This paper presents an online linear unmixing method leveraging Kalman filtering for real-time analysis of hyperspectral data. Unlike traditional methods that require processing of the entire data set, the proposed approach sequentially updates pure spectra estimates as new data is acquired, that is, on a spectrum-by-spectrum basis, thereby signifi...
Published in Smart Materials and Structures
For the magnetorheological suspension control system of all-terrain vehicles (ATVs), state estimation is an effective method to obtain system feedback signals that cannot be directly measured by sensors. However, when confronted with modeling errors and sudden changes in sensor noise during complex road driving, conventional estimation methods with...
This work introduces an on-the-fly (i.e., online) linear spectral unmixing method which is able to sequentially analyze spectral data acquired on a spectrum-by-spectrum basis. After deriving a sequential counterpart of the conventional linear mixing model, the proposed approach recasts the linear unmixing problem into a linear state-space estimatio...
Published in International journal of computer assisted radiology and surgery
The integration of a surgical robotic instrument tracking module within optical microscopes holds the potential to advance microsurgery practices, as it facilitates automated camera movements, thereby augmenting the surgeon's capability in executing surgical procedures. In the present work, an innovative detection backbone based on spatial attentio...
Underwater simultaneous localization and mapping (SLAM) has significant challenges due to the complexities of underwater environments, marked by limited visibility, variable conditions, and restricted global positioning system (GPS) availability. This study provides a comprehensive analysis of sensor fusion techniques in underwater SLAM, highlighti...
The non-redescending convex functions degrade the filtering robustness, whereas the redescending non-convex functions improve filtering robustness, but they tend to converge towards local minima. This work investigates the properties of convex and non-convex cost functions from robustness and stability perspectives, respectively. To improve filteri...
The rapid expansion of BeiDou satellite navigation applications has led to a growing demand for real-time high-precision positioning services. Currently, high-precision positioning services face challenges such as a long initialization time and heavy reliance on reference station networks, thereby failing to fulfill the requirements for real-time, ...
Fault detection and diagnosis (FDD) methods and fault-tolerant control (FTC) have been the focus of intensive research across various fields to ensure safe operation, reduce costs, and optimize maintenance tasks. Unmanned aerial vehicles (UAVs), particularly quadcopters or quadrotors, are often prone to faults in sensors and actuators due to their ...
The acquisition of vehicle driving status information is a key function of vehicle dynamics systems, and research on high-precision and high-reliability estimation of key vehicle states has significant value. To improve the state observation effect, a vehicle sideslip angle estimation method adopting a robust bias compensation Kalman filter and ada...
Recently, solar and wind power generation have gained attention as pathways to achieving carbon neutrality, and Renewable Energy Resource Management System (RERMS) technology has been developed to monitor and control small-scale, distributed renewable energy resources. In this work, we present an Event-Triggered Transmission (ETT) algorithm for RER...
