Hybrid Data Fusion

Positioning has become a key driver for new services and has given wide user adoption in recent years. The Global Navigation Satellite Systems(GNSS) such as , Galileo or GPS will deliver accurate position information for good environmental conditions and for Line of Sight access to several satellites. In critical scenarios, e.g., urban canyons or the transition from outdoor to indoor, there may be situations where even combined Galileo and GPS constellations may not provide the minimum number of measurements required for positioning.  

Another technique is the determination of the MS location by exploiting the already available resources of a wireless cellular network. This is generally based on measurements such as Time of Arrival (ToA), Angle of Arrival (AoA), Time Difference of Arrival (TDoA) or Received Signal Strength (RSS), processed by network with its basestations.  

Services and applications based on accurate knowledge of the location of mobile station will play a fundamental role in future wireless system. Also, higher precisions could be achieved for critical navigation scenarios through data fusion of the GNSS based and cellular system based positioning. 

The GREAT project is investigating a hybrid approach to location determination, which will be of interest depending on the MS position and the environmental conditions. The available GNSS signals and measurements from the cellular network are processed in a Hybrid Data Fusion entity to improve the performance in terms of accuracy and coverage. The GREAT project aims to research efficient algorithms / signal processing software for position computation using multiple measurement sources, such as GPS, Galileo and measurements from the cellular communication network.

Hybrid positioning algorithms use in addition to the Galileo/GPS based positioning, information from cellular communication systems (GSM, UMTS, CDMA, 4G with focus on 3GPP LTE) based techniques (Cell-ID, TA, TOA, E-OTD, OTDOA, AFLT). The working tasks for hybrid positioning algorithms can be given as:

1. Identification of critical navigation scenarios for Galileo, in which Galileo based positioning may benefit from cellular communication system based positioning.
   
2. Identification of advanced cellular positioning techniques and their receiver/network requirements
   
3. Development of navigation techniques of hybrid Galileo/GPS/Cellular solutions. Different terrestrial navigation techniques are analyzed for their suitability for combination with Galileo.

4. Emphasis for the algorithm selection is on:
   1. Coverage extension of Galileo
   2. Accuracy of hybrid navigation techniques
   3. Delays, e.g., through mobile radio networks
   4. Receiver/network requirements
   5. Impacts on the hardware design of hybrid mass market navigation receivers.

Benefits to the user include the improved coverage in critical urban canyon environments and the transition from indoor to outdoor where not enough GNSS satellites are in view.  This again can improve the yield of successful location attempts.

Hybrid Data Fusion integration to other Work packages

Aperture angle in dependence on height (H) of the buildings and width (W) of the street

Galileo and GPS satellite constellation