In several recent papers and a new book, Mathematics of Data FUsion, we have shown how finite-set statistics (FISST), a special case of random set theory, provides a theoretically rigorous foundation for many aspects of data fusion. In particular, we demonstrated that this theory provides a fundamental new approach to the problem of determining optimal dwell allocations, mode selections, and servo parameters for reassignable and/or multimode sensor. The basic approach relied on the fact that FISST provides a means of mathematically transforming multisensor, multitarget sensor management problems into conventional nonlinear optimal control problems. In this paper we show that the approach can be extended to include the possibility that the sensor may be distributed among many platforms. We also briefly describe a special cases of finite-set statistics called 'joint multitarget probabilities' or 'JMP', which has been applied to another sensor management approach by Musick, Kastella, and Mahler.