Dr. Jurgo Preden Profile

Dr. Jurgo Preden

at Tallinn Univ of Technology

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Proceedings Article | 10 June 2014 Paper

Distributed fusion and automated sensor tasking in ISR systems

Jurgo Preden, Raido Pahtma, Sergei Astapov, Johannes Ehala, Andri Riid, Leo Motus

Proceedings Volume 9079, 90790M (2014) https://doi.org/10.1117/12.2054731

KEYWORDS: Sensors, Intelligence systems, Acoustics, Magnetic sensors, Data fusion, Data communications, Telecommunications, Unattended ground sensors, Data acquisition, Computing systems

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Modern Intelligence, Surveillance and Reconnaissance (ISR) systems are increasingly being assembled from autonomous systems, so the resulting ISR system is a System of Systems (SoS). In order to take full advantage of the capabilities of the ISR SoS, the architecture and the design of these SoS should be able to facilitate the benefits inherent in a SoS approach - high resilience, higher level of adaptability and higher diversity, enabling on-demand system composition. The tasks performed by ISR SoS can well go beyond basic data acquisition, conditioning and communication as data processing can be easily integrated in the SoS. Such an ISR SoS can perform data fusion, classification and tracking (and conditional sensor tasking for additional data acquisition), these are extremely challenging tasks in this context, especially if the fusion is performed in a distributed manner. Our premise for the ISR SoS design and deployment is that the system is not designed as a complete system, where the capabilities of individual data providers are considered and the interaction paths, including communication channel capabilities, are specified at design time. Instead, we assume a loosely coupled SoS, where the data needs for a specific fusion task are described at a high level at design time and data providers (i.e., sensor systems) required for a specific fusion task are discovered dynamically at run time, the selection criteria for the data providers being the type and properties of data that can be provided by the specific data provider. The paper describes some of the aspects of a distributed ISR SoS design and implementation, bringing examples on both architectural design as well as on algorithm implementations.

Proceedings Article | 22 May 2013 Paper

On-line data validation in distributed data fusion

Jurgo Preden, James Llinas, Galina Rogova, Raido Pahtma, Leo Motus

Proceedings Volume 8742, 87420S (2013) https://doi.org/10.1117/12.2016249

KEYWORDS: Data fusion, Telecommunications, Data acquisition, Data communications, Data modeling, Clocks, Unattended ground sensors, Computing systems, Sensors, Information fusion

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Data acquisition and data fusion systems are becoming increasingly complex, being in fact systems of systems, where every component may be a system with varying levels of autonomy by themselves. Possible changes in system configuration by entities joining or being removed from the system make the system complex. As synchronous operation cannot be expected in such a system configuration, the temporal and spatial correctness of data must be achieved via other means. This paper presents the concept of mediated interactions as a method for ensuring correctness of computation in a distributed system. The mediator associated with each computing entity is responsible for online checking of the data both before it is sent out at the sender side and before it is received at the receiver side, ensuring that only data satisfying the validity constraints of the receiver-side data processing algorithm is used in computation. This assumes that each data item is augmented with metadata, which enables online data validation. The validity and quality dimensions in use depend on the system requirements defined by a specific problem and situational context; they may be temporal, spatial and involve various data quality dimensions, such as accuracy, confidence, relevance, credibility, and reliability. Among other capabilities, the mediator is able to cope with the unknowns in the temporal dimension that occur at runtime and are not predictable, such as channel delay, jitter of clocks and processing delays. This capability becomes an especially relevant factor in multi-tasking systems and in configurations in which a computing entity may have to process a variable number of parallel streams of data. Both the architecture and a simulation case study of a distributed data fusion scenario are presented in the paper.

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