Estimation and analysis of user IPP delays using bilinear model for satellite-based augmented navigation systems

Several countries are involved in developing satellite-based augmentation systems (SBAS) for improving the positional accuracy of GPS. India is also developing one such system, popularly known as GPS-aided geo-augmented navigation (GAGAN), to cater to civil aviation applications. The ionospheric effect is the major source of error in GAGAN. An appropriate efficient and accurate ionospheric time model for GAGAN is necessary. To develop such a model, data from 17 GPS stations of the GAGAN network spread across India are used in modelling. The prominent model, known as bi-linear interpolation technique, is investigated for user IPP (UIPP) delay estimation. User IPP delays for quiet, moderate and disturbed days are estimated. It is evident that measured mean UIPP delays closely follow estimated mean UIPP delays

Faster Acquisition Technique for Software-defined GPS Receivers

Acquisition is a most important process and a challenge task for identifying visible satellites, coarse values of carrier frequency, and code phase of the satellite signals in designing software defined Global positioning system (GPS) receiver. This paper presents a new, simple, efficient and faster GPS acquisition via sub-sampled fast Fourier transform (ssFFT). The proposed algorithm exploits the recently developed sparse FFT (or sparse IFFT) that computes in sub-linear time. Further it uses the property of fourier transforms (FT): Aliasing a signal in the time domain corresponds to sub-sampling it in the frequency domain, and vice versa. The ssFFT is an FFT algorithm that computes sub-sampled version of the data by an integer factor ‘d’, and hence, the computational complexity is proportionately reduced by a factor of ‘d log d’ compared to conventional FFT-based algorithms for any length of the input GPS signal. The simulation results show that the proposed ssFFT based GPS acquisition computation is 8.5571 times faster than the conventional FFT-based acquisition computation time. The implementation of this method in an FPGA provides very fast processing of incoming GPS samples that satisfies real-time positioning requirements.Defence Science Journal, Vol. 65, No. 1, January 2015, pp.5-11, DOI:http://dx.doi.org/10.14429/dsj.65.557

Low latitude ionospheric response to March 2015 geomagnetic storm using multi-instrument TEC observations over India

The regional ionospheric models are successful in capturing the variability of ionosphere with the inclusion of local ground-based GPS observations and location dependent ionospheric dynamics. In this context, there is a need to develop regional ionospheric maps that aids in improving the consistency of global models. In this paper, an attempt is made to understand the potentiality of multi-instrument observations over Indian region. Four different Total Electron Content (TEC) data sources namely from network of GPS receivers, Ionosonde stations, space based COSMIC radio occultation profiles and SWARM mission data is utilized. The multi-source data is chosen for the geo-magnetic storm conditions prevailed during March 2015. Data from multiple-sources is observed over the period from 15th March 2015 to 20th March 2015. Validation of ground and space-based TEC data with International GNSS service (IGS) station data is significantly observed

Modelling of ionospheric time delays based on adjusted spherical harmonic analysis

The ionosphere is the region of the upper atmosphere and the study of the upper atmosphere has a significant role in monitoring, modeling and forecasting for satellite based navigation services. As India lies in a low latitude region, a more careful approach has to be taken to characterize the ionosphere due to the irregularities and equatorial anomaly conditions. In order to study the ionospheric temporal variations, a regional ionospheric model based on the Adjusted Spherical Harmonic Analysis (ASHA) is implemented. The results indicate that the ASHA model is one of the contenders for estimating ionospheric delays well for GNSS augmentation systems

Deficiency of a Niemann-Pick, Type C1-related Protein in Toxoplasma Is Associated with Multiple Lipidoses and Increased Pathogenicity

Several proteins that play key roles in cholesterol synthesis, regulation, trafficking and signaling are united by sharing the phylogenetically conserved ‘sterol-sensing domain’ (SSD). The intracellular parasite Toxoplasma possesses at least one gene coding for a protein containing the canonical SSD. We investigated the role of this protein to provide information on lipid regulatory mechanisms in the parasite. The protein sequence predicts an uncharacterized Niemann-Pick, type C1-related protein (NPC1) with significant identity to human NPC1, and it contains many residues implicated in human NPC disease. We named this NPC1-related protein, TgNCR1. Mammalian NPC1 localizes to endo-lysosomes and promotes the movement of sterols and sphingolipids across the membranes of these organelles. Miscoding patient mutations in NPC1 cause overloading of these lipids in endo-lysosomes. TgNCR1, however, lacks endosomal targeting signals, and localizes to flattened vesicles beneath the plasma membrane of Toxoplasma. When expressed in mammalian NPC1 mutant cells and properly addressed to endo-lysosomes, TgNCR1 restores cholesterol and GM1 clearance from these organelles. To clarify the role of TgNCR1 in the parasite, we genetically disrupted NCR1; mutant parasites were viable. Quantitative lipidomic analyses on the ΔNCR1 strain reveal normal cholesterol levels but an overaccumulation of several species of cholesteryl esters, sphingomyelins and ceramides. ΔNCR1 parasites are also characterized by abundant storage lipid bodies and long membranous tubules derived from their parasitophorous vacuoles. Interestingly, these mutants can generate multiple daughters per single mother cell at high frequencies, allowing fast replication in vitro, and they are slightly more virulent in mice than the parental strain. These data suggest that the ΔNCR1 strain has lost the ability to control the intracellular levels of several lipids, which subsequently results in the stimulation of lipid storage, membrane biosynthesis and parasite division. Based on these observations, we ascribe a role for TgNCR1 in lipid homeostasis in Toxoplasma

Detection of ionospheric spatial and temporal gradients for ground based augmentation system applications

11-19<span style="font-size:9.0pt;font-family: " times="" new="" roman";mso-fareast-font-family:"times="" roman";mso-bidi-font-family:="" mangal;mso-ansi-language:en-us;mso-fareast-language:en-us;mso-bidi-language:="" hi"="" lang="EN-US">Standalone Global Navigation Satellite System (GNSS) is inadequate for precise navigation of aircrafts. Ground-based Augmentation System (GBAS) augments the performance of GNSS for civil aviation by providing differential corrections to the position of an aircraft during takeoff and landing. Ionospheric gradients affect the accuracy of GNSS and they can be detected and characterized from GNSS observations. In this paper, the ionospheric temporal and spatial gradients have been detected and the ionospheric drift velocity has been evaluated from the data recorded by GNSS receivers located at Koneru Lakshmaiah University, Guntur (GNT) and Indian Meteorological Department, Machilipatnam (MPM), Andhra Pradesh, India. Both the stations are chosen as they are situated close to each other and to the Vijayawada Airport. The rate of TEC index (ROTI) and numerical differentiation are applied to detect the ionospheric temporal gradients. Time-step and Station-pair methods are used to detect the spatial gradients. Ionospheric gradients at GNT and MPM stations for the month of January 2015 have been discussed. The gradients are found to have occurred mostly between 2000 and 2200 hrs LT. The maximum value of ionospheric gradient velocity is 473.25 ms-1. The S4 value is above 0.8 and the phase scintillation value is above 0.7 radians. </span

Ionospheric forecasting model using fuzzy logic-based gradient descent method

Space weather phenomena cause satellite to ground or satellite to aircraft transmission outages over the VHF to L-band frequency range, particularly in the low latitude region. Global Positioning System (GPS) is primarily susceptible to this form of space weather. Faulty GPS signals are attributed to ionospheric error, which is a function of Total Electron Content (TEC). Importantly, precise forecasts of space weather conditions and appropriate hazard observant cautions required for ionospheric space weather observations are limited. In this paper, a fuzzy logic-based gradient descent method has been proposed to forecast the ionospheric TEC values. In this technique, membership functions have been tuned based on the gradient descent estimated values. The proposed algorithm has been tested with the TEC data of two geomagnetic storms in the low latitude station of KL University, Guntur, India (16.44°N, 80.62°E). It has been found that the gradient descent method performs well and the predicted TEC values are close to the original TEC measurements