3 citations · 3 across the 10 of their papers we have counts for
11 papers
Multi-Target Tracking of Cooperating Swarms by an Ensemble Gaussian Mixture Filter
Zain Jabbar, Andrey A. Popov
Per-target labeled random-finite-set filters, such as the state of the art -generalized labeled multi-Bernoulli filter, cannot represent cooperating, swarm-like, motion between…
Unbiased estimation of squared concentration in the Fisher-von Mises-Langevin distribution and the impossibility of unbiased concentration
Zain Jabbar, Yuqin Jiang, Andrey A. Popov
The estimation of concentration parameter in Fisher-von Mises-Langevin distribution is the directional statistics analogue of the estimation of the precision matrix for the Gaussia…
Pose Tracking with a Foundation Pose Model and an Ensemble Directional Kalman Filter
Tianlu Lu, Asif Sijan, Thomas Noh +2
This paper introduces the ensemble directional Kalman filter (EnDKF), an ensemble-based Kalman filtering approach for pose tracking that jointly estimates an object's position and…
Learning Discriminators for Resampling in the Ensemble Gaussian Mixture Filter through a Normalizing Flow Approach
Zain Jabbar, Andrey A. Popov
The ensemble Gaussian mixture filter (EnGMF) is a powerful, convergent particle filter capable of medium-to-high dimensional non-linear filtering. The EnGMF relies on a resampling…
Learning to Trust AI and Data-driven models in Data Assimilation through a Multifidelity Ensemble Gaussian Mixture Filter Framework
Andrey A. Popov
AI and data-driven models have large potential for data assimilation applications by creating fast and accurate forecasts. Their tendency to produce spurious inaccurate, nonphysica…
A divide and conquer strategy for multinomial particle filter resampling
Andrey A. Popov
This work provides a new multinomial resampling procedure for particle filter resampling, focused on the case where the number of samples required is less than or equal to the size…
Deterministic Optimal Transport-based Gaussian Mixture Particle Filtering for Verifiable Applications
Andrey A Popov, Renato Zanetti
Mixture-model particle filters such as the ensemble Gaussian mixture filter require a resampling procedure in order to converge to exact Bayesian inference. Canonically, stochastic…
The Ensemble Epanechnikov Mixture Filter
Andrey A. Popov, Renato Zanetti
In the high-dimensional setting, Gaussian mixture kernel density estimates become increasingly suboptimal. In this work we aim to show that it is practical to instead use the optim…
What are You Weighting For? Improved Weights for Gaussian Mixture Filtering With Application to Cislunar Orbit Determination
Dalton Durant, Andrey A. Popov, Renato Zanetti
This work focuses on the critical aspect of accurate weight computation during the measurement incorporation phase of Gaussian mixture filters. The proposed novel approach computes…
Precision Mars Entry Navigation with Atmospheric Density Adaptation via Neural Networks
Felipe Giraldo-Grueso, Andrey A. Popov, Renato Zanetti
Spacecraft entering Mars require precise navigation algorithms capable of accurately estimating the vehicle's position and velocity in dynamic and uncertain atmospheric environment…
Bayesian Recursive Update for Ensemble Kalman Filters
Kristen Michaelson, Andrey A. Popov, Renato Zanetti
Few real-world systems are amenable to truly Bayesian filtering; nonlinearities and non-Gaussian noises can wreak havoc on filters that rely on linearization and Gaussian uncertain…