Privacy-aware Kalman filtering
We are concerned with a privacy-preserving problem in Kalman filter: a sensor releases a set of measurements to fusion center, who has perfect knowledge of the dynamical model, to allow it to estimate the public state, while prevent it from estimating the private state. We propose to linearly transf...
Saved in:
Main Authors: | Song, Yang, Wang, Chong Xiao, Tay, Wee Peng |
---|---|
其他作者: | School of Electrical and Electronic Engineering |
格式: | Conference or Workshop Item |
語言: | English |
出版: |
2020
|
主題: | |
在線閱讀: | https://hdl.handle.net/10356/137345 |
標簽: |
添加標簽
沒有標簽, 成為第一個標記此記錄!
|
相似書籍
-
Compressive privacy for a linear dynamical system
由: Song, Yang, et al.
出版: (2021) -
Inverse Kalman filtering problems for discrete-time systems
由: Li, Yibei, et al.
出版: (2024) -
Distributed Kalman filtering for time-varying discrete sequential systems
由: Chen, Bo, et al.
出版: (2020) -
On the relationship between inference and data privacy in decentralized IoT networks
由: Sun, Meng, et al.
出版: (2021) -
Arbitrarily strong utility-privacy tradeoff in multi-agent systems
由: Wang, Chong Xiao, et al.
出版: (2021)