Innovators at NASA's Johnson Space Center have developed a suite of libraries around which a Kalman filter can be designed for research or real-time applications. The Generic Kalman Filter (GKF) provides all the functionality of a Kalman filter, including state and variance/co-variance matrix propagation and measurement updating, while allowing a user to define subroutines for particular problems. The innovation uses a library of trusted subroutines to handle the mundane functions that are common to all Kalman filters. This generic quality allows for flexibility and fast start-up speed for the creation of a new filter. The suite consists of the GKF software library, the GKF header file, and template GKF user-implementation starter code providing examples of both calling functions and filter subfunctions. The subroutines are written in the C programming language and are designed with general filter structures in an object-oriented manner. This software may be released to U.S. persons only.
- Fast: Reduces development time and effort compared with custom-coding of filter algorithms
- Economical: Enables use of off-the-shelf software components for projects that require multiple Kalman filters or filter versions
- Versatile: Allows a user to easily test various types of tuning parameters, time update algorithms, or measurement update algorithms when designing a filter
- Production or simulation navigation systems for real-time applications
- Scientific studies where data are an input and estimated parameters are an output
This technology is being made available through JSC's Technology Transfer and Commercialization Office, which seeks to transfer technology into and out of NASA to benefit the space program and U.S. industry. NASA invites companies to consider licensing this technology for commercial applications.
If you would like more information about this technology or about NASA's technology transfer program, please contact:
Technology Transfer and Commercialization Office
NASA's Johnson Space Center