Branch and bound method for sensor scheduling in discrete time

In this paper we consider the question of sensor scheduling in discrete time. The basic problem is to design a linear filter whose output provides an unbiased minimum variance estimate of a signal process whose noisy measurements from multiple sensors are available for input to the filter. The problem is to select one source (sensor data) dynamically so as to minimize estimation errors. We formulate the problem as an optimal control problem. By analyzing the positive semi-definite property of the error covariance matrix, we develop a branch and bound method to calculate the optimal scheduling strategy and give a numerical result for interpretation.