Oxygen isotopes of lake marl at Gerzensee and Leysin (Switzerland), covering the Younger Dryas and two minor oscillations, and their correlation to the GRIP ice core

The ratio of oxygen isotopes is a temperature proxy both in precipitation and in the calcite of lacustrine sediments. The very similar oxygen-isotope records from Greenland ice cores and European lake sediments during the Last Glacial Termination suggest that the drastic climatic changes occurred quasi-simultaneously on an extra-regional, probably hemispheric scale. In order to study temporal relations of the different parameters recorded in lake sediments, for example biotic response times to rapid climatic changes, a precise chronology is required. In unlaminated lake sediments there is not yet available a method to provide a high-resolution chronology, especially for periods with radiocarbon plateaux. Alternatively, an indirect time scale can be constructed by linking the lake stratigraphy with other well-dated climate records. New oxygen-isotope records from Gerzensee and Leysin, with an estimated sampling resolution of between 15 and 40 years, match the Greenlandic isotope record in many details. Under the assumption that the main variations in temperature and thus in oxygen isotopes occurred about simultaneously in Greenland and Switzerland, we have assigned a time scale to the lake sediments of Gerzensee and Leysin by wiggle-matching their stable-isotope records with those of Greenland ice cores, which are among the best dated climatic archives. We estimate a precision of 20 to 100 years during the Last Glacial Termination.

Fine-grained indoor positioning and tracking systems

Indoor positioning has attracted considerable attention for decades due to the increasing demands for location based services. In the past years, although numerous methods have been proposed for indoor positioning, it is still challenging to find a convincing solution that combines high positioning accuracy and ease of deployment. Radio-based indoor positioning has emerged as a dominant method due to its ubiquitousness, especially for WiFi. RSSI (Received Signal Strength Indicator) has been investigated in the area of indoor positioning for decades. However, it is prone to multipath propagation and hence fingerprinting has become the most commonly used method for indoor positioning using RSSI. The drawback of fingerprinting is that it requires intensive labour efforts to calibrate the radio map prior to experiments, which makes the deployment of the positioning system very time consuming. Using time information as another way for radio-based indoor positioning is challenged by time synchronization among anchor nodes and timestamp accuracy. Besides radio-based positioning methods, intensive research has been conducted to make use of inertial sensors for indoor tracking due to the fast developments of smartphones. However, these methods are normally prone to accumulative errors and might not be available for some applications, such as passive positioning. This thesis focuses on network-based indoor positioning and tracking systems, mainly for passive positioning, which does not require the participation of targets in the positioning process. To achieve high positioning accuracy, we work on some information of radio signals from physical-layer processing, such as timestamps and channel information. The contributions in this thesis can be divided into two parts: time-based positioning and channel information based positioning. First, for time-based indoor positioning (especially for narrow-band signals), we address challenges for compensating synchronization offsets among anchor nodes, designing timestamps with high resolution, and developing accurate positioning methods. Second, we work on range-based positioning methods with channel information to passively locate and track WiFi targets. Targeting less efforts for deployment, we work on range-based methods, which require much less calibration efforts than fingerprinting. By designing some novel enhanced methods for both ranging and positioning (including trilateration for stationary targets and particle filter for mobile targets), we are able to locate WiFi targets with high accuracy solely relying on radio signals and our proposed enhanced particle filter significantly outperforms the other commonly used range-based positioning algorithms, e.g., a traditional particle filter, extended Kalman filter and trilateration algorithms. In addition to using radio signals for passive positioning, we propose a second enhanced particle filter for active positioning to fuse inertial sensor and channel information to track indoor targets, which achieves higher tracking accuracy than tracking methods solely relying on either radio signals or inertial sensors.

A ~ 32-70 K formation temperature range for the ice grains agglomerated by Comet 67P/Churyumov-Gerasimenko

Grand Canonical Monte Carlo simulations are used to reproduce the N₂/CO ratio ranging between 1.7 x 10⁻³ and 1.6 x 10⁻² observed in situ in the Jupiter-family comet 67 P/Churyumov-Gerasimenko (67 P) by the ROSINA mass spectrometer on board the Rosetta spacecraft. By assuming that this body has been agglomerated from clathrates in the protosolar nebula (PSN), simulations are developed using elaborated interatomic potentials for investigating the temperature dependence of the trapping within a multiple-guest clathrate formed from a gas mixture of CO and N₂ in proportions corresponding to those expected for the PSN. By assuming that 67 P agglomerated from clathrates, our calculations suggest the cometary grains must have been formed at temperatures ranging between ~ 31.8 and 69.9 K in the PSN to match the N₂/CO ratio measured by the ROSINA mass spectrometer. The presence of clathrates in Jupiter-family comets could then explain the potential N₂ depletion (factor of up to ~ 87 compared to the protosolar value) measured in 67 P/Churyumov-Gerasimenko.

VIS-NIR reflectance of water ice/regolith analogue mixtures and implications for the detectability of ice mixed within planetary regoliths

Permanently shadowed regions at the poles of the Moon and Mercury have been pointed out as candidates for hosting water ice at their surface. We have measured in the laboratory the visible and near infrared spectral range (VIS-NIR) bidirectional reflectance of intimate mixtures of water ice and the JSC-1AF lunar simulant for different ice concentrations, particle sizes, and measurement geometries. The nonlinearity between the measured reflectance and the amount of ice in the mixture can be reproduced to some extent by the mixing formulas of standard reflectance models, in particular, those of Hapke and Hiroi, which are tested here. Estimating ice concentrations from reflectance data without knowledge of the mixing coefficientsstrongly dependent on the size/shape of the grainscan result in large errors. According to our results, it is possible that considerable amounts of water ice might be intimately mixed in the regolith of the Moon and Mercury without producing noticeable photometric signatures.

Volcanic terrain and the possible periglacial formation of "excess ice" at the mid-latitudes of Utopia Planitia, Mars

At the mid-latitudes of Utopia Planitia (UP), Mars, a suite of spatially-associated landforms exhibit geomorphological traits that, on Earth, would be consistent with periglacial processes and the possible freeze-thaw cycling of water. The suite comprises small-sized polygonally-patterned ground, polygon-junction and -margin pits, and scalloped, rimless depressions. Typically, the landforms incise a dark-toned terrain that is thought to be ice-rich. Here, we investigate the dark-toned terrain by using high resolution images from the HiRISE as well as near-infrared spectral-data from the OMEGA and CRISM. The terrain displays erosional characteristics consistent with a sedimentary nature and near-infrared spectra characterised by a blue slope similar to that of weathered basaltic-tephra. We also describe volcanic terrain that is dark-toned and periglacially-modified in the Kamchatka mountain-range of eastern Russia. The terrain is characterised by weathered tephra inter-bedded with snow, ice-wedge polygons and near-surface excess ice. The excess ice forms in the pore space of the tephra as the result of snow-melt infiltration and, subsequently, in-situ freezing. Based on this possible analogue, we construct a three-stage mechanism that explains the possible ice-enrichment of a broad expanse of dark-toned terrain at the mid-latitudes of UP: (1) the dark-toned terrain accumulates and forms via the regional deposition of sediments sourced from explosive volcanism; (2) the volcanic sediments are blanketed by atmospherically-precipitated (H2O) snow, ice or an admixture of the two, either concurrent with the volcanic-events or between discrete events; and, (3) under the influence of high obliquity or explosive volcanism, boundary conditions tolerant of thaw evolve and this, in turn, permits the migration, cycling and eventual formation of excess ice in the volcanic sediments. Over time, and through episodic iterations of this scenario, excess ice forms to decametres of depth. (C) 2015 Elsevier B.V. All rights reserved.

Fine-grained Indoor Tracking by Fusing Inertial Sensor and Physical Layer Information in WLANs

Indoor positioning has become an emerging research area because of huge commercial demands for location-based services in indoor environments. Channel State Information (CSI) as fine-grained physical layer information has been recently proposed to achieve high positioning accuracy by using range based methods, e.g., trilateration. In this work, we propose to fuse the CSI-based ranging and velocity estimated from inertial sensors by an enhanced particle filter to achieve highly accurate tracking. The algorithm relies on some enhanced ranging methods and further mitigates the remaining ranging errors by a weighting technique. Additionally, we provide an efficient method to estimate the velocity based on inertial sensors. The algorithms are designed in a network-based system, which uses rather cheap commercial devices as anchor nodes. We evaluate our system in a complex environment along three different moving paths. Our proposed tracking method can achieve 1.3m for mean accuracy and 2.2m for 90% accuracy, which is more accurate and stable than pedestrian dead reckoning and range-based positioning.