A system and method is provided for registering outputs from a plurality of remote positional data sources, the system having: a plurality of positional data sources disposed on a plurality of units providing a plurality of types of positional data relative to at least one commonly tracked object held as a local positional data source; a processor disposed on a unit configured to process the positional data from each positional data source and apply a filter to the positional data; and the processor configured to weigh the positional data based on a probability of that a positional datum in the positional data is accurate and using weighted positional data to identify an absolute location of the commonly tracked object.

A thorough understanding of aircraft operations counts at airports is helpful due to the use of those counts in the planning and design process and in the allocation of funds for improvement. Methods of counting aircraft operations at airports lacking full-time personnel are typically based on conventional statistical sampling using relatively small sample sizes due to the inherent difficulty and expense of positioning acoustic or pneumatic counting devices at those airports for extended periods of time. Such methods are often inaccurate because of the lack of sufficient representative samples. A means of counting operations using a combination of Mode C, Mode S, and ADS-B extended squitter aircraft transponder data received using a 1090 MHz software-defined radio system is disclosed herein. The increasing presence of such signals in both controlled and uncontrolled airspace around airports, due to a recent federal mandate that all aircraft in certain types of controlled airspace be equipped with ADS-B Out capability by 2020, lends itself to the measurement of operational parameters associated with the related aircraft. The 1090 MHz signals are received passively; i.e., there is no interrogation from the field-deployed device. The resulting sample counts are typically larger than those determined through conventional data collection procedures. In one aspect, these sample counts are applied to a Bayesian statistical estimation technique, which produces an improved estimate of operations.

A remotely deployable network of multi-rotor aircraft and landing stations enable widespread use of multi-rotor aircraft in varied environments and application scenarios. A multi-rotor aircraft having modular components to facilitate a range of applications performs remote operations. Landing stations provide a power source to remote aircraft and facilitate semi-autonomous landing. A computing device facilitates use interaction with a network of multi-rotor aircraft and landing stations that together form a network for transmitting data concerning individual and regional aircraft operations.

Embodiments include methods for estimating movement of an aerial user equipment (UE) by a first RAN node serving the aerial UE in a cell of the RAN. Such methods include determining initialization parameters for an interacting multiple-model (IMM) for movement of the aerial UE in the cell. The initialization parameters include a plurality of neighbor cells, in the RAN, in which positioning measurements should be performed for the aerial UE, and/or for at least one movement mode of the IMM, an initial state comprising a plurality of initial position estimates for the aerial UE. Such methods include determining a movement state for the aerial UE at a first time based on the initialization parameters and positioning measurements of the aerial UE that are performed in the cell and in at least a portion of the neighbor cells. Other embodiments include complementary methods for a second RAN node.