Reinforcement information generation system, reinforcement information generation method, and reinforcement information generation program

Abstract

To provide a reinforcement information generation system capable of improving availability and location accuracy while reducing the impact of ionospheric disturbances on GNSS (Global Navigation Satellite System) by using observed data on ionospheric disturbances when generating reinforcement information.SOLUTION: A satellite selection device 100 of a reinforcement information generation system 90 includes a satellite selection unit 130. The satellite selection unit 130 selects multiple satellites that are less susceptible to ionospheric disturbances during the target period at the target electronic reference point based on an ionospheric forecast showing regions of ionospheric disturbances predicted based on observed ionospheric data visible satellite forecast showing multiple satellites capable of observation from target electronic reference station during the target period.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present disclosure relates to a supplemental information generation system, a supplemental information generation method, and a supplemental information generation program. [Background technology]

[0002] GNSS (Global Navigation Satellite System) is a system that uses radio waves transmitted from satellites to determine a position (positioning). The radio waves transmitted from satellites contain errors, and the most basic positioning method can usually determine a position with an accuracy of about a few meters. By calculating the amount of error at a known position and taking the difference between the amount of error thus calculated and the amount of error at the currently desired position, which is correlated in time and space, it is possible to correct and reduce the error. RTK-GPS (Real Time Kinematic-Global Positioning System) is known as one of the highly accurate error correction methods, and a technology that further develops RTK-GPS is PPP (Precise Point Positioning)-RTK (Non-Patent Document 1). In these technologies, it is necessary to observe signals from positioning satellites without interruption in order to accurately estimate the amount of error (correction information).

[0003] One of the factors that interrupts signal observation is the influence of an atmospheric layer called the ionosphere. The behavior of the ionosphere can have spatial and temporal characteristics, or it can be sudden. Therefore, it is difficult to accurately predict the influence of the ionosphere. Here, by taking advantage of such influence on signals, ionosphere observations using GNSS have been performed (Non-Patent Document 2). However, the ionosphere has a multi-layer structure and a wide spatial size. Therefore, it is practically difficult to observe the entire ionosphere using GNSS. Therefore, a method of observing the ionosphere using a frequency band different from the GNSS frequency band is also being considered (Non-Patent Document 3). [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Patent No. 5570649 [Non-patent literature]

[0005] [Non-Patent Document 1] Wubbena, Gerhard, Schmitz, Martin, Bagge, Andreas, “PPP-RTK: Precise Point Positioning Using State-Space Representation in RTK Networks”, Proceedings of the 18th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS 2005), Long Beach, CA, September 2005, pp. 2584-2594. [Non-Patent Document 2] T. Tsugawa, M. Nishioka, A. Saito, Y. Otsuka, S. Saito, T. Maruyama, T. Nagatsuma, KTMurata, and M. Ishii, “High-resolution ionospheric total electron content observations using dense GNSS receiver networks”, 38th COSPAR Scientific Assembly. Held 18-15 July 2010, in Bremen, Germany, p.13 [Non-Patent Document 3] Otsuka, Y., Ogawa, T. and Effendy, “VHF radar observations of nighttime F-region field-aligned irregularities over Kototabang, Indonesia.”, Earth Planet Sp 61, 431-437 (2009) Summary of the Invention [Problem to be solved by the invention]

[0006] When generating correction information, the GNSS signal (carrier phase) received at the CORS is used. The correction information is realized by using the received signal information to estimate the error value based on a certain model using a Kalman filter or the like. Here, the GNSS signal needs to be observed continuously. When the signal observation is interrupted (hereinafter referred to as cycle slip), the filter that estimates the error value is reset, so the error value needs to be estimated again. In particular, when a cycle slip occurs in a satellite located at a high elevation angle, the effects of the cycle slip that occurs will spread to the entire system. This is because when generating correction information, a satellite located at a high elevation angle is generally used as the reference satellite, and the difference between the observation amount of the reference satellite and the observation amount of other satellites is used.

[0007] Usually, cycle slips occur more often in signals received from satellites located at low elevation angles. This is because the path taken when receiving a signal from a satellite located at a low elevation angle is longer than the path taken when receiving a signal from a satellite located at a high elevation angle. The longer the path, the longer the time the signal takes to pass through the atmosphere, making the signal more susceptible to the effects of the atmosphere. In addition, the presence of buildings or other objects that block radio waves along the path at low elevation angles can also have an effect.

[0008] On the other hand, cycle slips rarely occur in signals received from satellites located at high elevation angles, but if scintillation due to sudden ionospheric disturbances (plasma bubbles, etc.) occurs, cycle slips can occur even at high elevation angles. Here, if cycle slips occur infrequently, they do not significantly affect the generation of correction information, but if ionospheric disturbances occur in the atmosphere, cycle slips occur frequently, making it difficult to generate correction information.

[0009] With conventional technology, it is possible to detect ionospheric disturbances that are currently occurring from GNSS observations, but it is difficult to predict and avoid their occurrence in advance. Therefore, ionospheric disturbances are one of the challenges in GNSS position estimation and in the generation of augmentation information, which is an applied technology. Ionospheric disturbances are particularly likely to occur in the southern part of Japan (Okinawa and the Ogasawara Islands, etc.) and in low-latitude areas such as Southeast Asia, where cycle slip problems are highly likely to occur. The present disclosure aims to reduce the impact of ionospheric disturbances on GNSS and improve availability and positioning accuracy by utilizing data observed from ionospheric disturbances when generating augmentation information. [Means for solving the problem]

[0010] The reinforcement information generation system according to the present disclosure includes: a satellite selection unit that selects, from among a plurality of satellites in a GNSS (Global Navigation Satellite System), a plurality of satellites that are unlikely to be affected by ionospheric disturbances at a target electronic reference point during the target period, based on an ionospheric forecast that indicates an ionospheric disturbance region, which is a region predicted based on ionospheric disturbances detected based on a result of observing the ionosphere and is a region where ionospheric disturbances will occur during a target period, and a visible satellite forecast that indicates, as a plurality of observable satellites, a plurality of satellites that can be observed from a target electronic reference point, which is an electronic reference point used to generate augmentation information, which is information that augments positioning by the GNSS, during the target period, from the plurality of observable satellites, and generates a reference satellite list indicating the plurality of selected satellites. A satellite selection device comprising: Equipped with. Effect of the Invention

[0011] According to the present disclosure, a plurality of satellites that are less susceptible to ionospheric disturbances are selected based on an ionospheric forecast based on observed ionospheric disturbances. The selected plurality of satellites are used in generating augmentation information. Therefore, according to the present disclosure, by using data obtained by observing ionospheric disturbances using some means, such as a VHF (Very High Frequency) radar, when generating augmentation information, it is possible to reduce the impact of ionospheric disturbances on GNSS and improve availability and position accuracy. [Brief description of the drawings]

[0012] [Figure 1] FIG. 2 is a diagram showing an example of the configuration of a reinforcement information generation system 90 according to the first embodiment. [Diagram 2] FIG. 2 is a diagram for explaining an ionospheric forecast and a visible satellite forecast according to the first embodiment. [Diagram 3] A diagram explaining the state of the sky. [Figure 4] 1 is a diagram showing an example of a hardware configuration of a satellite selecting device 100 according to a first embodiment. [Diagram 5] FIG. 13 is a diagram showing an example of a hardware configuration of a satellite selecting device 100 according to a modification of the first embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0013] In the description of the embodiments and the drawings, the same elements and corresponding elements are given the same reference numerals. Descriptions of elements given the same reference numerals are omitted or simplified as appropriate. Arrows in the drawings primarily indicate data flow or processing flow. In addition, "part" may be read as "circuit," "step," "procedure," "processing," or "circuitry" as appropriate. In this disclosure, "satellite" refers to a positioning satellite. A positioning satellite is an artificial satellite of the Global Navigation Satellite System (GNSS).

[0014] Embodiment 1 Hereinafter, the present embodiment will be described in detail with reference to the drawings. The present embodiment relates to a method of inputting data for generating GNSS correction information.

[0015] ***Configuration Description*** Fig. 1 shows an example of the configuration of a reinforcement information generation system 90 according to this embodiment. As shown in Fig. 1, the reinforcement information generation system 90 includes a reference point 20, an ionosphere observation device 30, a satellite selection device 100, a reinforcement information generation device 200, and a reinforcement information distribution device 300. The multiple devices included in the reinforcement information generation system 90 may be configured integrally.

[0016] There are a plurality of electronic reference points 20. A plurality of electronic reference points 20 form an electronic reference point network. The electronic reference points 20 are also simply called reference points. Each electronic reference point 20 transmits observation data acquired by each electronic reference point 20 and data indicating the coordinate values ​​of each electronic reference point 20 to the satellite selection device 100.

[0017] The ionospheric observation device 30 observes the ionosphere and detects ionospheric disturbances based on the observation results. A specific example of the ionospheric observation device 30 is a VHF (Very High Frequency) radar. A specific example of the ionospheric disturbance is a plasma bubble. The ionospheric observation device 30 transmits ionospheric observation data indicating the observation results to the satellite selection device 100.

[0018] The satellite selection device 100 includes a visible satellite prediction unit 110, an ionosphere prediction unit 120, and a satellite selection unit .

[0019] The visible satellite prediction unit 110 generates a visible satellite forecast for a target period. Specifically, the visible satellite prediction unit 110 receives observation data and data indicating coordinate values ​​from each CORS 20, and uses the received data to calculate, from the navigation calendar, a combination of satellites that can be observed from each CORS 20 during the target period. The length of the target period may be determined in any manner. The visible satellite forecast indicates, among the multiple satellites in the GNSS, multiple satellites that can be observed from the target CORSs during the target period as multiple observable satellites. The target CORSs are each CORSs 20 used when generating correction information.

[0020] The ionospheric prediction unit 120 generates an ionospheric forecast for a target period. Specifically, the ionospheric prediction unit 120 receives data indicating the results of detection of ionospheric disturbances from the ionospheric observation device 30, and predicts the time change of ionospheric disturbances for the target period based on the received data. A specific example of the result of detection of ionospheric disturbances is the result of detection of plasma bubble spots. A specific example of the time change of ionospheric disturbances is the time change of plasma bubble spots. The ionospheric forecast indicates an ionospheric disturbance region. The ionospheric disturbance region is a region predicted based on ionospheric disturbance detected based on the result of observing the ionosphere by the ionospheric observation device 30, and is a region where ionospheric disturbance occurs during a target period. The ionospheric forecast may indicate the ionospheric disturbance region at each time during the target period.

[0021] The satellite selection unit 130 predicts the visible path that will be affected by ionospheric disturbances in the target period for each CORS 20 based on the generated ionospheric forecast and visible satellite forecast, and removes satellites that pass through the elevation angle and azimuth angle for the predicted visible path from the selection candidates of the reference satellite. The satellite selection unit 130 selects multiple satellites that are unlikely to be affected by ionospheric disturbances in the target period at the target CORS from multiple observable satellites, and generates a reference satellite list indicating the selected multiple satellites. The reference satellite list is also called a list of satellites for which augmentation information is generated, and is a list indicating satellites for which augmentation information is generated. The augmentation information is information that augments positioning by GNSS, and is composed of correction information and a quality index. Each value is stored in the augmentation information for each satellite. The correction information is information related to positioning by GNSS, and is information included in the augmentation information. When each of the multiple satellites in the GNSS is selected as a target satellite, the satellite selection unit 130 may select multiple satellites by taking into consideration the length of the visible time of the target satellite at the target CORS and the degree to which the signal transmitted by the target satellite at the target CORS is affected by ionospheric disturbance. The process of the satellite selection unit 130 is called a target satellite determination algorithm. As a specific example, the satellite selection unit 130 selects a predetermined number of reference satellites in order based on the ionospheric forecast and the visible satellite forecast, taking into consideration the degree of resistance to the effects of ionospheric disturbances and the length of visibility time. The satellite selection unit 130 also predicts the degree to which each satellite will be affected by ionospheric disturbances based on the observation results by the ionospheric observation device 30, and quantifies the prediction results as a degradation index. At this time, the satellite selection unit 130 calculates the degree to which each of the selected multiple satellites will be affected by ionospheric disturbances based on the ionospheric forecast as a degradation index, and includes the calculated degradation index in the reference satellite list.

[0022] The supplementary information generating device 200 includes a supplementary information generating unit 210 . The reinforcement information generation unit 210 receives data indicating a reference satellite list indicating each reference satellite and a deterioration index corresponding to each satellite from the satellite selection unit 130. The reinforcement information generation unit 210 also receives data indicating an ionospheric forecast from the ionospheric prediction unit 120. The reinforcement information generation unit 210 generates correction information using the received data. By having the supplementary information generator 210 select satellites based on the reference satellite list, it is expected that observation loss due to cycle slip and the effect of observation loss on correction information generation will be kept relatively low, and robustness will be improved. Furthermore, by the augmentation information generation unit 210 adaptively changing the parameters in error estimation based on the degradation index corresponding to each satellite, it is expected that the quality of the correction amount will be maintained high even during times when the effects of ionospheric disturbances are significant. Furthermore, the augmentation information generating unit 210 calculates a quality index of the ionospheric correction term in the augmentation information based on the deterioration index corresponding to each satellite and the generation status of the correction information. The quality index corresponds to a quality index. That is, the reinforcing information generating unit 210 generates correction information for positioning based on the signals transmitted by each of the multiple satellites indicated in the reference satellite list and the ionospheric forecast, and calculates an index indicating the degree of accuracy degradation of the reinforcing information due to ionospheric disturbances at each satellite indicated by the reinforcing information as a quality index based on the ionospheric forecast, the generated correction information, and the error included in the ranging result estimated based on the ranging result at the ranging reference point. The ranging reference point is an ERP 20 used when calculating the ranging error using the generated correction amount. The ranging reference point may be the same ERP 20 as the target ERP, or may be an ERP 20 different from the target ERP.

[0023] The reinforcement information distribution device 300 includes a reinforcement information distribution unit 310 . The reinforcement information distribution unit 310 distributes the reinforcement information and information indicating the index calculated by the reinforcement information generation unit 210. Specifically, the reinforcement information distribution unit 310 receives the reinforcement information and information indicating the quality index from the reinforcement information generation unit 210, and distributes the received reinforcement information to end users. In addition, the reinforcement information distribution unit 310 notifies end users of the effects of ionospheric disturbances based on the quality index calculated by the reinforcement information generation unit 210.

[0024] Existing quality indices are based on GNSS observables and data calculated during the process using the GNSS observables. On the other hand, in the present embodiment, in calculating the quality index, observation data showing the observation result of a radar observing the ionosphere is used directly or indirectly in combination. Therefore, according to the present embodiment, it is possible to calculate a higher quality index. The radar observing the ionosphere may be a sensor other than the GNSS. Furthermore, according to the present embodiment, by combining the visible satellite forecast with the ionospheric forecast, it is possible to notify the user in advance of satellites that will be affected by ionospheric disturbances. The user can realize robust self-location estimation by selectively using satellites to perform positioning based on the notified information.

[0025] FIG. 2 is a diagram explaining an ionospheric forecast and a visible satellite forecast. 2, the ionospheric disturbances predicted based on the observation results by the ionospheric observation device 30 and indicated by the ionospheric forecast are shown. The positions of the positioning satellites are those indicated by the visible satellite forecast. In this example, the positioning signal transmitted by the positioning satellite A is not affected by ionospheric disturbances at each electronic reference point 20, but the positioning signal transmitted by the positioning satellite B is affected by ionospheric disturbances. Therefore, in this example, the positioning satellite A is selected as the reference satellite corresponding to each electronic reference point 20, but the positioning satellite B is not selected.

[0026] Fig. 3 is a view of the sky from a specific CORS 20 used to generate augmentation information at a certain time during the target period. Fig. 3 shows an area where ionospheric disturbances are occurring at the target time, satellites that are affected by ionospheric disturbances among those observable from the CORS 20, and satellites that are not affected by ionospheric disturbances among those observable from the CORS 20. The satellite selection unit 130 selects a reference satellite from among satellites that are not affected by ionospheric disturbances.

[0027] 4 shows an example of the hardware configuration of satellite selection device 100 according to this embodiment. Satellite selection device 100 is made up of a computer. Satellite selection device 100 may be made up of multiple computers.

[0028] As shown in the figure, the satellite selection device 100 is a computer equipped with hardware such as a processor 11, a memory 12, an auxiliary storage device 13, an input / output IF (Interface) 14, and a communication device 15. These pieces of hardware are appropriately connected via signal lines 19.

[0029] The processor 11 is an integrated circuit (IC) that performs arithmetic processing and controls the hardware of the computer. Specific examples of the processor 11 include a central processing unit (CPU), a digital signal processor (DSP), and a graphics processing unit (GPU). The satellite selecting device 100 may include a plurality of processors that replace the processor 11. The plurality of processors share the role of the processor 11.

[0030] The memory 12 is typically a volatile storage device, and a specific example is a RAM (Random Access Memory). The memory 12 is also called a primary storage device or a main memory. Data stored in the memory 12 is saved in the auxiliary storage device 13 as necessary.

[0031] The auxiliary storage device 13 is typically a non-volatile storage device, and specific examples thereof include a ROM (Read Only Memory), an HDD (Hard Disk Drive), or a flash memory. Data stored in the auxiliary storage device 13 is loaded into the memory 12 as necessary. The memory 12 and the auxiliary storage device 13 may be integrated into one unit.

[0032] The input / output IF 14 is a port to which an input device and an output device are connected. A specific example of the input / output IF 14 is a Universal Serial Bus (USB) terminal. Specific examples of the input device are a keyboard and a mouse. A specific example of the output device is a display.

[0033] The communication device 15 is a receiver and a transmitter, and is, for example, a communication chip or a network interface card (NIC).

[0034] Each unit of the satellite selecting device 100 may use the input / output IF 14 and the communication device 15 as appropriate when communicating with other devices.

[0035] The auxiliary storage device 13 stores a reinforcement information generation program. The reinforcement information generation program is a program that causes a computer to realize the functions of each unit of each device included in the reinforcement information generation system 90. The reinforcement information generation program is loaded into the memory 12 and executed by the processor 11. The functions of each unit included in the satellite selection device 100 are realized by software.

[0036] Data used when executing the reinforcement information generation program and data obtained by executing the reinforcement information generation program are appropriately stored in a storage device. Each part of the satellite selection device 100 appropriately uses a storage device. As a specific example, the storage device is composed of at least one of the memory 12, the auxiliary storage device 13, a register in the processor 11, and a cache memory in the processor 11. Note that the terms "data" and "information" may have the same meaning. The storage device may be independent of the computer. The functions of the memory 12 and the auxiliary storage device 13 may be realized by other storage devices.

[0037] The supplementary information generation program may be recorded in a computer-readable non-volatile recording medium. Specific examples of the non-volatile recording medium include an optical disk and a flash memory. The supplementary information generation program may be provided as a program product. The hardware configurations of the other devices included in the reinforcement information generating system 90 may be similar to the hardware configuration of the satellite selecting device 100 .

[0038] ***Explanation of Operation*** The operation procedure of each device included in the reinforcement information generation system 90 corresponds to an reinforcement information generating method. Also, the program that realizes the operation of each device included in the reinforcement information generation system 90 corresponds to an reinforcement information generating program.

[0039] One of the PPP-RTK methods is the Centimeter-Level Augmentation Service (CLAS). CLAS covers all of Japan, including low-latitude areas such as Ishigaki Island and the Ogasawara Islands. Irregular fluctuations are likely to occur in low-latitude areas due to the high activity of the ionosphere. Irregular fluctuations cause cycle slips in GNSS signals. Therefore, the occurrence of irregular fluctuations carries the risk of reducing the quality of augmentation information and affecting its continuity.

[0040] Therefore, by applying this embodiment and utilizing ionospheric forecasts based on data obtained by observing the ionosphere, it is possible to exclude satellites at elevation and azimuth angles where ionospheric disturbances occur and satellites affected by ionospheric disturbances from targets for generating augmentation information, or to lower the weights corresponding to these satellites. This makes it possible to suppress deterioration in the quality of augmentation information and ensure continuity, and is expected to improve the quality of the augmentation information of CLAS. In addition, ionospheric variations occur not only in low-latitude regions, but also from Honshu to Hokkaido in the form of medium-scale propagating ionospheric disturbances (MSTIDs). It is known that MSTIDs also affect the quality of augmentation information. It is expected that the quality of augmentation information for MSTIDs will also be improved by utilizing ionospheric forecasts.

[0041] Furthermore, when generating the augmentation information, the augmentation information generating unit 210 estimates the accuracy degradation due to ionospheric disturbances from the ionospheric forecast information and the error estimate value. Data indicating the estimated accuracy degradation is distributed to the user. This allows the user to realize robust and relatively accurate positioning by adaptively changing parameters according to the ionospheric state based on the distributed data and performing positioning.

[0042] ***Explanation of the Effects of the First Embodiment*** As described above, according to this embodiment, it is possible to improve the quality (accuracy) and robustness of the GNSS augmentation information by using an ionospheric forecast based on the observation results of an ionospheric observation device 30 such as a VHF radar. Specifically, according to this embodiment, it is possible to predict in advance the occurrence of cycle slips due to ionospheric disturbances such as plasma bubbles using observation sensors other than the GNSS, and to avoid using observation data corresponding to satellites expected to be affected by ionospheric disturbances, thereby making it possible to expect improvements in quality and continuity. Furthermore, even if degradation of GNSS augmentation information cannot be prevented by prior prediction, it is possible to absorb errors on the user side by adaptively changing estimated parameters through cooperation with observation sensors other than GNSS and by notifying the user of the degradation index.

[0043] In addition, when generating correction information, the integer bias is solved using a specific satellite located at a high elevation angle as the reference satellite. Normally, cycle slips rarely occur in satellites located at high elevation angles. However, cycle slips may occur due to the effects of scintillation caused by ionospheric disturbances such as plasma bubbles. When a cycle slip occurs in the reference satellite, the integer bias must be re-estimated, and the effects will spread to the entire system. In conventional technology, although ionospheric disturbances can be detected by GNSS observations, there is a problem in that it is not possible to predict and avoid ionospheric disturbances in advance. According to this embodiment, the satellites likely to be affected by ionospheric disturbances at each CORS 20 are identified using the "ionospheric forecast" showing the results of predicting the time-dependent change in ionospheric disturbance conditions based on the observation results by the ionospheric observation device 30 and the "visible satellite forecast" showing the results of calculating the combination of satellites observable from each CORS 20, and the identified satellites are removed from the candidates for the reference satellite. When the reference satellite is not affected by cycle slip, re-estimation of the integer bias is not required, and the number of satellites required for generating correction information can be secured. Therefore, in this case, the positioning augmentation service can be continued even if ionospheric disturbances occur.

[0044] ***Other configurations*** <Variation 1> FIG. 5 shows an example of the hardware configuration of the satellite selecting device 100 according to this modified example. The satellite selection device 100 includes a processing circuit 18 in place of the processor 11 , the processor 11 and memory 12 , the processor 11 and auxiliary storage device 13 , or the processor 11 , memory 12 , and auxiliary storage device 13 . The processing circuit 18 is hardware that realizes at least a part of each unit of the satellite selecting device 100 . The processing circuitry 18 may be dedicated hardware, or may be a processor that executes programs stored in the memory 12 .

[0045] When processing circuitry 18 is dedicated hardware, processing circuitry 18 may be, for example, a single circuit, a composite circuit, a programmed processor, a parallel programmed processor, an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or a combination thereof. The satellite selecting device 100 may include a plurality of processing circuits that replace the processing circuit 18. The plurality of processing circuits share the role of the processing circuit 18.

[0046] In the satellite selection device 100, some of the functions may be realized by dedicated hardware, and the remaining functions may be realized by software or firmware.

[0047] Processing circuitry 18 is illustratively implemented in hardware, software, firmware, or a combination thereof. The processor 11, memory 12, auxiliary storage device 13, and processing circuit 18 are collectively referred to as the “processing circuitry.” In other words, the functions of the functional components of the satellite selection device 100 are realized by the processing circuitry. The hardware configurations of other devices included in the reinforcement information generation system 90 may be the same as those of this modified example.

[0048] ***Other embodiments*** Although the first embodiment has been described, it is possible to combine a plurality of parts of the present embodiment. Alternatively, it is possible to partially implement the present embodiment. In addition, the present embodiment may be modified in various ways as necessary, and may be implemented in any combination, either as a whole or in part. The above-described embodiment is essentially a preferred example, and is not intended to limit the scope of the present disclosure, its applications, and uses. The procedure may be appropriately changed.

[0049] Various aspects of the present disclosure are summarized below as appendices.

[0050] (Appendix 1) a satellite selection unit that selects, from among a plurality of satellites in a GNSS (Global Navigation Satellite System), a plurality of satellites that are unlikely to be affected by ionospheric disturbances at the target electronic reference point during the target period, based on an ionospheric forecast indicating an ionospheric disturbance region, which is a region predicted based on ionospheric disturbances detected based on a result of observing the ionosphere, and which is a region where ionospheric disturbances occur at an electronic reference point used for generating augmentation information, which is information that augments positioning by the GNSS, during a target period, and a visible satellite forecast indicating a plurality of satellites that can be observed from the target electronic reference point during the target period as a plurality of observable satellites, and generates a reference satellite list indicating the selected plurality of satellites. A satellite selection device comprising: An augmentation information generation system comprising:

[0051] (Appendix 2) The augmentation information generation system described in Appendix 1, wherein the satellite selection unit selects multiple satellites when each of multiple satellites in the GNSS is a target satellite, taking into consideration the length of visibility of the target satellite at the target electronic reference point and the degree to which the signal transmitted by the target satellite at the target electronic reference point is affected by ionospheric disturbances.

[0052] (Appendix 3) The augmentation information generation system described in Appendix 1 or 2, wherein the satellite selection unit calculates the degree of influence of ionospheric disturbances for each of the selected multiple satellites based on the ionospheric forecast as a degradation index, and includes the calculated degradation index in the reference satellite list.

[0053] (Appendix 4) The reinforcement information generation system further comprises: a reinforcing information generating unit that generates correction information, which is information related to the GNSS positioning based on the signals transmitted by each of the multiple satellites indicated in the reference satellite list and the ionospheric forecast, and calculates an index indicating a degree of accuracy degradation of the reinforcing information due to ionospheric disturbances in each satellite indicated in the reinforcing information, based on the ionospheric forecast, the generated correction information, and an error included in the ranging result estimated based on the ranging result at a ranging reference point that is an electronic reference point. A device for generating reinforcement information comprising: 3. The reinforcement information generation system according to claim 1 or 2, comprising:

[0054] (Appendix 5) The reinforcement information generation system further comprises: a supplementary information distribution unit that distributes the supplementary information and information indicating the calculated index; A reinforcement information distribution device comprising: 5. The reinforcement information generation system of claim 4, comprising: [Explanation of symbols]

[0055] 11 processor, 12 memory, 13 auxiliary storage device, 14 input / output IF, 15 communication device, 18 processing circuit, 19 signal line, 20 electronic reference station, 30 ionospheric observation device, 90 augmentation information generation system, 100 satellite selection device, 110 visible satellite prediction unit, 120 ionospheric prediction unit, 130 satellite selection unit, 200 augmentation information generation device, 210 augmentation information generation unit, 300 augmentation information distribution device, 310 augmentation information distribution unit.

Claims

1. a satellite selection unit that selects, from among a plurality of satellites in a GNSS (Global Navigation Satellite System), a plurality of satellites that are unlikely to be affected by ionospheric disturbances at the target electronic reference point during the target period, based on an ionospheric forecast that indicates an ionospheric disturbance region, which is a region predicted based on ionospheric disturbances detected based on a result of observing the ionosphere and is a region where ionospheric disturbances will occur during a target period, and a visible satellite forecast that indicates, as a plurality of observable satellites, a plurality of satellites that can be observed from a target electronic reference point, which is an electronic reference point used to generate augmentation information, which is information that augments positioning by the GNSS, during the target period, from the plurality of observable satellites, and generates a reference satellite list indicating the plurality of selected satellites. A satellite selection device comprising: An augmentation information generation system comprising:

2. The reinforcement information generation system of claim 1, wherein the satellite selection unit selects a plurality of satellites when each of a plurality of satellites in the GNSS is a target satellite, taking into consideration the length of visibility of the target satellite at the target electronic reference point and the degree to which the signal transmitted by the target satellite at the target electronic reference point is affected by ionospheric disturbances.

3. The reinforcement information generation system according to claim 1 or 2, wherein the satellite selection unit calculates a degree of influence of ionospheric disturbances for each of the selected plurality of satellites based on the ionospheric forecast as a degradation index, and includes the calculated degradation index in the reference satellite list.

4. The reinforcement information generation system further comprises: a reinforcing information generating unit that generates correction information, which is information related to the positioning by the GNSS based on the signals transmitted by each of the multiple satellites indicated in the reference satellite list and the ionospheric forecast, and calculates an index indicating a degree of accuracy degradation of the reinforcing information due to ionospheric disturbances in each satellite indicated in the reinforcing information, based on the ionospheric forecast, the generated correction information, and an error included in the ranging result estimated based on the ranging result at a ranging reference point that is an electronic reference point. A device for generating reinforcement information comprising: The system for generating reinforcement information according to claim 1 or 2, comprising:

5. The reinforcement information generation system further comprises: a supplementary information distribution unit that distributes the supplementary information and information indicating the calculated index; A reinforcement information distribution device comprising: The system for generating reinforcement information according to claim 4 .

6. A method for generating augmentation information, in which a computer selects, from among a plurality of satellites in a GNSS (Global Navigation Satellite System), a plurality of satellites that are less likely to be affected by ionospheric disturbances at a target electronic reference point during a target period, based on an ionospheric forecast indicating an ionospheric disturbance region, which is a region predicted based on ionospheric disturbances detected based on results of observing the ionosphere, where ionospheric disturbances will occur during a target period, and a visible satellite forecast indicating, as a plurality of observable satellites, a plurality of satellites that can be observed from a target electronic reference point, which is an electronic reference point used to generate augmentation information, which is information that augments positioning by the GNSS, during the target period, and generates a reference satellite list indicating the selected plurality of satellites.

7. A satellite selection process for selecting, from among a plurality of satellites in a GNSS (Global Navigation Satellite System), a plurality of satellites that are unlikely to be affected by ionospheric disturbances at a target electronic reference point during the target period, based on an ionospheric forecast indicating an ionospheric disturbance region, which is a region predicted based on ionospheric disturbances detected based on a result of observing the ionosphere and in which ionospheric disturbances will occur during a target period, and a visible satellite forecast indicating, as a plurality of observable satellites, a plurality of satellites that can be observed from a target electronic reference point, which is an electronic reference point used to generate augmentation information, which is information that augments positioning by the GNSS, during the target period, from the plurality of observable satellites, and generating a reference satellite list indicating the plurality of selected satellites. A reinforcement information generating program that causes a satellite selection device, which is a computer, to execute the above.

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