Implementation of new navigation algorithm based on cross-correntropy for precise positioning in low latitude regions of South India

Autor: V. B. S. Srilatha Indira Dutt, L. Ganesh, P. Sirish Kumar
Rok vydání: 2020
Předmět:
Zdroj: International Journal of Speech Technology. 23:747-756
ISSN: 1572-8110
1381-2416
DOI: 10.1007/s10772-020-09727-6
Popis: The objective of this article is to develop a new positioning algorithm to estimate the position accurately in low latitude region and assess the algorithm’s performance in terms of accuracy and precision. The Kalman Filter (KF) has been widely recognized as one of the most powerful state estimation techniques in estimating system state variables and suppressing measurement noise. The Kalman Filter is desirable because the uncertainty in the Minimum Mean Square Error (MMSE) estimation can be minimized. In this article, we implemented a new algorithm called as Cross-Correntropy Kalman Filter (CCKF) to enhance the position accuracy and performance of the GPS receiver. Primarily the improvement depends on the Cross-Correntropy criterion which is a measure of local similarity, and a novel Fixed-Point algorithm for updating subsequent estimates. In this work, we present a thorough derivation of the method suggested, how to accurately measure the estimate of the GPS receiver position. Furthermore, in tabular forms, we provide a comparison of receiver position error (X, Y, Z coordinates) and performance metrics (2-D & 3-D) together with graphical representations for both algorithms (KF & CCKF).
Databáze: OpenAIRE
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