2015/12/01 by Mengqi Ren, Ruixin Niu, Ren, Mengqi +1
Biochemistry, Genetics and Molecular Biology · Computer Science · Medicine · #Advanced biosensing and bioanalysis techniques #Distributed Sensor Networks and Detection Algorithms #FOS: Electrical engineering #SARS-CoV-2 detection and testing #Systems and Control (eess.SY) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.1512.00399
openalex publication_date 2015/12/01 · openalex created_date 2016/06/24 · openalex updated_date 2026/07/28
The problem of faulty sensor detection is investigated in large sensor networks where the sensor faults are sparse and time-varying, such as those caused by attacks launched by an adversary. Group testing and the Kalman filter are designed jointly to perform real time system state estimation and time-varying faulty sensor detection with a small number of tests. Numerical results show that the faulty sensors are efficiently detected and removed, and the system state estimation performance is significantly improved via the proposed method. Compared with an approach that tests sensors one by one, the proposed approach reduces the number of tests significantly while maintaining a similar fault detection performance.