and reliable facility for remote sensing of the atmosphere. The information on vertical distribution of atmospheric aerosol which can be obtained using such a lidar is necessary for investigating the physics of atmospheric processes and forecast of optical state of the atmosphere. At the same time, the interpretation of data on single-frequency sounding is associated with some difficulties of fundamental character, mainly due to insufficient software of the experiment. Under such conditions the problems of optimal processing of lidar returns aiming at extracting the useful information on aerosol are of great importance, especially if one takes into account the hindering effects of atmospheric background and optical noises. This paper presents a statistical approach to this problem, and the possibilities of single-frequency sounding from space are analyzed.     

Development of an improved ground-based prototype of space plant-growing facility

Based on a formerly developed ground-based prototype of space plant-growing facility, the development of its improved prototype has been finished, so as to make its operating principle better adapt to the space microgravity environment. According to the developing experience of its first generation prototype and detailed demonstration and design of technique plan, its blueprint design and machining of related components, whole facility installment, debugging and trial operations were all done gradually. Its growing chamber contains a volume of about 0.5 m³ and a growing area of approximate 0.5 m²; the atmospheric environmental parameters in the growing chamber and water content in the growing media were controlled totally and effectively; lighting source is a combination of both red and blue light emitting diodes (LED). The following demonstrating results showed that the entire system design of the prototype is reasonable and its operating principle can nearly meet the requirements of space microgravity environment. Therefore, our plant-growing technique in space was advanced further, which laid an important foundation for next development of the space plant-growing facility and plant-cultivating experimental research in space microgravity condition.     

Hypothesis-test-based landcover change detection using multi-temporal satellite images – A comparative study

Remote sensing images and technologies have been widely applied to environmental monitoring, in particular landuse/landcover classification and change detection. However, the uncertainties involved in such applications have not been fully addressed. In this paper two hypothesis-test-based change detection methods, namely the bivariate joint distribution method and the conditional distribution method, are proposed to tackle the uncertainties in change detection by making decisions based on the desired level of significance. Both methods require a data set of class-dependent no-change pixels to form the basis for class-dependent hypothesis test. Using an exemplar study area in central Taiwan, performance of the proposed methods are shown to be significantly superior to two other commonly applied methods (the post-classification comparison and the image differencing methods) in terms of the overall change detection accuracies. The conditional distribution method takes into consideration the correlation between digital numbers of the pre- and post-images and the effect of the known pre-image digital number on the range of the post-image digital number, and therefore yields the highest change detection accuracy. It is also demonstrated that the class-dependent change detection is crucial for accurate landuse/landcover change detection.     

Neutral Upper Atmosphere and Ionosphere Modeling

Numerical modeling tools can be used for a number of reasons yielding many benefits in their application to planetary upper atmosphere and ionosphere environments. These tools are commonly used to predict upper atmosphere and ionosphere characteristics and to interpret measurements once they are obtained. Additional applications of these tools include conducting diagnostic balance studies, converting raw measurements into useful physical parameters, and comparing features and processes of different planetary atmospheres. This chapter focuses upon various classes of upper atmosphere and ionosphere numerical modeling tools, the equations solved and key assumptions made, specified inputs and tunable parameters, their common applications, and finally their notable strengths and weaknesses. Examples of these model classes and their specific applications to individual planetary environments will be described.     

Estimation techniques for GMSK using linear detectors in satellite communications

This paper describes data-aided signal level and noise variance estimators for Gaussian minimum shift keying (GMSK) when the observations are limited to the output of a filter matched to the first pulse-amplitude modulation (PAM) pulse in the equivalent PAM representation. The estimators are based on the maximum likelihood (ML) principle and assume burst-mode transmission with known timing and a block of L₀ known bits. While it is well known that ML estimators are asymptotically unbiased and efficient, the analysis quantifies the rate at which the estimators approach these asymptotic properties. It is shown that the carrier phase, amplitude, and noise variance estimators are unbiased and can achieve their corresponding Cramer-Rao bounds with modest combinations of signal-to-noise ratio and observation length. The estimates are used to estimate the signal-to-noise ratio. It is shown that the mean squared error performance of the ratio increases with signal-to-noise ratio while the mean squared error performance of the ratio in decibels decreases with signal-to-noise ratio. Simulation results are provided to confirm the accuracy of the analytic results.     

Error Covariance Analysis of a Karhunen-Loeve Random Field Estimator

An error covariance analysis of a two-dimensional Karhunen-Loeve random field estimator (KLE) for gridded gravity data is presented without actually using the data. Attention is focused particularly on the north-south deflection component of the disturbance vector so that the rms value of its residual error may not exceed 3 percent of the signal rms for grid spacing of not less than 5 nm, when signal-to-noise ratio in the data is varied within reasonable limits. To achieve this rather stringent goal, a discrete KLE derived entirely from a two-dimensional grid configuration is needed. The KLE for geodesy applications was developed initially by Bose. Using continuous measurements and the orthogonality relations of the Karhunen-Loeve (KL) eigenvectors in a continuous domain, continuous KL gain coefficients ?mnj and consequently the continuous KL gain vector Kmn were obtained; thus a satisfactory continuous KLE was achieved. However the discrete version of the KLE was then given by keeping the old (continuous) ?mnj, and simply computing the KL eigenvectors on the grid coordinates to evaluate the discrete KL gain vector Kmn. Clearly this is not a satisfactory discrete KLE since , ?mnj are not constants but rather depend on the measurement noise variances. So if the measurements are now going to be discrete, one must rederive ?mnj for this situation.     

Dynamics of a spacecraft and normalization around Lagrangian points in the Neptune–Triton system

The problem of a spacecraft orbiting the Neptune–Triton system is presented. The new ingredients in this restricted three body problem are the Neptune oblateness and the high inclined and retrograde motion of Triton. First we present some interesting simulations showing the role played by the oblateness on a Neptune’s satellite, disturbed by Triton. We also give an extensive numerical exploration in the case when the spacecraft orbits Triton, considering Sun, Neptune and its planetary oblateness as disturbers. In the plane a × I (a = semi-major axis, I = inclination), we give a plot of the stable regions where the massless body can survive for thousand of years. Retrograde and direct orbits were considered and as usual, the region of stability is much more significant for the case of direct orbit of the spacecraft (Triton’s orbit is retrograde). Next we explore the dynamics in a vicinity of the Lagrangian points. The Birkhoff normalization is constructed around L₂, followed by its reduction to the center manifold. In this reduced dynamics, a convenient Poincaré section shows the interplay of the Lyapunov and halo periodic orbits, Lissajous and quasi-halo tori as well as the stable and unstable manifolds of the planar Lyapunov orbit. To show the effect of the oblateness, the planar Lyapunov family emanating from the Lagrangian points and three-dimensional halo orbits are obtained by the numerical continuation method.