In consideration of the sensor control for multi-target tracking

this paper proposes the corresponding sensor control strategy using Gaussian mixture multi-Bernoulli filter based on the FInite Set Statistics (FISST) theory. First

this paper gives the implementation of the Cubature Kalman Gaussian Mixture Cardinality Balanced Multi-target Multi-Bernoulli Filter (CK-GMCBMeMBerF)

and extracts the Gaussian mixture component to approximate multi-Bernoulli density. In addition

we study the solution of the Cauchy-Schwarz divergence between the two Gaussian mixture distributions

and derive the information gain corresponding to the change of multi-target probability density. Then

the corresponding sensor control strategy is proposed. Moreover

a detailed Gaussian Mixture (GM) implementation of the posterior expected number of targets (PENT) criteria is given based on CK-GMCBMeMBerF

and the corresponding sensor control strategy is studied with GM-PENT as the evaluation criteria. Finally

simulation results verify the effectiveness of these proposed algorithms.