Threat assessment is an important part of level 3 data fusion. Here we study a subproblem of this, worst- case risk assessment. Inspired by agent-based models used for simulation of trail formation for urban planning, we use ant colony optimization (ANTS) to determine possible av- enues of approach for the enemy, given a situation picture. One way of determining such avenues would be to cal- culate the "potential field" caused by placing sources at possible goals for the enemy. This requires postulating a functional form for the potential, and also takes long time. Here we instead seek a method for quickly obtaining an ef- fective potential. ANTS, which has previously been used to obtain approximate solutions to various optimization prob- lems, is well suited for this. The output of our method de- scribes possible avenues of approach for the enemy, i.e, ar- eas where we should be prepared for attack. (The algorithm can also be run "reversed" to instead get areas of opportu- nity for our forces to exploit.) Using real geographical data, we found that our method gives a fast and reliable way of determining such avenues. Our method can be used in a computer-based command and control system to replace the first step of human intelligence analysis.
['Pontus Svenson', 'Hedvig Sidenbladh']
Determining possible avenues of approach using ants