Hidden Markov model multiarm bandits: A methodology for beam scheduling in multitarget tracking

Abstract

In this paper, we derive optimal and suboptimal beam scheduling algorithms for electronically scanned array tracking systems. We formulate the scheduling problem as a multiarm bandit problem involving hidden Markov models (HMMs). A finite-dimensional optimal solution to this multiarm bandit problem is presented. The key to solving any multiarm bandit problem is to compute the Gittins index. We present a finite-dimensional algorithm that computes the Gittins index. Suboptimal algorithms for computing the Gittins index are also presented. Numerical examples are presented to illustrate the algorithms.