THE METHOD OF GNSS POSITIONING AVAILABILITY CONTROL FOR TRANSPORTATION APPLICATIONS Prof. Dr. Eng. Demyanov V.V, Assistant lecturer Likhota R.V. Irkutsk State Transport University Irkutsk, Russia to

INTRODUCTION High positioning accuracy and positioning reliability of GNSS users can be achieved by means of augmentation systems (LAAS or WAAS). Combining augmentation systems with receiver autonomous integrity monitoring algorithms (RAIM) we can get effective solutions for real-time positioning quality monitoring. Unfortunately both GNSS and LAAS (WAAS) performance is affected by irregular external impacts such as Space Weather events, multi-path effects and electromagnetic jammers. The character of GNSS positioning deterioration changes significantly in space and time under above mentioned conditions. On the other hand, each GNSS user has a personal required navigation parameters (RNP) which can be constant or can change in time (track motto along a railroad or aircraft landing motto, for example). There are no effective methods of positioning availability control which take in account both irregular external impacts and personal RNP yet. Such modern methods are extremely needed in order to provide safety on transportation and survival applications. We offer a new method of real-time GNSS+LAAS user positioning availability control for transportation applications. The positioning availability value is defined as a full probability of event when we get a personal GNSS user’s RNP taking in account the current PDOP, ranging errors and positioning errors.

Let’s make a short overview of the problem of GNSS+ Augmentation Systems performance under Space Weather hazards It is well known that geomagnetic storms can cause the signal tracking loss inside the GNSS receivers as well as sharp increasing of ranging errors. The other negative Space Weather factor for GNSS and augmentation systems (AS) performance is the powerful solar radio flares in 1-2 GHz frequency band. A numerous short-time failures of GPS and GLONASS SV ranging were observed during the powerful solar radio flares on December 6th and 13 th, 2006 at some IGS-stations within the Earth sunlit side. Such events can cause serious performance deterioration for both standalone GNSS and AS operating. Some references: 1.A review of GPS/GLONASS studies of the ionospheric response to natural and anthropogenic processes and phenomena / E.L. Afraimovich [et al.] // J. Space Weather Space Clim. – 2013– Vol. 3. – P. A27 2.Changsheng C. Cycle slip detection and repair for undifferenced GPS observations under high ionospheric activity / Changsheng C., Zhizhao L., Pengfei X. and D.Wujiao // GPS Solutions. – – Vol. 17. – P. 247–260 3.Demyanov V.V. An evaluation of potential solar radio emission power threat on GPS and GLONASS performance / Demyanov V.V., Afraimovich E.L., Jin S.G. // GPS Solutions. – – Vol. 13. – P Carrano, C.S. Effects of the December 2006 solar sadio bursts on the GPS receivers of the AFRL-SCINDA network / C. S. Carrano, K. M. Groves, C. T. Bridgwood // Proceedings of the International Beacon Satellite Symposium, June 11–15 / ed. Doherty P. H. – Boston, Datta-Barua S. Ionospheric Threats to space-based augmentation system development / S.Datta-Barua // Proc. of ION GNSS – Long Beach, CA. – P. 7 6.LAAS ionosphere spatial gradient threat model and impact of LGF and airborne monitoring / M. Luo [et al.] // ION GPS/GNSS, 9–12 September. – Portland OR, – P

Positioning accuracy and positioning deterioration sources  XYZ =PDOP  Ri

Ranging errors due to irregular structure of the radio-propagation media Here we can see, that ranging errors due to irregular ionospheric refraction depends on local ionospheric electron density distribution and intensity of the ionospheric irregularities. Ionospheric scintillations have complex character. Generally they produce sharp S/N fading at a reception point. A consequence of it is sharp increasing of ranging error of even SV tracking loose.

Ranging errors due to irregular structure of the radio-propagation media Ionospheric selective distortions works like a chain of band-pass filters. These “filters” suppress some components from SV signal spectra and cause the signal envelope distortion. A consequence of it – ranging error increasing. And, finally, solar radio flare works as an external electromagnetic jammer of SV signal at the reception point.

Conclusion! Refractive slant variations of ranging error in radio-propagation media is not the most significant problem for GNSS functioning. Irregular ionospheric events and Solar radio flares appeared unexpectedly and can deteriorate GNSS performance regardless all the means of GNSS quality improvement. GNSS stand alone positioning hardly can provide high positioning quality under Space Weather Hazards environment, let alone effective positioning availability control. In order to provide both high positioning accuracy and reliable positioning availability control Local Area and Wide Area Augmentation Systems are used. Which one is better for transport applications? We will see!

Wide Area Augmentation System:

WAAS performance for ionospheric ranging error correction

WAAS service availability under geomagnetic storms Can WAAS Availability Be Inferred from Geomagnetic Data? An Analysis / Datta-Barua S., [et al.] // In Proceedings of The Beacon Satellite Symposium : (BSS 2005), Trieste, October 18–22. – Italy, 2005.

Positioning availability control algorithm for WAAS The Master Station reference positioning vector: G - The SV-user geometry matrix y – The matrix of corrected SV’s rangings W – Ranging dispersions matrix Alarm protection levels: Confident coefficient of probability of event when positioning error exceeds HAL or VAL:

Conclusion ! Wide Area concept is not the best one to support transport and survival applications under Space Weather Hazards and other sudden impacts

Local Area Augmentation System Local-Area augmentation system seems to better concept to realize both high positioning accuracy and an effective RNP availability control: the smaller coverage zone and the less intermediate computations – the higher confidence in the positioning availability control evaluation

Local Area Augmentation System LAAS provides high positioning quality and RNP availability in case if: 1)Positioning error de-correlation radius is not less than LAAS coverage zone; 2)Positioning error de-correlation time is longer than a period of differential correction; 3)Users can use all SV’s in view in LAAS coverage zone (HDOP and VDOP are approximately the same within the zone) These requirements can be violated under sudden impacts of the Space Weather hazards or as a result of local SV’s signal blackout with some object of infrastructure

Positioning errors de-correlation We used a local GPS-network of GPS-receivers with 1-sec data registration rate under geomagnetically quiet and stormy days (March, 25-th, 2003 and October 29-th, 2003, respectively) in order to evaluate spatial and temporal de-correlation of GPS positioning errors.

Positioning errors de-correlation According to the picture, we can see significant decreasing of the spatial de-correlation radius of all the error partials under magnetic storm. To compare we mark the maximal de-correlation radiuses with red (magnetic storm condition) and with green (quiet conditions). As we can see, the minimal de-correlation radius is about 40 km (for  Z component).

Positioning errors de-correlation There is significant decreasing of the de-correlation time of all the positioning error partials under magnetic storm as well. The de-correlation time varies significantly even under quiet conditions, let alone magnetic storms! The minimal de-correlation time we observed in both California and East-Siberia areas is about seconds. Correlation level τ ΔX (min/max), sτ ΔY (min/max), sτ ΔZ (min/max), s Geo-magnetically quiet conditions (March, 25-th, 2003) 0,7 26/90031/180059/2600 0,5 64/150068/ /2800 Geo-magnetic storm conditions (October, 29-th, 2003) 0,7 18/120023/130026/600 0,5 40/310055/150092/1100 Correlation level τ ΔX (min/max), sτ ΔY (min/max), sτ ΔZ (min/max), s Geo-magnetically quiet conditions (March 4-th, 2005) 0,751/40065/50042/200 0,5110/ /240096/3200 Geo-magnetic storm conditions (November 10-th, 2004) 0,726/10036/25028/1200 0,554/38078/300060/1800 Table 2. Positioning errors de-correlation time at Irkutsk GPS-site Table 1. Positioning errors de-correlation time at GPS-site GOLD (California)

Conclusion! According to the above mentioned, we can provide an adequate positioning errors correction and positioning availability monitoring by means of LAAS in case if: 1)LAAS coverage zone should not exceed 40 km; 2)Differential correction period and a period of positioning availability control should not be longer then 20 seconds

Position Delusion Of Precision It is not so rare event when SV tracking is broken inside of GNSS receiver as a result of radio propagation media disturbances, electromagnetic jummers or because of infrastructure (such as bridges, high buildings et.c.) which blocks SV signals. In case we loose the zenith SV we must expect both sharp PDOP increasing and positioning errors increasing as a result. Of course, we must take such events in account.

Position Delusion Of Precision Here is an example of sudden PDOP increasing as a result of the zenith SV loosing. We can see a coincidence of SV tracking loose, PDOP sharp increasing and positioning error increasing.

Conclusion! Individual PDOP value can change sharply and suddenly and cause correspondent sharp increasing of positioning error. Such events are not so rare but each event can bring serious danger for transport and survival applications. Thus individual current PDOP value has to be taken in account in real-time positioning availability control

The main algorithm for positioning availability control A is the event of that GNSS and LAAS equipment are in working order; B is the event of GNSS user equipment health; C is the event that the current positioning accuracy corresponds to the personal RNP of GNSS+LAAS user during the certain period of time; (1-P FAULT ) is the probability of the absence of positioning failure during the certain period of time; W PDOP is alarm index in order to warn GNSS user about the dangerous level of expected positioning error as a result of the poor current “SV-user” geometry (poor PDOP). We suppose to compute the current positioning availability evaluation as a full probability as follows:

The Aircraft landing application

Probabilities of compliance with the air echelons along the planar and altitudinal axes Alarm index of bad “SV-user” geometry The probability of k number of positioning faults during the landing time

The Railroad traffic control application The features of this application for our method are following: 1.A train moves along a stringent and well known trajectory, so we do not need to take in account planar and altitudinal positioning deviations, but we need to determine an expected error of the current length of the train braking action way, instead; 2.We do not need to warn user about sudden positioning accuracy deterioration in the vertical plane, so the alarm index - W PDOP can be simplified: only threshold value Π HDOP is enough to compute the current value of W PDOP.

The Railroad traffic control application X BR,Y BR - Coordinates of the stop point x tl, y tl – Coordinates of a previous train’s tail in Railroad coordinate system x hd y hd – Next train’s head coordinates in Railroad coordinate system L BR – The braking action way x hd *, y hd *, x tl *, y tl * – Train’s head and tail coordinates which are transformed to the nearest point on railroad Next train’s head Previous train’s tail Braking way

The Railroad traffic control application A probability of hitting inside the Area 2 (trains collision) Alarm index of bad “SV-user” geometry c - is a correlation coefficient between and time series of positioning errors; - are standard means of positioning errors along X and Y axes; - are standard deviations of positioning errors along X and Y axes.

The algorithm of the method implementation GNSS receiver computs: 1.Setting the individual positioning accuracy requirement such as  and  boundaries or positioning error probability and maximal standard deviations and ; 2.Setting the individual admissible number of positioning faults (k) over ΔT time interval; 3.Computing value depending on the application; 4.Computing 5.Computing Π VDOP and Π HDOP ; 6.Computing the current positioning availability evaluation (W) value; LAAS master station PC gets following statistics: 1.The frequency histogram of positioning fault events (P k ) over the observation interval ΔT and the parameter “a” of the Poisson distribution; 2.Current standard means and standard deviations of positioning errors: M(ΔX), M(ΔY), M(ΔZ), σ ΔX, σ ΔY, σ ΔZ which are supposed to be the constant within the LAAS coverage zone during the period of ΔT; 3.Current standard deviation of GPS (GLONASS) SVs ranging (σ ΔRSV ) for all SVs in view which is supposed to be the constant within the LAAS coverage zone during the period of ΔT.

General conclusions 1.The method of positioning availability control is based on the near-real- time measurements of positioning and ranging statistics, so we can expect an adequate result of availability control within LAAS coverage zone under irregular external impacts (geomagnetic storms, electromagnetic jamming, SV signal blocking by infrastructure et. al.). 2.The technique we considered allows taking in account the personal RNP of each user within LAAS coverage zone. This feature of the method is especially important for aircraft landing application. It is well known that personal RNP is changing during the landing process from ICAO CAT I down to ICAO CAT III RNP. Such RNP evolution in time requires a flexible technique of the positioning availability control in near-real time scale. 3.Being taking in account an individual PDOP factor we can warn user about some local features within the coverage zone. This is especially important for the railroad applications when the user often faces to a problem of SVs ranging faults because of the railroad infrastructure objects influence.

Thank you for attention! & Welcome to cooperation! Institute of solar and Terrestrial Physics Siberian Branch of Russian Academy of Science Tel: (3952) , (3952) Fax: (3952) , (3952) Irkutsk State Transport University Russian Federal Agency of Railway Transport Tel.: +7 (395-2) , Fax: +7 (395-2)