This paper reviews and describes methods for combining multimode sensor data. The context for the multimode sensor applications is an autonomous precision guided weapon, air-to-ground scenario. The first part of the paper reviews dual mode fusion architectures. Theoretical and measured performance results are referenced and extended. We introduce a fusion architecture hierarchy including post decision combiner rules, pre-decision combiner statistics, feature and raw data concomitant combiners. The architecture section concludes with a discussion and example of dual mode synergy performance versus sensor mode inequality. The second part of the paper describes the cost effectiveness benefits of dual mode and single mode sensors. Results from a many-on-many Monte Carlo mission effectiveness simulation are used to help quantify the multimode sensor benefits. In some cases synergistic multimode performance gain is a sufficient justification for adding a second or third sensor mode. In many cases the benefit is the extended and more robust operation over large search areas in the presence of countermeasures and adverse weather.