Application of POMDPs to Cognitive Radar

Autor:	Charles Topliff, William L. Melvin, Douglas B. Williams
Rok vydání:	2019
Předmět:	Mathematical optimization Heuristic business.industry Computer science Partially observable Markov decision process Observable law.invention Software law Markov decision process Radar business Cognitive radar Optimal decision
Zdroj:	ACSSC
DOI:	10.1109/ieeeconf44664.2019.9048936
Popis:	In recent years, hardware advances have resulted in software configurable radar systems that lend themselves well to decision-making systems. Partially observable Markov decision processes (POMDPs) are evaluated herein as a framework for decision-making in radar scenarios, and value iteration is examined as a method for computing an optimal decision policy with a POMDP. A scenario is investigated wherein a radar is competing with a greedy agent for spectrum. Results demonstrate improvement over a heuristic decision-making agent that seeks to maximize immediate reward.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::3f29133d05a69dac9a7c0a8a1dfc77e6 https://doi.org/10.1109/ieeeconf44664.2019.9048936 Zobrazit plný text záznamu