This paper addresses the problem of distributed estimation an unknown dynamic parameter by a multi-agent system over directed communication network in presence adversarial attack on agents' sensors. The mode adversaries is to corrupt sensor measurements some agents, while and information processing capabilities those agents remain unaffected. To ensure that all both normal as well under attack,...

Future formation flying missions are being planned for fleets of spacecraft in MEO, GEO, and beyond where relative navigation using GPS will either be impossible or insufficient. To perform fleet estimation for these scenarios, local ranging devices on each vehicle are being considered to replace or augment the available GPS measurements. These estimation techniques need to be reliable, scalabl...

This paper presents a distributed bounded-error state estimation algorithm suited, e.g., to measurement processing by a network of sensors. Contrary to centralized estimation, where all data are collected to a central processing unit, here, each data is processed locally by the sensor, the results are broadcasted to the network and taken into account by the other sensors. A first analysis of th...

An event-based state estimation approach for reducing communication in a networked control system is proposed. Multiple distributed sensor-actuator-agents observe a dynamic process and sporadically exchange their measurements and inputs over a bus network. Based on these data, each agent estimates the full state of the dynamic system, which may exhibit arbitrary interagent couplings. Local even...

The need in recent years for higher frequency in state estimation execution covering larger supervised networks has led to the investigation of faster and numerically more stable state estimation algorithms. However, technical developments in distributed Energy Management Systems, based on fast data communication networks, open up the possibility of parallel or distributed state estimation impl...

We consider the problem of estimating set-expression cardinality in a distributed streaming environment where rapid update streams originating at remote sites are continually transmitted to a central processing system. At the core of our algorithmic solutions for answering set-expression cardinality queries are two novel techniques for lowering data communication costs without sacrificing answe...

Distributed estimation has advantages over centralized estimation in reducing communication bandwidth, distributing the processing load and improving system survivability. One important technical issue in designing distributed estimation architectures and algorithms is the proper treatment of dependent information. This paper presents graphical models to represent dependent information in gener...

We consider the estimation of Dirichlet Process Mixture Models (DPMMs) in distributed environments, where data are distributed across multiple computing nodes. A key advantage of Bayesian nonparametric models such as DPMMs is that they allow new components to be introduced on the fly as needed. This, however, posts an important challenge to distributed estimation – how to handle new components ...