FPGA implementation of sigma-point class of non-linear Gaussian filters, namely Unscented Kalman Filter (UKF), Cubature Kalman Filter (CKF), Cubature Quadrature Kalman Filter (CQKF) and Gauss Hermite Filter (GHF). Currently targeted towards Xilinx Zynq-7000 (ZC702) and Digilent Nexys4 DDR boards.
The intuition behind sigma-point class of filters is founded on the principle that it is easier to approximate a probability distribution than it is to approximate an arbitrary non-linear function or transformation. The members of this class of filters accomplish the approximation of a probability distribution by deterministically "sampling" support points (called sigma points) and assigning weight to each of these points. The mean and covariance can then be computed based on the statistics of these "sigma" points.
The implementation uses proprietary Xilinx IP for now and they come with their own set of copyright notices. The aim is to move away from proprietary IP and switch to open-source alternatives.
This work is done, under the supervision of Dr Shovan Bhaumik (Associate Professor, Dept of Electrical Engineering, Indian Institute of Technology Patna), for the partial fulfilment of requirements towards the award of a Bachelors degree. Please feel free to get in touch with the author, Hatim Kanchwala me@hatimak.me, for any details.