A Unified Framework for Adaptive Beamforming and State Estimation in Dynamic Multi-Lane V2V Networks
This paper presents a Vehicle-to-Vehicle (V2V) communication modeling framework that addresses the challenges of reliable state estimation and beamforming control in dynamic, multi-lane road environments. By integrating an extended Unscented Kalman Filter (UKF) with adaptive process and measurement...
Saved in:
| Main Authors: | Nivetha Kanthasamy, Raghvendra V. Cowlagi, Alexander Wyglinski |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
|
| Series: | IEEE Open Journal of Vehicular Technology |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/11083750/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
EFFICIENCY ANALYSIS OF EXTENDED KALMAN FILTERING, UNSCENTED KALMAN FILTERING AND UNSCENTED PARTICLE FILTERING
by: I. A. Kudryavtseva
Published: (2016-12-01) -
Model predictive control for multi-axis steering trajectory tracking strategy of heavy-duty articulated vehicle with vehicle status accurate estimation
by: You Zhou, et al.
Published: (2025-09-01) -
Robust MPS-INS UKF Integration and SIR-Based Hyperparameter Estimation in a 3D Flight Environment
by: Juyoung Seo, et al.
Published: (2025-03-01) -
Sensorless Control of Hydrogen Pump Using Adaptive Unscented Kalman Filter
by: Sheianov Aleksandr, et al.
Published: (2020-06-01) -
State estimation of voltage and frequency stability in solar wind integrated grids using multiple filtering techniques
by: Abdulelah Alharbi
Published: (2025-08-01)