GPS World, January 2011

Personal Navigation WIRELESS LBS FIGURE 4 Position augmentation server functional modules navigation sensor measurements INS GNSS and so on X P V Ω Σ PVΩ h represents the model that relates l with X INS mechanization equations GNSS position models and so on and for the qualitative case the relation can be written as f q f M where the qualitative observations f are obtained from quantitative observations by performing low level processing M P V Ω Σ P V Ω q represents the model that relates f with M based on high level processing In the IEGLO project this theoretical approach has been materialized by defi ning the appropriate quantitative and qualitative observation and navigation spaces Quantitative Navigation Quantitative navigation in IEGLO is based on positioning thus no quantitative velocity or attitude determination is performed This leads to a very specifi c navigation space t T R p x y z P R3 IEGLO uses different positioning technologies for indoor and outdoor positioning GPS serves as the main positioning method outdoors while Wi Fi and RFID are used primarily for indoor positioning A GPS position augmentation service has been developed to augment GPSonly position solutions using European Geostationary Navigation Overlay Service EGNOS information acquired via the local area network and the Internet The augmentation service is useful for receivers which are not capable of processing EGNOS data but also for receivers which cannot receive EGNOS signals due to signal shadowing by urban canyons or the like In this case the GPS only position is transmitted to the augmentation server which corrects the position solution and retransmits the EGNOS Data Access System signal inspace through the Internet EDAS SiSNeT corrected position FIGURE 4 shows the functional modules of the augmentation server EDAS provides access to the wide area differential correction of EGNOS SiSNeT is a free service that provides EGNOS widea rea differential corrections and integrity information over the Internet The augmentation server accesses EGNOS information from EDAS or SiSNeT decodes the data and stores it in a database As a backup solution if EDAS cannot be accessed the augmentation server can also interface to an EGNOS receiver to decode the EGNOS signal in space The augmentation server is provided with ephemeris and ionospheric information from EDAS SiSNeT The GPS position is received from the correction requesting unit together with its time and used satellites It is corrected at the augmentation server and retransmitted back to the requesting unit From the mobile device sensor information is transmitted to the CG The sensor data is processed into positioning messages with additional reference information for Wi Fi RFID and GSM positioning A generic fi lter method determines a reliable IEGLO position from the different determined positions which is transmitted to the service center together with the accuracy and time information The choice of the position depends on its accuracy and its age Qualitative Navigation Positioning is indeed the main navigation component in IEGLO A main goal of the project is to be able to contact a person in case of an emergency anytime anywhere and thus position is suffi cient But beyond this suffi ciency a broader navigation concept can be developed using two of the available sensors in the IEGLO system the GPS receiver and the 3 axial accelerometer As described earlier these two sensor measurements quantitative observations would yield some motion features of the person qualitative observations with which to estimate the motion context of the person qualitative states This is a two step processing low level and high level Low Level Processing from quantitative to qualitative observations As depicted in Figure 2 the qualitative observations used in IEGLO are ground speed segment balance changes high accelerations low motion and periodicity These qualitative observations are low level processed in two steps First robust and non robust statistical estimators based in order statistics like the median median absolute deviation normalized MADN α trimmed mean and deviation or least squares like the mean standard deviation respectively and deterministic analyzers such as the fast Fourier transform FFT velocity transformation VT equidistant maxima search EMS are applied to estimate some intermediate values like the fi rst and second statistical moments maximum and minimum values and FFTs Secondly these intermediate quantities are evaluated using propositional calculus to decide if a situation is fi nally detected All the qualitative observations extraction in IEGLO are described as follows On one hand GPS positions are used to compute the ground speed segments of the device That is given a sample of GPS positions P t p N i i i 1 the ground speed sample is extracted through a fi nite difference based technique called velocity transformation www gpsworld com January 2011 GPS World 67