GNC (Guidance, Navigation, and Control) is a niche field of engineering. Not many students know about it… or are even exposed to it. In my humble opinion, it’s where the cool kids work.
So what is GNC? If you look it up, you’ll find that each subteam focuses on a different aspect of the mission.
Navigation engineers use the sensors to figure out where the system is, its position, velocity, attitude, etc. This is where sensor modeling and sensor fusion (Kalman filters 👀) come into play. You’re taking messy, noisy sensor data, IMU, GPS, star trackers, and estimating the actual state of the vehicle in real time.
Guidance engineers figure out the path or trajectory. Basically: where are we trying to go and how should we get there? In aerospace, astrodynamics is very crucial here. This is trajectory design, waypoint planning, orbital transfers, deciding the desired position, velocity, or orientation over time.
Control engineers… the house I live in.
This is where you actually make the system move. Guidance says where it needs to go. Navigation says where it currently is. Control compares the two and sends commands to thrusters, motors, control surfaces, and keeps adjusting using feedback so the system follows the plan.
So, if you’re interested in pursuing a career in GNC, here are three projects you can try… either as personal projects or expand into a senior design project, to build your resume and strengthen your skills.
Attitude Control Simulator:
Develop a 3-axis attitude control simulator with PID/LQR regulators in Python to stabilize simulated spacecraft/UAV dynamics.
Resources:
- Satellite Attitude Control Design with MATLAB, Simulink, FlightGear
- What is Flight Dynamics?
- Control Systems Lectures – Closed Loop Control
- Guidance, Navigation and Control System Design
Kalman Filter Design:
Implement an Extended Kalman Filter for simulated sensor fusion to estimate vehicle state with noisy IMU and GPS data.
Resources:
- Kalman Filters Explained by Brian Douglas
- The Kalman Filter [Control Bootcamp] – Steven Brunton
- How to Implement a Kalman Filter in Simulink
- Discrete MIMO Kalman Filter Design and Implementation
Embedded Controls Project:
Build a real embedded closed-loop control system using an Arduino (or similar microcontroller) that reads sensor data, compares it to a desired setpoint, implements a PID feedback controller, drives an actuator, and tunes performance based on system response.
Resources:
EngineersTeaTime 
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