Persistant formatted storage and inter-process communication.
A mongodb database is mainly used for storage of filter states and measurements. This data is primarily used for later analysis and plotting using the python utility.
Typically the data is stored in States and Measurements collections, with pseudo-indexes collections to allow other applications to see at-a-glance which elements are available for retrieval, without searching the whole db.
The database's States collection is used as a method of inter-process communication, providing simple configuration of cross-network data passing, integrity and backup. It is used for recording clocks and orbits from a POD process, which are then sampled and formatted as RTCM SSR outputs
- This allows separation of the estimation of parameters, and the generation and transmission of RTCM messages.
The states collection may also be used to pass current or predicted values to another Pea instance, allowing several filters to run in a fast/slow configuration. In this case the states entries are marked with the time of update/prediction, and other db entries are used to signify validity of complete sets of db entries using the 'updated' time.