We describe an extension of the virtual volume concept to multiple sensors. Data from multiple sensors are combined in real-time and mapped into a constantly updating three-dimensional grid. The data are combined in a time-centric manner, with data replacing older data, regardless of the sensor that the older data came from. We discuss scaling problems with this method and how they can be resolved.

We demonstrate this method of merging real-time data on base data (such as radar reflectivity) as well as on derived data (such as linear least square derivatives).