Academic literature on the topic 'GAGAN (GPS Aided Geo Augmentation Navigation)'

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.

To meet the demands of civil aviation and other precise navigation applications, several satellite-based augmentation systems (SBASs) have been developed around the world, such as the Wide Area Augmentation System (WAAS) for North America, the European Geostationary Navigation Overlay Service (EGNOS) for Europe, the Multi-functional Satellite Augmentation System (MSAS) for Japan, the GPS (Global Positioning System) Aided GEO Augmented Navigation (GAGAN) for India, and the System for Differential Corrections and Monitoring (SDCM) for Russia. The SBASs broadcast messages to correct satellite orbit, clock, and ionosphere errors to augment the GPS positioning performance. In this paper, SBAS orbit, clock and ionospheric corrections are evaluated. Specifically, the orbit, clock and ionospheric corrections derived from SBAS messages are comprehensively evaluated using data collected from the above mentioned systems over 181 consective days. The evaluation indicates that the EGNOS outperforms other systems with signal-in-space range error (SISRE) at 0.645 m and ionospheric correction accuracy at 0.491 m, respectively. Meanwhile, the accuracy of SDCM is comparable to EGNOS with SISRE of 0.650 m and ionospheric correction accuracy of 0.523 m. For WAAS, the SISRE is 0.954 m and the accuracy of ionospheric correction is 0.505 m. The accuracies of the SBAS corrections from the MSAS and GAGAN systems, however, are significantly worse than those of others. The SISREs are 1.931 and 1.325 m and the accuracies of ionospheric corrections are 0.795 and 0.858 m, for MSAS and GAGAN, respectively. At the same time, GPS broadcast orbit, clock and ionospheric corrections are also evaluated. The results show that there are no significant improvements in the SISRE of the broadcast navigation data by applying SBAS corrections. On the other hand, the accuracy of SBAS ionospheric corrections is still much better than GPS broadcast ionospheric corrections, which could still be beneficial for single-frequency users.

Energy is a critical issue in Mobile Ad-hoc Network. Nodes in Network are working in presence of limited or less energy due to dynamic nature of nodes or infrastructure less network. MANET has no infrastructure so nodes in MANET work on dynamic routing. In this way, energy proficient routing is required for reducing energy utilization. Energy proficient routing plans can extraordinarily reduce energy utilization and augments the lifetime of the networks. Scalability of Ad Hoc Networks can be enhanced by using land data, for example, in LAR, GPSR etc. They utilize physical area data; regularly from GPS (Global Positioning System).GPS empowers a gadget to decide their position as in longitude, Latitude and Altitude by getting this data from the satellites. There has been significant effort in proposing energy efficient routing protocols with the help of GAGAN (GPS Aided GEO Augmented Navigation) which have accuracy to approx One meter in India or its neighbor countries. GAGAN is a route framework which is helped by both GPS and nearby telemetry information to possibly give quicker and more exact situating and navigational information.

This paper elucidates the changing ownership of Public owned airports to Privatisation. The analysis is envisioned towards the passengers’ interest in availing air transport which are likely to become more efficient. The improvisation of regional connectivity would yield more people to opt for air transport. A series of efforts were taken before making the questionnaires that were placed in the survey including the psychological aspects when deciding about the choice of airports which are getting privatized. The collected inputs from the passengers vary from seldom travelers to frequent travelers across the country are analyzed using the linear programming technique such as the DEA[1] which depicts the effective views of the travelers to go for Privatisation. The questionnaire was carefully framed such that all the aspects covering ergonomics level, including the ease of navigation, the reach of supporting staff. The airports would get diversified with their services without the intervention of Government. In India, a total of 137 airports which include 23 International airports (3 Civil Enclaves), 10 Customs Airports (4 Civil Enclaves) having custom and immigration facilities for limited international operations and 104 Domestic airports (23 Civil Enclaves) are administered by the Airport Authority of India (AAI).[10] The USA has 14,549 Private airports (74%) within the total 19,636 airports. Many countries like the USA, Russia, China, U. K, France have a larger number of Privately-owned airports helping their countries in getting economically strengthened. IATA forecasts a growth of 6.8% per annum for India. The usage of No frill airports would reduce the cost of capital investment in making an airport to start functioning and help the nation to grow in the economy. In addition, Six AAI airports are operated, managed, and developed under Public-Private Partnership (PPP) namely, Guwahati, Jaipur, Ahmedabad, Mangalore, Thiruvananthapuram and Lucknow. At Mumbai, Delhi, Chennai, and Ahmedabad, Performance Based Navigation (PBN) arrival and departure procedures have been implemented and for Hyderabad airport, it is in progress and Space-based, Final Operational Phase (FOP) of (GAGAN), GPS Aided Geo Augmented Navigation[10] is under implementation which is not airport-based and will be available for use at all of the country's airports. Enhancing the prediction of outcomes through feature selection, the Data envelopment analysis (DEA) method is used for the analytics questionnaire. This is a function whose form is based on the efficiency of the scrutinized evaluations. It's an approach for measuring the performance efficiency of global public airports through varied contemplations of results of the survey. This technique aims to measure how efficiently a DEA uses the resources available to generate a group of outputs along with feature section models that are then analyzed after that to evaluate the contributing factors for airport operation and privatization.

AbstractSatellite-Based Augmentation System (SBAS) is essential to support aircraft navigation. L1 SBAS operates on the L1 frequency (1575.42 MHz) and is currently still of interest since all GNSS satellites and receivers do not fully support additional frequencies such as L5 (1176.45 MHz). Although the Global Positioning System (GPS) aided Geo Augmented Navigation (GAGAN) SBAS is available, the performances are degraded due to the discrepancies of the ionospheric correction over Thailand and surrounding areas. Hence, in this work, we propose a new method based on the geometry-free ionospheric delay estimation with a single frequency (L1) and a single reference station requirement. The local ionospheric delays are estimated based on the proposed method with the observed GPS and GAGAN data in Thailand. Then the ionospheric corrections are obtained from the estimated local ionospheric delays. The analysis shows that using the estimated corrections, the positioning errors are reduced both on quiet days and locally disturbed days in 2019. More reductions in the positioning errors are found in September and December than other months. In addition, we perform a preliminary availability assessment of two critical phases of flights. The GAGAN performances with the proposed method for the APV-I and LPV-200 categories are improved up to 57% and 53%, respectively, in comparison with the baseline method of the IGP correction.

If any Global Positioning System (GPS) receiver is operated in low latitude regions or urban canyons, the visibility further reduces. These system constraints lead to many challenges in providing precise GPS position accuracy over the Indian subcontinent. As a result, the standalone GPS accuracy does not meet the aircraft landing requirements, such as Category I (CAT-I) Precision Approaches. However, the required accuracy can be achieved by augmenting the GPS. Among all these issues, the predominant factors that significantly influence the receiver position accuracy are selecting a user/receiver position estimation algorithm. In this article, a novel method is proposed based on correntropy and designated as Correntropy Kalman Filter (CKF) for precise GPS applications and GPS Aided Geosynchronous equatorial orbit Augmented Navigation (GAGAN) based aircraft landings over the low latitude Indian subcontinent. The real-world GPS data collected from a dual-frequency GPS receiver located in the southern region of the Indian subcontinent (IISc), Bangalore with Lat/Long: 13.021°N/ 77.5°E) is used for the performance evaluation of the proposed algorithm. Results prove that the proposed CKF algorithm exhibits significant improvement (up to 34%) in position estimation compared to the traditional Kalman Filter.

Satellites have revolutionized navigation by making it more universal, accessible and ac- curate. Global Positioning System (GPS) is the most widely used satellite navigation system in the world. However, it is prone to errors from various sources such as the ionosphere, troposphere and clock biases. In order to make the system very accurate and reliable, especially to meet the requirements of safety-critical applications, Satellite Based Augmentation Systems (SBAS) have recently been designed in various countries to augment the GPS by providing corrections for its errors. An Indian SBAS called GAGAN (GPS Aided Geo Augmented Navigation), developed for the Airports Authority of India (AAI) by Indian Space Research Organization (ISRO) is currently being installed and proven for aviation and other use. The uncertain propagation delay of signals through the ionosphere is the most important contributor of error in GPS positioning, its maximal elimination is a major task of SBAS overlays. Ionospheric delays have steady, cyclic, and irregular components. The last types are of particular concern because they are unpredictable. This thesis deals with ionospheric depletion, an important phenomenon of this class that is specific to tropical regions like India and hence have not been well studied in the context of other SBAS systems of the world which cover mid-latitude domains. Depletion is an ionospheric phenomenon in which the density of electrons dips suddenly and then returns close to the previous value. It poses a challenge to the model adopted for ionospheric delay estimation since it may not be detectable by ground systems be- cause of its localized nature, and its occurrence and intensity cannot be predicted. In this work we have analyzed the depletion characteristics over the Indian region such as its distribution, frequency of occurrence, and depth and duration parameters. We have then studied and implemented an existing algorithm to detect a depletion from the Total Electron Content (TEC) data. This algorithm has been found to be inaccurate for estimation of depletion duration, and we have proposed an improved algorithm for depletion detection and shown it to be more suitable for the Indian SBAS, GAGAN. The algorithm utilizes multiple thresholds for depletion detection in order to improve performance in the presence of irregularities including noise. These thresholds are determined by analyzing real TEC data containing depletion events over the Indian region. The detected depletion events are those that have a strong likelihood of contributing large range errors and degrading GAGAN's reliability. The thresholds include depletion parameters such as the depth, duration, rate of change of TEC, and the rate of change of slope of the TEC curve. The characterization of depletion events over the Indian region yielded useful insights into the behaviour of the phenomenon. It was observed that the depletion events were invariably present post-sunset, between 1900 and 0200 hrs. This observation is consistent with the other studies on plasma bubbles so far. The average depth of the depletion was found to be about 3.31 meters of propagation delay while the strongest depletion corresponds to about 5.04 meters of delay. The latter observation impresses upon the need to detect and study the phenomenon of depletion since it is capable of causing a significant loss of accuracy and reliability to the system. The duration of the depletion was found to range from about 10 min to 2.35 hours. In addition, a statistical study of the relationship among the different parameters and a study devoted to now-casting of depletion was made to get a more quantitative insight into the phenomenon of depletion. Scintillation is another phenomenon occurring in the ionosphere which causes rapid fluctuations of phase and amplitude of the signal due to TEC variations in the ionosphere. The occurrences of depletion were observed to be accompanied by scintillation, as also noted in previous studies. The correlation of depletion and scintillation was studied using the data available for this research. A spatial characterization of the depletion events was also investigated using the same temporal TEC data from neighbouring stations which were relatively close to each other. This study addressed the movement of the plasma bubble with respect to the advection speed and direction with definite results. Attention was also devoted to the spatial dimension of the bubble as observed from various stations. Contributions to this variability in the apparent spatial extent comes from the observation of the depletion event from varying lines-of-sight corresponding to different GPS satellites which are also moving, and the differential `slicing' effect because of the location of the stations with respect to the plasma bubble, in addition to the evolution of the bubble during transit. The detection of depletion and its temporal characterization, in addition to the knowledge of its spatial extent and motion, can provide very useful insights on the behaviour of a depletion event and over the ionosphere in general. This knowledge and the mechanism for detection can help to improve the quality and dependability of the information provided by SBAS systems, in particular the Indian GAGAN system, for improved navigation in this part of the world. The present thesis aims to make a significant contribution in this direction.

Satellites have revolutionized navigation by making it more universal, accessible and ac- curate. Global Positioning System (GPS) is the most widely used satellite navigation system in the world. However, it is prone to errors from various sources such as the ionosphere, troposphere and clock biases. In order to make the system very accurate and reliable, especially to meet the requirements of safety-critical applications, Satellite Based Augmentation Systems (SBAS) have recently been designed in various countries to augment the GPS by providing corrections for its errors. An Indian SBAS called GAGAN (GPS Aided Geo Augmented Navigation), developed for the Airports Authority of India (AAI) by Indian Space Research Organization (ISRO) is currently being installed and proven for aviation and other use. The uncertain propagation delay of signals through the ionosphere is the most important contributor of error in GPS positioning, its maximal elimination is a major task of SBAS overlays. Ionospheric delays have steady, cyclic, and irregular components. The last types are of particular concern because they are unpredictable. This thesis deals with ionospheric depletion, an important phenomenon of this class that is specific to tropical regions like India and hence have not been well studied in the context of other SBAS systems of the world which cover mid-latitude domains. Depletion is an ionospheric phenomenon in which the density of electrons dips suddenly and then returns close to the previous value. It poses a challenge to the model adopted for ionospheric delay estimation since it may not be detectable by ground systems be- cause of its localized nature, and its occurrence and intensity cannot be predicted. In this work we have analyzed the depletion characteristics over the Indian region such as its distribution, frequency of occurrence, and depth and duration parameters. We have then studied and implemented an existing algorithm to detect a depletion from the Total Electron Content (TEC) data. This algorithm has been found to be inaccurate for estimation of depletion duration, and we have proposed an improved algorithm for depletion detection and shown it to be more suitable for the Indian SBAS, GAGAN. The algorithm utilizes multiple thresholds for depletion detection in order to improve performance in the presence of irregularities including noise. These thresholds are determined by analyzing real TEC data containing depletion events over the Indian region. The detected depletion events are those that have a strong likelihood of contributing large range errors and degrading GAGAN's reliability. The thresholds include depletion parameters such as the depth, duration, rate of change of TEC, and the rate of change of slope of the TEC curve. The characterization of depletion events over the Indian region yielded useful insights into the behaviour of the phenomenon. It was observed that the depletion events were invariably present post-sunset, between 1900 and 0200 hrs. This observation is consistent with the other studies on plasma bubbles so far. The average depth of the depletion was found to be about 3.31 meters of propagation delay while the strongest depletion corresponds to about 5.04 meters of delay. The latter observation impresses upon the need to detect and study the phenomenon of depletion since it is capable of causing a significant loss of accuracy and reliability to the system. The duration of the depletion was found to range from about 10 min to 2.35 hours. In addition, a statistical study of the relationship among the different parameters and a study devoted to now-casting of depletion was made to get a more quantitative insight into the phenomenon of depletion. Scintillation is another phenomenon occurring in the ionosphere which causes rapid fluctuations of phase and amplitude of the signal due to TEC variations in the ionosphere. The occurrences of depletion were observed to be accompanied by scintillation, as also noted in previous studies. The correlation of depletion and scintillation was studied using the data available for this research. A spatial characterization of the depletion events was also investigated using the same temporal TEC data from neighbouring stations which were relatively close to each other. This study addressed the movement of the plasma bubble with respect to the advection speed and direction with definite results. Attention was also devoted to the spatial dimension of the bubble as observed from various stations. Contributions to this variability in the apparent spatial extent comes from the observation of the depletion event from varying lines-of-sight corresponding to different GPS satellites which are also moving, and the differential `slicing' effect because of the location of the stations with respect to the plasma bubble, in addition to the evolution of the bubble during transit. The detection of depletion and its temporal characterization, in addition to the knowledge of its spatial extent and motion, can provide very useful insights on the behaviour of a depletion event and over the ionosphere in general. This knowledge and the mechanism for detection can help to improve the quality and dependability of the information provided by SBAS systems, in particular the Indian GAGAN system, for improved navigation in this part of the world. The present thesis aims to make a significant contribution in this direction.