Performance Improvement of Navic Signal Using Real-time Filtering Techniques

Abstract

The Indian Regional Navigational Satellite System [IRNSS] is India's own indigenous navigation system. Its purpose is to offer precise positional information to users in India as well as the surrounding region, which extends up to 1500 kilometers outside the country's borders. Satellite geometry, signal reception delays induced by the ionosphere and troposphere, multipath doppler effect produced by relative motion clock drift, and receiver noise all affect the positioning accuracy of a satellite-based navigation system. The ionosphere's influence surpasses all the preceding factors since even a slight delay in the signal has a significant impact on the user's position. Different methods, such as dual frequency methods, differential correction approaches, and various single frequency ion delay models, are used to alleviate ionosphere delays. In the proposed work Kalman filter is applied to correct the positioning errors [1]. The suggested method's performance in an urban setting is examined using real-time data obtained by a Global Navigation Satellite System (GNSS) receiver. Both static and dynamic data is used to analyse the performance of the proposed method. In the position domain the results are evaluated using the parameters - Percentage Fit Error and Mean Absolute Error [2]. The lost path during reception is regenerated using linear interpolation function. The simulation results obtained show that the proposed Kalman filter algorithm in combination with interpolation significantly improves accuracy of tracking in real-time.