Extended Kalman Filter (EKF) and Global Positioning System (GPS) Algorithms

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Resource Overview

This ZIP file contains fundamental principles and concise documentation for both Extended Kalman Filter (EKF) and Global Positioning System (GPS) algorithms. The primary objective is to provide a relatively straightforward EKF implementation that processes input functions directly rather than handling complex symbolic expressions. It serves as an introductory guide to Kalman filtering algorithms for GPS applications, facilitating deeper understanding of their underlying concepts. The EKF demonstration includes source materials comparing positioning solutions using both Extended Kalman Filter and Least Squares methods. The package comprises four MATLAB M-files and two data files, where Extended_KF.m contains the core EKF function implementation alongside supplementary functions and GPS sample data files.

Detailed Documentation

This documentation accompanies a ZIP file containing fundamental principles and concise explanations for both Extended Kalman Filter (EKF) and Global Positioning System (GPS) algorithms. These algorithms are designed to provide a relatively accessible EKF implementation that processes input functions directly, avoiding the complexity of symbolic expression handling. Additionally, this documentation serves as a brief introduction to Kalman filtering algorithms and GPS technology, enabling better comprehension of their theoretical foundations and practical implications.

For the EKF demonstration, we provide source materials that compare positioning solutions using both Extended Kalman Filter and Least Squares methods. Specifically, the package includes four MATLAB M-files and two data files. The Extended_KF.m file contains the main EKF function body implementing the prediction and correction steps, while other files contain auxiliary functions and GPS sample data sets. This documentation aims to enhance understanding of these algorithms and provide valuable reference materials for further study and implementation.

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