A Scalable, FPGA-Based Implementation of the Unscented Kalman Filter

Abstract

Autonomous aerospace systems may well soon become ubiquitous pending an increase in autonomous capability. Greater autonomous capability means there is a need for high-performance state estimation. However, the desire to reduce costs through simplified development processes and compact form factors can limit performance. A hardware-based approach, such as using a field-programmable gate array (FPGA), is common when high performance is required, but hardware approaches tend to have a more complicated development process when compared to traditional software approaches; greater development complexity, in turn, results in higher costs. Leveraging the advantages of both hardware-based and software-based approaches, a hardware/software (HW/SW) codesign of the unscented Kalman filter (UKF), based on an FPGA, is presented. The UKF is split into an application-specific part, implemented in software to simplify the development process, and a non-application-specific part, implemented in hardware as a parameterisable ‘ black box ’ module (i.e. IP core) to increase performance. Simulation results demonstrating a possible nanosatellite application of the design are presented; implementation (synthesis, timing, power) details are also presented.