Methods are presented for the cost-effective development and integration of multi-sensor data fusion technology. The key new insight is in formulating the system engineering process as a resource management problem. Effectively, system engineering is formulated as a problem of planning under uncertainty, where the probability of outcome of various actions, the utility of such outcomes and the cost of actions are posed as time-varying functions. The fusion-specific problem is that of decomposing system operational and support requirements into requirements for a network of processing nodes, involving functions for data alignment, data association and state estimation.