103 citations · 251 across the 14 of their papers we have counts for
15 papers
On the validity of using the delta method for calculating the uncertainty of the predictions from an overparameterized model
Magnus Malmström, Isaac Skog, Daniel Axehill +1
The uncertainty in the prediction calculated using the delta method for an overparameterized (parametric) black-box model is shown to be larger or equal to the uncertainty in the p…
Tightly Integrated Motion Classification and State Estimation in Foot-Mounted Navigation Systems
Isaac Skog, Gustaf Hendeby, Manon Kok
A framework for tightly integrated motion mode classification and state estimation in motion-constrained inertial navigation systems is presented. The framework uses a jump Markov…
Uncertainty quantification in neural network classifiers -- a local linear approach
Magnus Malmström, Isaac Skog, Daniel Axehill +1
Classifiers based on neural networks (NN) often lack a measure of uncertainty in the predicted class. We propose a method to estimate the probability mass function (PMF) of the dif…
Iterated Filters for Nonlinear Transition Models
Anton Kullberg, Isaac Skog, Gustaf Hendeby
A new class of iterated linearization-based nonlinear filters, dubbed dynamically iterated filters, is presented. Contrary to regular iterated filters such as the iterated extended…
Inertial Navigation Using an Inertial Sensor Array
Håkan Carlsson, Isaac Skog, Gustaf Hendeby +1
We present a comprehensive framework for fusing measurements from multiple and generally placed accelerometers and gyroscopes to perform inertial navigation. Using the angular acce…
Online Joint State Inference and Learning of Partially Unknown State-Space Models
Anton Kullberg, Isaac Skog, Gustaf Hendeby
A computationally efficient method for online joint state inference and dynamical model learning is presented. The dynamical model combines an a priori known, physically derived, s…
Fifteen Years of Progress at Zero Velocity: A Review
Johan Wahlström, Isaac Skog
Fifteen years have passed since the publication of Foxlin's seminal paper "Pedestrian tracking with shoe-mounted inertial sensors". In addition to popularizing the zero-velocity up…
Learning Driver Behaviors Using A Gaussian Process Augmented State-Space Model
Anton Kullberg, Isaac Skog, Gustaf Hendeby
An inference method for Gaussian process augmented state-space models are presented. This class of grey-box models enables domain knowledge to be incorporated in the inference proc…
Zero-Velocity Detection - A Bayesian Approach to Adaptive Thresholding
Johan Wahlström, Isaac Skog, Fredrik Gustafsson +2
A Bayesian zero-velocity detector for foot-mounted inertial navigation systems is presented. The detector extends existing zero-velocity detectors based on the likelihood-ratio tes…
Map-aided Dead-reckoning --- A Study on Locational Privacy in Insurance Telematics
Johan Wahlström, Isaac Skog, João G. P. Rodrigues +2
We present a particle-based framework for estimating the position of a vehicle using map information and measurements of speed. Two measurement functions are considered. The first…
The -model for Random Graphs --- Regression, Cramér-Rao Bounds, and Hypothesis Testing
Johan Wahlström, Isaac Skog, Patricio S. La Rosa +2
We develop a maximum-likelihood based method for regression in a setting where the dependent variable is a random graph and covariates are available on a graph-level. The model gen…
Smartphone-based Vehicle Telematics - A Ten-Year Anniversary
Johan Wahlström, Isaac Skog, Peter Händel
Just like it has irrevocably reshaped social life, the fast growth of smartphone ownership is now beginning to revolutionize the driving experience and change how we think about au…
Inertial Sensor Arrays, Maximum Likelihood, and Cramér-Rao Bound
Isaac Skog, John-Olof Nilsson, Peter Händel +1
A maximum likelihood estimator for fusing the measurements in an inertial sensor array is presented. The maximum likelihood estimator is concentrated and an iterative solution meth…
Cooperative localization by dual foot-mounted inertial sensors and inter-agent ranging
John-Olof Nilsson, Dave Zachariah, Isaac Skog +1
The implementation challenges of cooperative localization by dual foot-mounted inertial sensors and inter-agent ranging are discussed and work on the subject is reviewed. System ar…
Bayesian Estimation with Distance Bounds
Dave Zachariah, Isaac Skog, Magnus Jansson +1
We consider the problem of estimating a random state vector when there is information about the maximum distances between its subvectors. The estimation problem is posed in a Bayes…