Statistical Similarity Measure-Based Adaptive Outlier-Robust State Estimator With Applications
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Automatic Control"
DOI: 10.1109/tac.2022.3176837
Abstract: This article presents an adaptive outlier-robust state estimator (AORSE) under the statistical similarity measures (SSMs) framework. Two SSMs are first proposed to evaluate the similarities between a pair of positive definite random matrices and between… read more here.
Keywords: state; statistical similarity; robust state; adaptive outlier ... See more keywords
A Sliding Window Variational Outlier-Robust Kalman Filter Based on Student’s t-Noise Modeling
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Aerospace and Electronic Systems"
DOI: 10.1109/taes.2022.3164012
Abstract: Existing robust state estimation methods are generally unable to distinguish model uncertainties (state outliers) from measurement outliers as they only exploit the current measurement. In this article, the measurements in a sliding window are, therefore,… read more here.
Keywords: robust kalman; kalman filter; variational outlier; sliding window ... See more keywords
Innovative And Additive Outlier Robust Kalman Filtering With A Robust Particle Filter
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Transactions on Signal Processing"
DOI: 10.1109/tsp.2021.3125136
Abstract: In this paper, we propose CE-BASS, a particle mixture Kalman filter which is robust to both innovative and additive outliers, and able to fully capture multi-modality in the distribution of the hidden state. Furthermore, the… read more here.
Keywords: outlier robust; innovative additive; particle; robust kalman ... See more keywords
Sparse Stable Outlier-Robust Signal Recovery Under Gaussian Noise
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Signal Processing"
DOI: 10.1109/tsp.2023.3244082
Abstract: This paper presents a novel framework for sparse robust signal recovery integrating the sparse recovery using the minimax concave (MC) penalty and robust regression called sparse outlier-robust regression (SORR) using the MC loss. While the… read more here.
Keywords: noise; sparse; outlier robust; robust signal ... See more keywords