Ionospheric Delay Estimation during Ionospheric Depletion Events for Single Frequency Users of IRNSS

The IRNSS (Indian Regional Navigation System) navigation users estimate their position by using a receiver which receives the navigation signal from the IRNSS satellites which will be operating on L5 (1176.45MHz) and S (2492.028MHz) frequencies. There are 3 types of IRNSS users: 1) Dual frequency (L5 and S), 2) Single frequency (L5) and 3) Single frequency (S). The signal from the satellites before reaching the user receiver passes through the ionospheric layer of the atmosphere and suffers a delay. The delay in the signal introduces error in the position computed by the user. The dual frequency users of IRNSS correct the ionospheric error by taking advantage of the dispersive nature of ionosphere. On the other hand, single frequency user requisite an algorithm for computing the ionospheric delay along his line of sight. In IRNSS, the ionospheric error corrections for single frequency (L5 or S) users will be provided by two ways: 1) Grid based and 2) Coefficient based. These corrections may not be valid when an abnormal behavior of ionosphere occurs due to geomagnetic storm, solar coronal mass ejections or any other disturbances in the earth’s magnetic field. The abnormal behavior may result in increase or decrease of the TEC (Total Electron Content) in the ionosphere. Ionospheric depletion event is one such, where there is a sudden drop in TEC forming plasma bubbles travelling through the ionosphere. A user, whose line-of-sight when crosses such a TEC depleted area of ionosphere suffers from an extra error due to depletion. The amount of error is proportional to the depth of depletion. This error in the range ultimately results in the user position accuracy degradation. In this paper a novel algorithm has been designed and developed which will estimate the ionospheric delay, thereby providing ionospheric corrections even at times of depletions. The developed technique in turn provides achievable position accuracy during times of ionospheric depletions. The developed technique has been tested with GAGAN (GPS Aided GEO Augmented Navigation) INRES (Indian Reference Stations) data and IRNSS IRIMS (IRNSS Range and Integrity Monitoring Stations) data having deep ionospheric depletions. The fully tested and validated ionospheric delay estimation algorithm is proposed to be implemented in IRNSS single frequency (L5/S) receivers. Keywords: IRNSS Single Frequency User, Ionospheric Error, Ionospheric Depletion, Ionospheric Delay Estimation, Kalman Filte

IRNSS/NavIC and GPS: a single- and dual-system L5 analysis

The Indian Regional Navigation Satellite System (IRNSS) has recently (May 2016) become fully operational. In this contribution, for the fully operational IRNSS as a stand-alone system and also in combination with GPS, we provide a first assessment of L5 integer ambiguity resolution and positioning performance. While our empirical analyses are based on the data collected by two JAVAD receivers at Curtin University, Perth, Australia, our formal analyses are carried out for various onshore locations within the IRNSS service area. We study the noise characteristics (carrier-to-noise density, measurement precision, time correlation), the integer ambiguity resolution performance (success rates and ambiguity dilution of precision), and the positioning performance (ambiguity float and ambiguity fixed). The results show that our empirical outcomes are consistent with their formal counterparts and that the GPS L5-data have a lower noise level than that of IRNSS L5-data, particularly in case of the code data. The underlying model in our assessments varies from stand-alone IRNSS (L5) to IRNSS (Formula presented.) GPS (L5), from unconstrained to height-constrained and from kinematic to static. Significant improvements in ambiguity resolution and positioning performance are achievable upon integrating L5-data of IRNSS with GPS

The efficiency of natural antibacterials

Chemical filled antibacterials are used daily in every household. These antibacterials have many health risks that most consumers do not know about. This experiment strives to create natural antibacterials that are beneficial for all consumers

Modern Business Data Analysis and Data Visualization: A Real-Time Fusion Study

In contemporary data science and analytics, data clustering is a small bucket that divides computation among various child nodes. The network’s capacity, specialized tools, and applications that cannot be trained quickly are among these methods’ drawbacks. In addition, the IoT-formed Big Data raw data can result in highly heterogeneous and unstructured data. This kind of data is difficult to analyze for real-time analytics. Real-time analytical challenges can be reduced by making computational values available locally rather than via distributed resources. Most of the time, it takes a long time and a lot of money to run these teams and skill sets. As an alternative, provide tools that let end users, professionals in the industry, and data scientists directly create and deploy complex data analytics application solutions with less technical knowledge. It highlights key advantages, disadvantages, and potential future directions by contrasting various current research and practice approaches to assisting end users with data analytics

Single frequency ionospheric error correction using coefficients generated from regional ionospheric data for IRNSS

125-130Indian Regional Navigation Satellite System (IRNSS) is the satellite based navigation system being developed by India for locating user’s position in 3-dimensional space and time over IRNSS service area. The users estimate their position by using a receiver which receives the navigation signal from the IRNSS satellites which is operating on L5 (1176.45 MHz) and S (2492.028 MHz) frequencies. There are three types of IRNSS users: dual frequency (L5 and S); single frequency (L5); and single frequency (S). The signal from the satellites before reaching the user receiver passes through the ionospheric layer of the atmosphere and suffers a delay. The delay in the signal introduces error in the position computed by the user. The dual frequency users of IRNSS correct the ionospheric error by taking advantage of the dispersive nature of ionosphere. On the other hand, single frequency user requisite an algorithm for computing the ionospheric delay along his line-of-sight. In IRNSS, the ionospheric error correction for single frequency (L5 or S) user is provided through a set of eight ionospheric coefficients. These coefficients are computed on ground by using previous 24-hour data and broadcasted as secondary navigation parameters (messages) to the user. These corrections are available for any user in the primary service area (extending up to 1500 km from Indian boundary) of IRNSS with a validity period of one day. The algorithm designed and developed for the estimation of these coefficients is explained in this paper which uses the global ionospheric model based on cosine curve approximation of diurnal variation of ionospheric delay. The estimation technique has been tested initially with simulated data and then with measurement driven model data for days of different ionospheric activity. The results are promising when compared with GPS transmitted Klobuchar coefficients over IRNSS primary service area. This algorithm is a part of the IRNSS navigation software which is operational at IRNSS Navigation Center (INC), Bangalore