# A Drift Homotopy Implicit Particle Filter Method for Nonlinear Filtering problems

arXiv: https://arxiv.org/abs/2106.11380 · HTML: https://mlsanity.com/paper/2106.11380/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 Jun 2021.

## Built on by (most cited first, 1 of 1)

- [State Estimation Using Particle Filtering in Adaptive Machine Learning Methods: Integrating Q-Learning and NEAT Algorithms with Noisy Radar Measurements](https://mlsanity.com/paper/2504.07393/) (2025)

## Abstract (arXiv)

In this paper, we develop a drift homotopy implicit particle filter method. The methodology of our approach is to adopt the concept of drift homotopy in the resampling procedure of the particle filter method for solving the nonlinear filtering problem, and we introduce an implicit particle filter method to improve the efficiency of the drift homotopy resampling procedure. Numerical experiments are carried out to demonstrate the effectiveness and efficiency of our drift homotopy implicit particle filter.