5 papers
Multi-Domain Iterative Detection for Massive Connectivity in LEO Satellite Networks
Xinhua Liu, Yueqing Wang, Keke Ying +7
Grant-Free (GF) random access is promising for low Earth orbit satellite Internet due to its reduced access latency. However, existing schemes suffer from poor performance in massi…
Data-Driven Moving Horizon Estimators for Linear Systems with Sample Complexity Analysis
Peihu Duan, Jiabao He, Yuezu Lv +1
This paper investigates the state estimation problem for linear systems subject to Gaussian noise, where the model parameters are unknown. By formulating and solving an optimizatio…
Secure State Estimation of Cyber-Physical Systems via Gaussian Bernoulli Mixture Model
Xingzhou Chen, Nachuan Yang, Peihu Duan +2
The implementation of cyber-physical systems in real-world applications is challenged by safety requirements in the presence of sensor threats. Most cyber-physical systems, especia…
An Autocovariance Least-Squares-Based Data-Driven Kalman Filter for Unknown Systems
Suyang Hu, Xiaoxu Lyu, Peihu Duan +2
This article investigates the problem of data-driven state estimation for linear systems with both unknown system dynamics and noise covariances. We propose an Autocovariance Least…
Robust Data-Driven Kalman Filtering for Unknown Linear Systems using Maximum Likelihood Optimization
Peihu Duan, Tao Liu, Yu Xing +1
This paper investigates the state estimation problem for unknown linear systems subject to both process and measurement noise. Based on a prior input-output trajectory sampled at a…