Author: eyzhang

This week, I focused on beginning implementation of the Extended Kalman Filter for our positioning system. I set up the filter structure in code, including the state representation, prediction step using IMU acceleration, and covariance propagation. I also started implementing the measurement update step that will incorporate celestial position estimates to correct inertial drift. Currently, I am testing the filter framework using simulated data to verify that the prediction and update steps behave correctly.

My progress is on schedule. The main goal for this phase was to begin coding the estimation algorithm, and I now have the core filter structure in place.

Next week, I plan to complete testing of the filter, tune the noise parameters, and prepare the implementation to accept real IMU and celestial solver data once the hardware is ready.

This week, I focused on developing the estimation framework for our celestial positioning module. Specifically, I designed the structure of our Kalman Filter based state estimator and formalized the mathematical model for fusing IMU acceleration with celestial position outputs. I worked through both 2D and 3D formulations and decided that a full 3D state representation is needed to properly handle gravity projection and tilt induced drift. I derived the continuous and discrete time process models for position and velocity propagation using accelerometer measurements.

My progress is currently on schedule. This week was intended for algorithm development and mathematical groundwork before the implementation. The derivations are complete at a conceptual level, and I am ready to begin coding to validate filter behavior before hardware integration.

This week, I prepared and presented our proposal, achieving a much deeper understanding of our project as a whole. Additionally, I learned more in-depth about Kalman Filters and state estimators. This is important because our project requires the aggregation of different sensor data to achieve location prediction.

My progress is on schedule since my background knowledge will allow me to start planning our algorithm and how our project will fit into the algorithms. By next week, I expect to have written out algorithms specific to our project.