Particle Swarm Optimization in the Dynamic Electronic Warfare Battlefield

Paul Ryan Witcher, Purdue University


This research improves the realism of an electronic warfare (EW) environment involving dynamic motion of assets and transmitters. Particle Swarm Optimization (PSO) continues to be used to place assets in such a manner where they can communicate with the largest number of highest priority transmitters. This new research accomplishes improvement in three areas. First, the previously stationary assets and transmitters are given a velocity component, allowing them to change positions over time. Because the assets now have a starting position and velocity, they require time to reach the PSO solution. In order to optimally assign each asset to move in the direction of a PSO solution location, a graph-based method is implemented. This encompasses the second area of research. The graph algorithm runs in O(n 3) time and consumes less than 0.2% of the total measured computation time to find a solution. Transmitter location updates prompt a recalculation of the PSO, causing the assets to change their assignments and trajectories every second. The computation required to ensure accuracy with this behavior is less than 0.5% of the total computation time. The final area of research is the completion of algorithmic performance analysis. A scenario with 3 assets and 30 transmitters only requires an average of 147ms to update all relevant information in a single time interval of one second. Analysis conducted on the data collected in this process indicates that more than 95% of the time providing automatic updates is spent with PSO calculations. Recommendations on minimizing the impact of the PSO are also provided in this research.




Christopher, Purdue University.

Subject Area

Computer Engineering|Electrical engineering

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