Implementing the Unscented Kalman Filter on an embedded system: A lesson learnt

The development process of an Unscented Kalman Filter (UKF) in an embedded platform for navigation purposes is presented in this work. This type of filter is usually executed in real-time, therefore high processing speed is required. The authors outline the steps followed to allow the use of a cheap microcontroller unit to implement a full state UKF at a maximum frequency of about 200 Hz. Some important parts of the developed algorithm are explained in order to make clear where the computational bottlenecks are. This work can be used as an inspiring experience for other implementations, providing a guide to develop and deploy a complex algorithm into a microprocessor. Two different microprocessing architectures are proposed to explain some platform-dependent optimisations. These platforms are a Digital Signal Processor (DSP) and an ARM microcontroller. General advices and hardware-oriented optimisations are presented in order to reach the execution time reduction achieved in this paper. In this paper are shown the results of the improvements done in both platforms and the minimum requirements are listed as a conclusion.