Results 141 to 150 of about 12,544 (245)

A Sequential Kalman-Newton-KM Framework for AIS and Radar Data Fusion in Restricted Inland Waterways. [PDF]

Sensors (Basel)
Shi H, Wang D, Wei L, Liang S.
europepmc   +1 more source

Polar‐low track prediction using machine‐learning methods

Quarterly Journal of the Royal Meteorological Society, EarlyView.
Machine‐learning models are developed to produce reliable and efficient forecasts of polar‐low (PL) trajectories 12 hours ahead. A temporal model (RLSTM) benefiting from the rolling‐forecast strategy, improves overall prediction accuracy and is suitable for quick experimentation, while a spatiotemporal model (PL‐UNet), incorporating both historical and
Ziying Yang, Rune Grand Graversen, Filippo Maria Bianchi, Jiping Liu, Ruibo Lei   +4 more
wiley   +1 more source

A new method to identify and explain sources of precipitation modification, illustrated for the western Netherlands

Quarterly Journal of the Royal Meteorological Society, EarlyView.
This study develops a method to identify the source areas of precipitation events, as illustrated for the western part of the Netherlands. Radar‐based precipitation data are traced back to their source areas and machine‐learning techniques are used to identify hypothesized causes: urban heat, surface roughness, and air pollution. We find that urban and
Jelmer van der Graaff, Gert‐Jan Steeneveld   +1 more
wiley   +1 more source

Exploiting Aeolus winds in a regional numerical weather prediction model

Quarterly Journal of the Royal Meteorological Society, EarlyView.
Aeolus measured winds have proven to be beneficial for global models. However, demonstrating positive impact for limited‐area models has been a challenge so far. For the first time, we have demonstrated a statistically significant positive impact of Aeolus winds in a limited‐area model by using the 4DVar data assimilation technique and the most recent ...
Gert‐Jan Marseille, Roohollah Azad, Martin Ridal, Susanna Hagelin   +3 more
wiley   +1 more source

Initial State Privacy of Nonlinear Systems on Riemannian Manifolds

International Journal of Robust and Nonlinear Control, EarlyView.
ABSTRACT In this paper, we investigate initial state privacy protection for discrete‐time nonlinear closed systems. By capturing Riemannian geometric structures inherent in such privacy challenges, we refine the concept of differential privacy through the introduction of an initial state adjacency set based on Riemannian distances.
Le Liu, Yu Kawano, Antai Xie, Ming Cao
wiley   +1 more source

Velocity and Angle Tracking of Fast Targets Using a Bandwidth-Coded Hybrid Chirp FMCW Radar. [PDF]

Sensors (Basel)
Gökdemir B, Dalveren Y, Kara A, Derawi M.   +3 more
europepmc   +1 more source

Enabling Under Ice Glider Operations: A Backseat Driver Approach

Journal of Field Robotics, EarlyView.
ABSTRACT Polar Oceans are key locations for forcing global ocean circulation, influencing both global climate and biogeochemical cycles. Due to restricted access to these seasonally and perennially ice‐covered regions, these areas are severely undersampled.
Yaomei Wang, Benjamin Allsup, Georgios Salavasidis, Stephen Woodward, Adeniyi Adenaya, Mike Smart, Alexis Johnson, Felipe Marques Dos Santos, Jake Ludgate, Daniel Matterson, Alvaro Lorenzo, J. Alexander Brearley, Alexander Brian Phillips   +12 more
wiley   +1 more source

The Evolution of Autonomous Systems for Planetary Cave Exploration: A Review

Journal of Field Robotics, EarlyView.
ABSTRACT The exploration of Subsurface Access Points (SAPs), such as lava tubes on the Moon and Mars, has gained significant interest due to their potential as stable environments shielded from surface radiation and temperature extremes. These sites are considered high‐value targets for detecting water and signs of ancient life, and assessing their ...
Sarah Swinton, Daniel Mitchell, Jamie Blanche, Euan McGookin, David Flynn   +4 more
wiley   +1 more source

MVDFusion: Multimodal Vehicle Detection in Foggy Weather Using LiDAR and Radar Fusion. [PDF]

Sensors (Basel)
Tian J, Gao Y, Xia X, Ju G, Ye P, Tang S, Wang H, Wang X.   +7 more
europepmc   +1 more source

Deep Reinforcement Learning Based Autonomous Decision‐Making for Cooperative Uncrewed Aerial Vehicles: A Search and Rescue Real World Application

Journal of Field Robotics, EarlyView.
ABSTRACT This paper presents the first end‐to‐end framework that combines guidance, navigation, and centralized task allocation for multiple UAVs performing autonomous search‐and‐rescue (SAR) in GNSS‐denied indoor environments. A twin delayed deep deterministic policy gradient controller is trained with an artificial potential field (APF) reward that ...
Thomas Hickling, Maxwell Hogan, Abdulla Tammam, Nabil Aouf   +3 more
wiley   +1 more source