139 citations · 364 across the 10 of their papers we have counts for
13 papers
3D angle-of-arrival positioning using von Mises-Fisher distribution
Henri Nurminen, Laura Suomalainen, Simo Ali-Löytty +1
We propose modeling an angle-of-arrival (AOA) positioning measurement as a von Mises-Fisher (VMF) distributed unit vector instead of the conventional normally distributed azimuth a…
Damped Posterior Linearization Filter
Matti Raitoharju, Lennart Svensson, Ángel F. García-Fernández +1
The iterated posterior linearization filter (IPLF) is an algorithm for Bayesian state estimation that performs the measurement update using iterative statistical regression. The ma…
Automatic numerical differentiation by maximum likelihood estimation of state-space model
Robert Piche
A linear Gaussian state-space smoothing algorithm is presented for estimation of derivatives from a sequence of noisy measurements. The algorithm uses numerically stable square-roo…
Skew-t Filter and Smoother with Improved Covariance Matrix Approximation
Henri Nurminen, Tohid Ardeshiri, Robert Piché +1
Filtering and smoothing algorithms for linear discrete-time state-space models with skew-t-distributed measurement noise are proposed. The algorithms use a variational Bayes based…
Skew-t inference with improved covariance matrix approximation
Henri Nurminen, Tohid Ardeshiri, Robert Piche +1
Filtering and smoothing algorithms for linear discrete-time state-space models with skew-t distributed measurement noise are presented. The proposed algorithms improve upon our ear…
Kullback-Leibler Divergence Approach to Partitioned Update Kalman Filter
Matti Raitoharju, Ángel F. García-Fernández, Robert Piché
Kalman filtering is a widely used framework for Bayesian estimation. The partitioned update Kalman filter applies a Kalman filter update in parts so that the most linear parts of m…