🚀 1 Paper accepted to IEEE TAES 2025! 🚀
We are happy to announce that the lab has one paper accepted to IEEE Transactions on Aerospace and Electronic Systems 2025! Congratulations to our student, Michael Potter, for his great work:
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Continuously Optimizing Radar Placement with Model Predictive Path Integrals
Continuously Optimizing Radar Placement with Model Predictive Path Integrals
Continuously Optimizing Radar Placement with Model Predictive Path Integrals
Michael utilized Model Predictive Path Integrals, a stochastic control method, to optimize the placement of multiple radars under kinematic and environmental constraints for tracking multiple targets. He developed an information-based objective that accounts for the decay in radar return power as the distance between the radar and target increases. This approach enables superior geometric placement of the radars compared to competing methods, which neglect the radar decay when calculating the Fisher Information Matrix.