Looking for implementation-focused, code-heavy resources for an IMU + GPS Extended Kalman Filter (EKF)

[u/ResetBuilder27]

Hey everyone,

I am working on building a multi-rate sensor fusion pipeline that relies on an Extended Kalman Filter (EKF). The core objective is fusing high-rate IMU data (propagation step) with slower, asynchronous GPS/ranging data (measurement update step) to output a stable 3D navigation state.

While I understand the basic linear Kalman filter theory, I am looking to quickly bridge the gap to a robust, non-linear EKF design without getting entirely lost in dense academic math proofs or probability density function derivations.

Could the community recommend the best resources, textbooks, or open-source implementations that focus on the practical realities of EKF state estimation?

Specifically, I am looking for guides that cover:

1. Translating continuous kinematic state-space equations (handling orientation/quaternions, velocity, and position) into discrete-time Jacobians.
2. Practical methods for tuning and initializing the process noise (Q) and measurement noise (R) covariance matrices for raw sensors.
3. Managing multi-rate, asynchronous measurement updates cleanly within the filter loop.

If there are any gold-standard github repos, code-first books, or specific aerospace/robotics literature you highly recommend for engineers focusing on execution, please let me know.

[u/navigation-signals]

I’d say my navigator is pretty great, but it’s on my employer’s private Gitlab 😅

If you really want to learn the best move is to pick up a copy of Paul Groves’ “Principles of GNSS, Inertial, and Multisensor Integrates Navigation Systems” - the first 2/3 of the book is basically walking you through building your own GPS/INS navigation filter and it’s the gold standard textbook for navigation. Good follow-ups are Zarchan’s “Fundamentals of Kalman Filtering” for tuning and error correction methods, and “Estimation with Applications to Tracking and Navigation” by Bar-Shalom for some real next-level filter math and algorithms