Compositional tools such as the synchronised pattern generators and real-time MIDI chord player.Making minimal assumptions about the environment's behavior. Used to optimally solve a broad class of waveform-agile tracking problems while On a multi-alphabet version of the Context-Tree Weighting (CTW) method can be Probabalistic model for the scene's behavior. Length phrases in order to build a context-tree, which is used as a Universal source coding, where a stationary source is parsed into variable Our approach is based on well-established tools from the field of Which asymptotically achieves Bellman optimality in any radar scene which canīe modeled as a $U^$ order Markov process for a finite, but unknown, This work develops a universal sequential waveform selection scheme Realistic target and channel dynamics, and a more general framework isĭesirable. That the memory length of the underlying Markov process is often unknown for However, a major limitation of reinforcement learning is In which the problem is framed as a Markov decision process (MDP), allowing for More recently, reinforcement learning has been proposed for waveform selection,
Optimization, even though radar scenes exhibit strong temporal correlation. Further, due to computationalĬoncerns, many traditional approaches are limited to near-term, or myopic, The target motion and measurement models. High SNR regime, and requires a rather restrictive set of assumptions regarding However, this approach is only valid in the Many conventional solutions utilize anĮstimation-theoretic interpretation, in which a waveform-specificĬramér-Rao lower bound on measurement error is used to select the optimal Thornton and 3 other authors Download PDF Abstract: Online selection of optimal waveforms for target tracking with active sensors Download a PDF of the paper titled Universal Learning Waveform Selection Strategies for Adaptive Target Tracking, by Charles E.
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