Mr. Anssi P. Karkkainen Profile

Anssi P. Karkkainen

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Proceedings Article | 28 April 2010 Paper

Improving situation awareness using a hub architecture for friendly force tracking

Anssi Karkkainen

Proceedings Volume 7709, 770905 (2010) https://doi.org/10.1117/12.852627

KEYWORDS: Telecommunications, Global Positioning System, Situational awareness sensors, Satellites, Computer security, Receivers, Chemical elements, Information security, Data communications, Satellite communications

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Situation Awareness (SA) is the perception of environmental elements within a volume of time and space, the comprehension of their meaning, and the projection of their future status. In a military environment the most critical elements to be tracked are followed elements are either friendly or hostile forces. Poor knowledge of locations of friendly forces easily leads into the situation in which the troops could be under firing by own troops or in which decisions in a command and control system are based on incorrect tracking. Thus the Friendly Force Tracking (FFT) is a vital part of building situation awareness. FFT is basically quite simple in theory; collected tracks are shared through the networks to all troops. In real world, the situation is not so clear. Poor communication capabilities, lack of continuous connectivity n and large number of user on different level provide high requirements for FFT systems. In this paper a simple architecture for Friendly Force Tracking is presented. The architecture is based on NFFI (NATO Friendly Force Information) hubs which have two key features; an ability to forward tracking information and an ability to convert information into the desired format. The hub based approach provides a lightweight and scalable solution, which is able to use several types of communication media (GSM, tactical radios, TETRA etc.). The system is also simple to configure and maintain. One main benefit of the proposed architecture is that it is independent on a message format. It communicates using NFFI messages, but national formats are also allowed.

Proceedings Article | 20 May 2009 Paper

Boosting intelligence analysis process and situation awareness using the self-organizing map

Anssi Kärkkäinen

Proceedings Volume 7352, 735204 (2009) https://doi.org/10.1117/12.819940

KEYWORDS: Visualization, Data modeling, Data processing, Situational awareness sensors, Visual analytics, Neural networks, Data mining, Analytical research, 3D modeling, Military intelligence

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Situational awareness is critical on the modern battlefield. A large amount of intelligence information is collected to improve decision-making processes, but in many cases this huge information load is even decelerating analysis and decision-making because of the lack of reasonable tools and methods to process information. To improve the decision making process and situational awareness, lots of research is done to analyze and visualize intelligence information data automatically. Different data fusion and mining techniques are applied to produce an understandable situational picture. Automated processes are based on a data model which is used in information exchange between war operators. The data model requires formal message structures which makes information processing simpler in many cases. In this paper, generated formal intelligence message data is visualized and analyzed by using the self-organizing map (SOM). The SOM is a widely used neural network model, and it has shown its effectiveness in representing multi-dimensional data in two or three dimensional space. The results show that multidimensional intelligence data can be visualized and classified with this technique. The SOM can be used for monitoring intelligence message data (e.g. in purpose of error hunting), message classification and hunting correlations. Thus with the SOM it is possible to speed up the intelligence process and make better and faster decisions.

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