T. Sakai, K. Matsunaga, K. Hoshinoo, K. Ito, ENRI T. Walter, Stanford University T. Sakai, K. Matsunaga, K. Hoshinoo, K. Ito, ENRI T. Walter, Stanford University Mitigating Ionospheric Threat Using a Dense Monitoring Network Mitigating Ionospheric Threat Using a Dense Monitoring Network ION GNSS 2007 Fort Worth, TX Sept , 2007

ION GNSS Sept ENRI S LIDE 1 The ionospheric effect is a major error source for SBAS:The ionospheric effect is a major error source for SBAS: –The ionospheric term is dominant factor of protection levels; –Necessary to reduce GIVE values not only in the storm condition but also in the nominal condition to improve availability of vertical guidance. The problem is caused by less density of IPP samples:The problem is caused by less density of IPP samples: –The current planar fit algorithm needs inflation factor (Rirreg) and undersampled threat model to ensure overbounding residual error; –Solution: integrating the external network such as GEONET and CORS; –Developed a GIVE algorithm suitable to such a situation. Evaluated a new GIVE algorithm with GEONET:Evaluated a new GIVE algorithm with GEONET: –100% availability of APV-II (VAL=20m) at most of Japanese Airports; –Still protects users; No HMI condition found. Introduction

ION GNSS Sept ENRI S LIDE 2 MSAS Status Launch of MTSAT-1R (Photo: RSC) All facilities installed:All facilities installed: –2 GEOs: MTSAT-1R (PRN 129) and MTSAT-2 (PRN 137) on orbit; –4 GMSs and 2 RMSs connected with 2 MCSs; –IOC WAAS software with localization. Successfully certified for aviation use:Successfully certified for aviation use: –Broadcast test signal since summer 2005 with Message Type 0; –Certification activities: Fall 2006 to Spring Began IOC service on Sept. 27 JST (15:00 Sept. 26 UTC).Began IOC service on Sept. 27 JST (15:00 Sept. 26 UTC).

ION GNSS Sept ENRI S LIDE 3 Position Accuracy Horizontal RMS 0.50m MAX 4.87m Vertical RMS 0.73m MAX 3.70m GPS MSAS GPS (940058) 05/11/14 to 16 (940058) 05/11/14 to 16 PRN129

ION GNSS Sept ENRI S LIDE 4 The current MSAS is built on the IOC WAAS:The current MSAS is built on the IOC WAAS: –As the first satellite navigation system developed by Japan, the design tends to be conservative; –The primary purpose is providing horizontal navigation means to aviation users; Ionopsheric corrections may not be used; –Achieves 100% availability of Enroute to NPA flight modes. Concerns for MSAS The major concern for vertical guidance is ionosphere:The major concern for vertical guidance is ionosphere: –The ionospheric term is dominant factor of protection levels; –Necessary to reduce GIVE to provide vertical guidance with reasonable availability.

ION GNSS Sept ENRI S LIDE 5 APV-I Availability of IOC MSAS MSAS Broadcast 06/10/17 00:00-24:00 PRN129 (MTSAT-1R) Test Signal Contour plot for: APV-I Availability HAL = 40m VAL = 50m Note: 100% availability of Enroute through NPA flight modes.

ION GNSS Sept ENRI S LIDE 6 Components of VPL The ionospheric term is dominant component of Vertical Protection Level.The ionospheric term is dominant component of Vertical Protection Level. VPL Clock & Orbit (5.33  flt ) Ionosphere (5.33  UIRE ) MSAS Broadcast 06/10/17 00:00-12: Tokyo PRN129 (MTSAT-1R) Test Signal

ION GNSS Sept ENRI S LIDE 7 Problem: Less Density of IPP Ionospheric component: GIVE:Ionospheric component: GIVE: –Uncertainty of estimated vertical ionospheric delay; –Broadcast as 4-bit GIVEI index. Current algorithm: ‘Planar Fit’:Current algorithm: ‘Planar Fit’: –Vertical delay is estimated as parameters of planar ionosphere model; –GIVE is computed based on the formal variance of the estimation. The formal variance is inflated by:The formal variance is inflated by: –Rirreg: Inflation factor based on chi-square statistics handling the worst case that the distribution of true residual errors is not well-sampled; a function of the number of IPPs; Rirreg = 2.38 for 30 IPPs; –Undersampled threat model: Margin for threat that the significant structure of ionosphere is not captured by IPP samples; a function of spatial distribution (weighted centroid) of available IPPs.

ION GNSS Sept ENRI S LIDE 8 Using External Network Integrating the external network to the SBAS:Integrating the external network to the SBAS: –Increase the number of monitor stations and IPP observations dramatically at very low cost; –Just for ionospheric correction; Clock and orbit corrections are still generated by internal monitor stations because the current configuration is enough for these corrections; –Input raw observations OR computed ionospheric delay and GIVE from the external network; loosely-coupled systems. Necessary modifications:Necessary modifications: –A new algorithm to compute vertical ionospheric delay and/or GIVE is necessary because of a great number of observations; –Safety switch to the current planar fit with internal monitor stations when the external network is not available.

ION GNSS Sept ENRI S LIDE 9 Available Network: GEONET GEONET (GPS Earth Observation Network):GEONET (GPS Earth Observation Network): –Operated by Geographical Survey Institute of Japan; –Near 1200 stations all over Japan; –20-30 km separation on average. Open to public:Open to public: –30-second sampled archive is available as RINEX files. Realtime connection:Realtime connection: –All stations have realtime datalink to GSI; –Realtime raw data stream is available via some data providers. GEONET station MSAS station

ION GNSS Sept ENRI S LIDE 10 Sample IPP Distribution A snap shot of all IPPs observed at all GEONET stations at an epoch;A snap shot of all IPPs observed at all GEONET stations at an epoch; GEONET offers a great density of IPP observations;GEONET offers a great density of IPP observations; There are some Japan- shape IPP clusters; each cluster is corresponding to the associated satellite.There are some Japan- shape IPP clusters; each cluster is corresponding to the associated satellite.

ION GNSS Sept ENRI S LIDE 11 New Algorithms (1) Residual Bounding: –An algorithm to compute GIVE for given vertical delays at IGPs; –Vertical delays are given; For example, generated by planar fit; –Determine GIVE based on observed residuals at IPPs located within 5 degrees from the IGP; Not on the formal variance of estimation; –Improves availability of the system. (2) Residual Optimization: –An algorithm to optimize vertical delays at IGPs; –Here ‘Optimum’ means the condition that sum square of residuals is minimized; –GIVE values are generated by residual bounding; –Improves accuracy of the system.

ION GNSS Sept ENRI S LIDE 12 Residual Bounding (1) An algorithm to compute GIVE for given vertical delays at IGPs:An algorithm to compute GIVE for given vertical delays at IGPs: –The MCS knows ionospheric correction function (bilinear interpolation) used in user receivers, I v,broadcast (,  ), for given vertical delays at IGPs broadcast by the MCS itself; –Residual error between the function and each observed delay at IPP, I v,IPPi, can be computed; –Determine GIVE based on the maximum of residuals at IPPs located within 5 degrees from the IGP. Vertical delay for user Observed delay at IPP

ION GNSS Sept ENRI S LIDE 13 Residual Bounding (2) Interpolated plane for users Largest residual Confidence bound Overbounding largest residual IGP iIGP i+1 Vertical Delay Location IPP measurements Determine GIVE based on the maximum of residuals at IPPs located within 5 degrees from the IGP.Determine GIVE based on the maximum of residuals at IPPs located within 5 degrees from the IGP.

ION GNSS Sept ENRI S LIDE 14 Residual Optimization An algorithm to optimize vertical delays at IGPs:An algorithm to optimize vertical delays at IGPs: –Vertical delays at IGPs can also be computed based on IPP observations as well as GIVE values; –Again, define residual error between the user interpolation function and each observed delay at IPP, I v,IPPi ; –The optimum set of vertical delays minimizes the sum square of residuals; GIVE values are minimized simultaneously; –The optimization can be achieved by minimizing the energy function (often called as cost function) following over IGP delays (See paper): Function of IGP delays

ION GNSS Sept ENRI S LIDE 15 Number of Available IPPs The histogram of the number of IPPs available at each IGP (located within 5 deg from the IGP);The histogram of the number of IPPs available at each IGP (located within 5 deg from the IGP); For 68% cases, 100 or more IPPs are available;For 68% cases, 100 or more IPPs are available; Exceeds 1000 for 27% cases.Exceeds 1000 for 27% cases.

ION GNSS Sept ENRI S LIDE 16 GIVE by Residual Bounding (1) Histogram of computed GIVE values in typical ionospheric condition for two algorithms;Histogram of computed GIVE values in typical ionospheric condition for two algorithms; Residual bounding with GEONET offers significantly reduced GIVE values;Residual bounding with GEONET offers significantly reduced GIVE values; Blue lines indicate quantization steps for GIVEI.Blue lines indicate quantization steps for GIVEI. Planar Fit Residual Bounding (All GEONET sites)

ION GNSS Sept ENRI S LIDE 17 GIVE by Residual Bounding (2) Histogram of computed GIVE values in severe storm condition for two algorithms;Histogram of computed GIVE values in severe storm condition for two algorithms; The result is not so different from case of typical condition.The result is not so different from case of typical condition. Planar Fit Residual Bounding (All GEONET sites)

ION GNSS Sept ENRI S LIDE 18 Reduction of GIVEI Histogram of 4-bit GIVEI index broadcast to users;Histogram of 4-bit GIVEI index broadcast to users; Lower limit of GIVEI is 10 for planar fit;Lower limit of GIVEI is 10 for planar fit; Residual bounding can reduce GIVEI as well as GIVE values.Residual bounding can reduce GIVEI as well as GIVE values. Planar Fit Residual Bounding (All GEONET sites)

ION GNSS Sept ENRI S LIDE 19 Comparison with FOC WAAS FOC WAAS: Dynamic Rirreg, RCM, multi- state storm detector, and CNMP;FOC WAAS: Dynamic Rirreg, RCM, multi- state storm detector, and CNMP; GIVE values derived by residual bounding are still smaller than FOC WAAS algorithms.GIVE values derived by residual bounding are still smaller than FOC WAAS algorithms. Planar Fit (FOC WAAS) Residual Bounding (All GEONET sites)

ION GNSS Sept ENRI S LIDE 20 Residual Optimization Histogram of difference of IGP delays with and without residual optimization;Histogram of difference of IGP delays with and without residual optimization; Adjustment of IGP delay stays 0.052m;Adjustment of IGP delay stays 0.052m; In comparison with quantization step of 0.125m, the effect is little.In comparison with quantization step of 0.125m, the effect is little.

ION GNSS Sept ENRI S LIDE 21 User Position Accuracy User vertical position error at Tokyo in typical ionospheric condition;User vertical position error at Tokyo in typical ionospheric condition; Residual bounding improves user position accuracy, while residual optimization is not effective so much.Residual bounding improves user position accuracy, while residual optimization is not effective so much. Residual Optimization (RMS = 1.10m) Residual Bounding (RMS = 1.10m) Planar Fit (RMS = 1.47m)

ION GNSS Sept ENRI S LIDE 22 Evaluation by Prototype SBAS Prototype SBAS software developed by ENRI (NTM 2006):Prototype SBAS software developed by ENRI (NTM 2006): –Computer software running on PC or UNIX; –Generates the complete 250-bit SBAS messages every seconds; –Simulates MSAS performance with user receiver simulator; –Available as an MSAS testbed; Measures benefit of additional monitor stations and evaluates new candidate algorithms. Integration with the proposed algorithms:Integration with the proposed algorithms: –Scenario of vertical ionospheric delay and GIVE is generated based on GEONET archive data with application of the proposed algorithms; –The prototype generated augmentation messages with ionospheric corrections induced as the scenario; –Tested for typical ionospheric condition (July 2004) and severe storm condition (October 2003).

ION GNSS Sept ENRI S LIDE 23 User Protection PPWAD Simulation 03/10/ Tokyo Condition: Severe Storm Algorithm: Residual Bounding (All GEONET sites) Users are still protected by this algorithm during the severe storm.

ION GNSS Sept ENRI S LIDE 24 System Availability PPWAD Simulation 04/7/22-24 Condition: Typical Ionosphere Algorithm: Residual Bounding (All GEONET sites) Contour plot for: APV-II Availability HAL = 40m VAL = 20m

ION GNSS Sept ENRI S LIDE 25 Introduced new algorithms and usage of the external network to mitigate ionospheric threats:Introduced new algorithms and usage of the external network to mitigate ionospheric threats: –Algorithms for bounding ionospheric corrections based on optimization of residual error measured by dense monitoring network; –Integration of GEONET as an external network. Evaluation by prototype SBAS software:Evaluation by prototype SBAS software: –Reduced GIVEI enables 100% availability of APV-II flight mode (VAL=20m) at most of Japanese airports; –No integrity failure (HMI condition). Further investigations:Further investigations: –Consideration of threats against the proposed algorithms; –Reduction of the number of stations required for residual bounding; –Temporal variation and scintillation effects. Conclusion

ION GNSS Sept ENRI S LIDE 26Announcement Ionospheric delay database will be available shortly:Ionospheric delay database will be available shortly: –The datasets used in this study; and –Recent datasets generated daily from August 2007; –Each dataset is a file which consists of slant delays observed at all available GEONET stations with 300-second interval; Hardware biases of satellites and receivers are removed; Access to URL: