Electrical & Electronics Engineering

Permanent URI for this collectionhttp://197.211.34.35:4000/handle/123456789/130

Electrical & Electronics Engineering

Browse

Author: search.filters.author.Wen-Hua Chen

Search Results

Now showing 1 - 2 of 2
  • No Thumbnail Available
    Item
    Probability hypothesis density filter for parameter estimation of multiple hazardous sources
    (Elsevier, 2024-08-30) Abdullahi Daniyan; Cunjia Liu; Wen-Hua Chen
    This study introduces an advanced methodology for estimating the source term of multiple, variable-number biochemical hazard releases, where the exact count of sources is not predetermined. Focusing on environments monitored via a network of sensors, we tackle this challenge through a multi-source Bayesian filtering paradigm, employing the theory of random finite sets (RFS). Our novel approach leverages a modified particle filter-based probability hypothesis density (PHD) filter within the RFS framework, enabling simultaneous estimation of critical source characteristics (such as location, emission rate, and effective release height) and the quantification of source numbers. This method not only accurately estimates pertinent source parameters but is also adept at identifying the emergence of new sources and the cessation of existing ones within the monitored area. The efficacy of our approach is validated through extensive simulations, which mimic a range of scenarios with varying and unknown source counts, highlighting the proposed method’s robustness and precision.
  • No Thumbnail Available
    Item
    Bayesian Multiple Extended Target Tracking Using Labeled Random Finite Sets and Splines
    (IEEE, 2018-10-04) Abdullahi Daniyan; Sangarapillai Lambotharan; Anastasios Deligiannis; Yu Gong; Wen-Hua Chen
    In this paper, we propose a technique for the joint tracking and labeling of multiple extended targets. To achieve multiple extended target tracking using this technique, models for the target measurement rate, kinematic component, and target extension are defined and jointly propagated in time under the generalized labeled multi-Bernoulli filter framework. In particular, we developed a Poisson mixture variational Bayesian model to simultaneously estimate the measurement rate of multiple extended targets and extended target extension was modeled using B-splines. We evaluated our proposed method with various performance metrics. Results demonstrate the effectiveness of our approach.