Comparison of observed ionospheric vertical TEC over the sea in Indian region with IRI-2016 model

The vertical ionospheric TEC values obtained from GAGAN grid based ionospheric delay correction values over the sea in the Indian equatorial region have been compared with the corresponding values derived from the International Reference Ionosphere model, IRI-2016. The objective of this work is to study the deviation of the vertical TEC derived from the IRI model from ground truths over the sea for different conditions. This will serve the basic intention of assessing the candidature of the IRI model as an alternative ionospheric correction model in navigation receivers in terms of accuracy. We have chosen different solar activity periods, seasons, geomagnetic conditions, locations etc. for our comparison and analysis. The TEC values by the IRI-2016 were compared with the actual measured values for the given conditions and errors were obtained. The measured vertical TEC values at the ionospheric grid points were derived from the GAGAN broadcast ionospheric delay data and used as reference. The IRI model with standard internal functions was used in estimating the TEC at the same ionospheric grid points. The errors in the model derived values are statistically analysed. Broadly, the results show that, for the Indian sector over the sea, the IRI model performs better on quiet days in off equatorial regions, particularly in the northern region. The overall performance degrades for other conditions with the model generally underestimating the true TEC values and most severely in the equatorial region. The performance is worst in this region for the disturbed days of the equinoctial period. The comparison study is also done with the TEC data measured directly by dual frequency GPS receivers. The results were found to be in general agreement with those obtained by comparing the model with GAGAN broadcast data as reference. This study will be useful in considering the IRI-2016 model for real time estimates of TEC as an alternative to the current parametric model in a satellite navigation receiver in absence of other options.     

Improved predictions of equatorial TEC for real time applications

It is important to use models developed specifically for the equatorial ionospheric estimation for real-time applications, particularly in Satellite Navigation. This work demonstrates a methodology for improved predictions of VTEC in real time using the model developed for the equatorial ionosphere by the authors. This work has been done using TEC data of the low solar activity period of 2005 obtained using dual frequency GPS receivers installed under the GAGAN project of ISRO. For the purpose, the model is first used in conjunction with Kriging technique. Improvement in accuracy is observed when compared with the estimations from the model alone using the measurements as true reference. Further improvement is obtained by Bayesian combination of these estimates with independent Neural Network based predictions. Statistical performance of improvement is provided. An improvement of ∼1 m in confidence level of estimation of VTEC is obtained.     

A balloon-borne sun-tracking multichannel photometer for atmospheric aerosol measurements

A balloon borne multichannel photometer for measurement of atmospheric scattering in the near ultraviolet and the visible wavelength regions has been developed at the Physical Research Laboratory, Ahmedabad for study of the size distribution and number density of aerosols at tropospheric and lower stratospheric altitudes. The instrumentation involves tracking the sun in elevation and scanning in azimuth. The payload was recently flown on a 100 kg. balloon from the Hyderabad Balloon Facility on 18 April 1984. The balloon reached a float altitude of 35 km and good quality data has been obtained from an altitude of 6 km upto float altitude. Data analysis is still in progress. The present paper details the instrument design and presents a few illustrations of the instrument performance from this flight.     

Concept of wireless sensor network for future in-situ exploration of lunar ice using wireless impedance sensor

It is known that a wireless sensor network uses some sort of sensors to detect a physical quantity of interest, in general. The wireless sensor network is a potential tool for exploring the difficult-to-access area on the earth and the concept may be extended to space applications in future. Recently, lunar water has been detected by a few lunar missions using remote sensing techniques. The lunar water is expected to be in the form of ice at very low temperatures of permanently dark regions on the moon. To support the remote observations and also to find out potential ice bearing sites on the moon, in-situ measurement of the lunar ice is essential. However, a rover may not be able to reach the permanently shadowed regions due to terrain irregularity. One possibility to access such areas is to use a wireless sensor network on the lunar surface.     

Solar X-ray Monitor (XSM) on-board Chandrayaan-2 orbiter

The remote X-ray fluorescence spectroscopy is a powerful technique to investigate the elemental abundances in the atmosphere-less planetary bodies. The experiment involves measuring spectra of fluorescent X-rays from lunar surface using a low energy X-ray detector onboard an orbiting satellite. Since the flux of fluorescent X-ray lines critically depend on the flux and spectrum of the incident solar X-rays, it is essential to have simultaneous and accurate measurement of X-ray from both Moon and Sun. In the context of Moon, this technique has been employed since early days of space exploration to determine elemental composition of lunar surface. However, so far it has not been possible to exploit it to its full potential due to various reasons. Therefore it is planned to continue the remote X-ray fluorescence spectroscopy experiment on-board Chandrayaan-2 which includes both lunar X-ray observations and solar X-ray observations as two separate payloads. The lunar X-ray observations will be carried out by Chandra Large Area Soft x-ray Spectrometer (CLASS) experiment; whereas the solar X-ray observations will be carried out by a separate payload, Solar X-ray Monitor (XSM). Here we present the overall design of the XSM instrument, the present development status as well as preliminary results of the laboratory model testing. XSM instrument will have two packages namely – XSM sensor package and XSM electronics package. XSM will accurately measure spectrum of Solar X-rays in the energy range of 1–15 keV with energy resolution ∼200 eV @ 5.9 keV. This will be achieved by using state-of-the-art Silicon Drift Detector (SDD), which has a unique capability of maintaining high energy resolution at very high incident count rate expected from Solar X-rays. XSM onboard Chandrayaan-2 will be the first experiment to use such detector for Solar X-ray monitoring.     

Prediction of ionospheric total electron content using adaptive neural network with in-situ learning algorithm

The Ionospheric Total Electron Content is responsible for the group delay of the signals from the Navigation satellites. This delay causes ranging error, which in turn degrades the accuracy of position estimated by the receivers. For critical applications, single frequency receivers resort to Satellite Based Augmentation Systems in order to have improved accuracy and integrity. The performance of these systems in terms of accuracy can be improved if predictions of the delays are available simultaneously with real measurements. This paper attempts to predict the Total Electron Content using adaptive recurrent Neural Network at three different locations of India. These locations are selected at the magnetic equator, at the equatorial anomaly crest and outside the anomaly range, respectively. In-situ Learning Algorithm has been used for tracking the non-stationary nature of the variation. Prediction is done for different prediction intervals. It is observed that, for each case, the mean and root mean square values of prediction errors remain small enough for all practical applications. Analysis of Variance is also done on the results.     

Estimation of equatorial electrojet from total electron content at geomagnetic equator using Kalman filter

The temporal variation of the equatorial electrojet is estimated utilising a suitably designed Kalman filter and using the established empirical relations between the anomaly component of equatorial TEC and the modified electrojet. TEC data obtained from dual frequency GPS receivers are used for the purpose. Estimation requires the a-priori knowledge of the peak electrojet value of the day and hence can be made in post temporal scenario only. Initial results obtained during a low solar activity time in an equinoctial month shows acceptable accuracy of the proposed algorithm. Limited analysis is done by segregating the results into temporal sessions of pre-attainment and post-attainment of the electrojet peak.     

Attenuation prediction for fade mitigation using neural network with in situ learning algorithm

Increasing demand of bandwidth in communication satellites has forced satellite links to be designed in Ku bands and above. But at these frequencies, rain and other tropospheric elements result in large attenuation. To mitigate the tropospheric attenuation of microwave satellite signals above 10 GHz using any standard Fade Mitigation Technique (FMT), it is essential to have a priori knowledge about the level of attenuation. Hence, short-term rain attenuation prediction models play a key role in maintaining the link in which necessary compensation can be applied depending on the early information of attenuation. This paper presents a method of attenuation prediction using Adaptive Artificial Neural Network. Here In situ Learning Algorithm (ILA) has been used to enable the system to track the non-stationary nature of the attenuation. To validate this, Ku Band data, collected at three different sites in India have been used for the purpose of prediction. The performance of the algorithm is determined through the estimation of prediction accuracy by comparing the predicted values with the measured data. Results obtained using the mentioned technique shows considerably good accuracy even up to 20 s of prediction interval with acceptable ratio between the under and over predictions. The prediction performance is evaluated for different prediction intervals. Furthermore the present model is also compared with the persistence model and the relative performance is quantified.     

Doppler utilised Kalman estimation (DUKE) of ionospheric delay for satellite navigation

The ionospheric delay experienced by the satellite navigation signals depends upon the Total Electron Content (TEC) and needs to be corrected. While the single frequency receivers always use parametric models to correct this delay, dual frequency receivers, when suffers a loss of lock of one of its signal, also has to resort to these models. Here, an alternative method, based on Doppler, surrogated by range rate variation, has been attempted to estimate the ionospheric delay using a Kalman filter. GPS data have been used for all visible satellites over four days selected around the equinox and solstice with nominal geomagnetic conditions and estimations done in continuous and calibrated modes. Results of continuous estimation, obtained for a mid latitude station, showed moderate accuracy while it was significantly better for the calibrated mode with no seasonal dependence. Estimations done for station within the extent of equatorial anomaly, has not only resulted in relative deterioration in performance, but also shown seasonal dependence. Compared with estimates of Klobuchar model, the Calibrated estimation showed superior performance, conspicuously in the mid latitude station. However, for the continuous mode, performance was at par with the model at higher latitudes but inferior to it in regions within the extent of the equatorial anomaly.     

A comprehensive study on middle atmospheric thermal structure over a tropic and sub-tropic stations

The general characteristics of middle atmospheric thermal structure have been studied by making use of the Rayleigh lidar data collected over the period of about four years (1998–2001). Here, the data has been used from two different stations in the Indian sub-continent in tropics (Gadanki; 13.5°N, 79.2°E) and in sub-tropics (Mt. Abu; 24.5°N, 72.7°E). The observed monthly mean temperature profiles are compared with different model atmospheres (CIRA-86 and MSISE-90). We observed, the mean temperature profiles have closer agreement with MSISE-90 than CIRA-86. The temperature profiles measured by lidar and HALOE satellite overpass nearby lidar site are generally in agreement with each other. The systematic and statistical errors in deriving temperature are found to be uniform for both the stations, as 1 K at 50 km, 3 K at 60 km and 10 K at 70 km. The special features of mesospheric temperature inversion (MTI) and double stratopause structure (DBS) are also addressed for both the stations.