Optimal sensor scheduling in nonlinear filtering of diffusion processes
SIAM Journal on Control and Optimization
Grid Coverage for Surveillance and Target Location in Distributed Sensor Networks
IEEE Transactions on Computers
Convex Optimization
Information theoretic sensor management
Information theoretic sensor management
Optimal sensor scheduling for resource-constrained localization of mobile robot formations
IEEE Transactions on Robotics
Brief Sensor scheduling in continuous time
Automatica (Journal of IFAC)
Automatica (Journal of IFAC)
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A set of N independent Gaussian linear time invariant systems is observed by M sensors whose task is to provide the best possible steady-state causal minimum mean square estimate of the state of the systems, in addition to minimizing a steady-state measurement cost. The sensors can switch between systems instantaneously, and there are additional resource constraints, for example on the number of sensors which can observe a given system simultaneously. We first derive a tractable relaxation of the problem, which provides a bound on the achievable performance. This bound can be computed by solving a convex program involving linear matrix inequalities. Exploiting the additional structure of the sites evolving independently, we can decompose this program into coupled smaller dimensional problems. In the scalar case with identical sensors, we give an analytical expression for an index policy proposed in a more general context by Whittle. In the general case, we develop open-loop periodic switching policies whose performance matches the bound arbitrarily closely.