A fair amount of iterative testing goes into developing interconnected guidance, navigation, and control systems. While nothing can replace the insight that comes from testing the interconnected system, actual algorithm development for each sub-system is better done in isolation. For
Hamid Mokhtarzadeh
Hamid is Principal Navigation Engineer at Organic Navigation and has expertise in sensor fusion, navigation systems, and custom engineering software tools.
Getting Started: GNC Analysis with Python
Easily process IMU data from your browser using imuengine.io All you need to write Python code is a text editor. Similar to the extension .c or .m for C or MATLAB code, respectively, python code source files are saved
Python for Engineering and Science
This post kicks off a series about software. I present a set of open-source Python-based tools which enable powerful functionality in computation, programming, and visualization. Before starting I think it is important to address one question: How is this relevant
Accelerometer Performance: 3, 6, or 9-Axis Sensors?
Easily process IMU data from your browser using imuengine.io Combined Functionality: What do you lose? There is a trend towards combining hardware components and even processors into single chips. This is certainly true for inertial sensors: * 3-axis: accelerometer only
Accelerometer Impact: Simple Task in, Rich Signal out
Easily process IMU data from your browser using imuengine.io A Tale of Two Unknowns Sensors are used to measure information that are not readily available or known. So after picking a new sensor for this task, you now have
Adding Time for Offline Analysis
If things were systematic and clean, the process of going from an idea to a working prototype may be: 1. Based on idea, decide on candidate hardware and algorithm 2. Log data with the candidate hardware 3. Process and work