Abstract
Precise positioning and robust surveillance systems are essential to safeguard countries like India with a long geographical border and an extensive coastline. This has led to the development and evolution of numerous such systems. Some of these system’s real-world applications include aviation, marine, mining, military, medicine, and agriculture. A global positioning system can provide a 3-D position of the unknown object on or above the earth’s surface. Inherently, in GPS pseudo-range measurements, several errors are resulting from various error sources. This article implemented three navigational algorithms, namely, the Least Square Estimator (LSE), Kalman Filter (KF), and Correntropy Kalman Filter (CKF), and the results are compared. The results show that the GPS data follow the Gaussian distribution and how the GPS uncertainties are distributed in the 1-dimensional surface concerning X, Y, Z directions.
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Srilatha Indira Dutt, V.B.S., Sirish Kumar, P., Krishna Rao, P. (2022). Statistical Distribution of GPS Uncertainties Over Low Latitude Regions of India. In: Das, A.K., Nayak, J., Naik, B., Dutta, S., Pelusi, D. (eds) Computational Intelligence in Pattern Recognition . Advances in Intelligent Systems and Computing, vol 1349. Springer, Singapore. https://doi.org/10.1007/978-981-16-2543-5_13
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DOI: https://doi.org/10.1007/978-981-16-2543-5_13
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