Modeling error analysis of stationary linear discrete-time filters

The performance of Kalman-type, linear, discrete-time filters in the presence of modeling errors is considered. The discussion is limited to stationary performance, and bounds are obtained for the performance index, the mean-squared error of estimates for suboptimal and optimal (Kalman) filters. The computation of these bounds requires information on only the model matrices and the range of errors for these matrices. Consequently, a design can easily compare the performance of a suboptimal filter with that of the optimal filter, when only the range of errors in the elements of the model matrices is available

Characterisation of the UV environment of the Beagle 2 landing site

A study of the UV environment of the Beagle 2 landing site has been carried out. An instrument to measure the UV flux is present on the lander, and this work serves to aid in the interpretation of expected data

Algorithms for adaptive stochastic control for a class of linear systems

Control of linear, discrete time, stochastic systems with unknown control gain parameters is discussed. Two suboptimal adaptive control schemes are derived: one is based on underestimating future control and the other is based on overestimating future control. Both schemes require little on-line computation and incorporate in their control laws some information on estimation errors. The performance of these laws is studied by Monte Carlo simulations on a computer. Two single input, third order systems are considered, one stable and the other unstable, and the performance of the two adaptive control schemes is compared with that of the scheme based on enforced certainty equivalence and the scheme where the control gain parameters are known

Atmospheric modelling for NOMAD-UVIS on board the ExoMars Trace Gas Orbiter mission

The Ultraviolet and Visible Spectrometer (UVIS) instrument development process requires the construction of an atmospheric model to provide synthetic UV transmission spectra. We discuss the requirements of the model to enable observational limits to be found, and the potential for certain atmospheric parameters to be further constrained

A multi-spacecraft reanalysis of the atmosphere of Mars

We have conducted a nine-Mars Year (MY) consistent reanalysis of the martian atmosphere covering the period MY 24–32 and making use of data from three different spacecraft. Remotely-sensed measurements of temperature, dust opacity, water ice and ozone from NASA’s Mars Global Surveyor (MGS) and Mars Recconaisance Orbiter (MRO) and ESA’s Mars Express (MEx) were assimilated [1] into a single model simulation, sampled two-hourly over the whole period. This forms a large, regular reanalysis dataset that is being made publicly available as an output of the EU UPWARDS project. The same analysis technique, with an improved model and higher resolution will be conducted with ESA Trace Gas Orbiter (TGO) data as it becomes available

Assimilating the Martian water cycle

Water ice clouds have been shown to alter the thermal structure of the Martian atmosphere. Here we discuss the assimilation of total column water vapour and dust optical depth data from the Thermal Emission Spectrometer (TES) into the UK/LMD MGCM, and compare the predictions of cloud and temperature in the assimilation with observations

Trace gas assimilation of Mars orbiter observations

Ozone, water vapour and argon are minor constituents in the Martian atmosphere, observations of which can be of use in constraining atmospheric dynamical and physical processes. This is especially true in the winter season of each hemisphere, when the bulk of the main constituent in the atmosphere (CO2 ) condenses in the polar regions shifting the balance of atmospheric composition to a more trace gas rich air mass. Current Mars Global Circulation Models (MGCMs) are able to represent the photochemistry occuring in the atmosphere, with constraints being imposed by comparisons with observations. However, a long term comparison using data assimilation provides a more robust constraint on the model. We aim to provide a technique for trace gas data assimilation for the analysis of observations from current and future satellite missions (such as ExoMars) which observe the spatial and temporal distribution of trace gases on Mars

Assessment of Kisan Mobile Advisory (KMA) Service for Dissemination of Agriculture Information in Mehsana District; Gujarat

Introduction of information and communication (ICT) in the field of Agriculture has brought many changes in traditional methods of extension. It enables the dissemination of requisite information at the right time to the right people. The revolution in ICT has made access to the information easy and cost effective to the rural masses in general and farming community in particular. Kisan Mobile Sandesh (KMS) or Kisan Mobile Advisory Services (KMAS) is one among several methods of ICTs working successfully for dissemination of latest information. KMAS is best on the liner model of communication, which involve four major component of communication process viz. Sender, Message, Channel and Receiver, Mobile phones, Short Message Service (sms) are important tools and can be used by the KVK specialist. The extension functionary is the user of the information while farmers are implementer at field level. Kisan Mobile Advisory Service was launched for sending information through SMS in Mehsana District through Krishi Vigyan Kendra during January 2014. The content of messages were typed in Gujarati language and information related to crop production, crop protection, vegetable and fruit production, spice crops, dairy farming, weather forecasting, post harvest management and other agricultural and allied related information sent to end users. To evaluate the sending information and usefulness of information, the present study was constitutes, survey of 80 farmers, 10 in-service personnel and 10 input suppliers of district during 2014-15. Result of survey shows that messages were highly understandable for large majority 42.50 % of the members of farmer’s category. It was highly understandable for 80 % and 50 % KMA member of in-service personnel and input supplier category respectively. Messages were needful and timely for 67.50% of KMA member of farmer’s category and about 70% and 50% for in-service personnel and input supplier, respectively. As far as applicability of message is concerned, the messages were fully applicable for about 44 % of KMA member of farmer’s category whereas medium and partially applicable were reported by 17.50 % and 22.50 % of members, respectively. It was also found that messages were fully applicable for in-service personnel (60 %) and input supplier (50 %). Majority of the framers 72.50 % were conveyed the messages minimum to one another farmers in social system. DOI: 10.17762/ijritcc2321-8169.15075