Due to an increasing number of sensors carried by distributed airborne platforms in modern military scenarios, the desire to use them in a cooperative manner to improve data collection further has emerged. Different capabilities and a multitude of possible sensor-platform combinations make planning for collaborative airborne sensor deployment a challenging task. It requires knowledge about the performance each sensor has for a given state so that it can be transferred into a condition where it can provide the most value for the designated mission. Performance in this context is mainly defined by the ability to detect targets and to localize them as accurately as possible. For the collaborative airborne sensor use this performance prediction shall be provided by sensor performance models. Therefore, in this paper we develop sensor performance models for electro-optical and infrared (EO/IR) cameras, ground moving target indicator (GMTI) radars, signals intelligence (SIGINT) and electronic support measures (ESM) sensors with different antenna types which deliver simulated sensor outputs and measurement predictions. Utilizing a combination of physics-based and data driven approaches. These models are valuable in forecasting the measurements and target information each sensor type can provide for given sensor specifications, environmental parameters, target types, and target states. The validity of the models is verified through simulations representing a possible deployment case for each sensor.