This paper studies the outage minimization problem for state estimation of a scalar linear dynamical system using multiple sensors. The sensors amplify and forward their measurements to a remote fusion center over wireless fading channels. For stable systems, the resulting infinite horizon problem is a constrained Markov decision process (MDP) that can be solved using dynamic programming techniques. A suboptimal power allocation that is less computationally intensive is also proposed, and numerical results demonstrate very close performance to the power allocation obtained from the solution of the MDP. For unstable systems, a finite horizon formulation of the outage minization problem is also presented.