JP5616702B2 - GNSS analysis system, GNSS analysis apparatus, and GNSS analysis program - Google Patents

Description

  The present invention mainly relates to a GNSS analyzer. Specifically, the present invention relates to a configuration for performing on-site baseline analysis that combines high speed and high accuracy with a GNSS analyzer.

  In a danger zone where a disaster such as a landslide is likely to occur, a ground monitoring system may be installed to monitor a slight displacement of the ground or a structure. In recent years, displacement monitoring using a GNSS (Global Navigation Satellite System) has been adopted for such a ground monitoring system.

  Conventionally, in displacement monitoring using GNSS, displacement is obtained by executing baseline analysis by a known static method based on acquired observation data. Although the static baseline analysis is highly accurate (accuracy of several millimeters), it has a drawback that it takes time (usually 1 hour or more) to measure GNSS radio waves in order to obtain sufficient accuracy. As shown in FIG. 6, in this static method, generally, a measurement station 80 installed at a site receives GNSS radio waves to acquire observation data, and then the observation data is sent to a monitoring center 81 located at a remote location. And the baseline analysis is performed by the analysis personal computer 82 in the monitoring center 81. In this configuration, since observation data must be transferred to the monitoring center 81, the analysis result cannot be confirmed directly on site.

  On the other hand, a known real-time kinematic method may be used for displacement monitoring. In this real-time kinematic method, as shown in FIG. 7, a GNSS radio wave is received at a measurement station 90 installed at the site, and the observation data is wirelessly communicated to a reference station 91 which is also a fixed point installed at the site. Send by. The reference station 91 is configured to perform an analysis process on the received observation data and obtain and output the displacement of the measurement station. According to this configuration, a result can be obtained on the spot only by performing a short-time measurement (several seconds to several tens of minutes). However, the accuracy of the real-time kinematic method is about several centimeters, and the accuracy is inferior compared to the static method.

  As described above, the static method and the real-time kinematic method have a pros and cons. In this regard, Patent Literature 1 and Patent Literature 2 disclose configurations in which observation is performed by combining a static method and a real-time kinematic method.

  In Patent Document 1, static analysis processing is performed because ground fluctuation is small particularly in a state where there is no abnormality, and when the ground displacement value exceeds a specified range that is determined to be a dangerous range, the change can be immediately accommodated. In order to do this, a configuration for selecting a real-time kinematic analysis process is disclosed. According to Patent Document 1, it is possible to continuously monitor from a minute ground change to a rapid ground change, and to make a system capable of early warning and evacuation determination.

  Further, Patent Document 2 changes from a static positioning method to a real-time kinematic positioning method when the slope displacement indicated by slope displacement data observed according to the static positioning method exceeds a preset displacement threshold, and is defined in advance. In addition, a configuration is disclosed in which slope displacement data is obtained at a first time interval and the slope displacement is monitored at a second time interval shorter than the first time interval. According to Patent Document 2, it is possible not only to accurately grasp the state of the slope, but also to cope with an emergency situation such as when the displacement of the slope is large.

JP 2004-45158 A JP 2004-144623 A

  However, Patent Document 1 has a configuration in which a measurement value is transmitted to a remote ground monitoring station, and analysis processing is performed by an analysis processing device in the ground monitoring station. Patent Document 2 is a configuration in which observation data is sent to a monitoring center and slope displacement data is obtained at the monitoring center. Thus, in patent document 1 and patent document 2, there was annoyance that the data acquired in the field had to be transferred to another place (ground monitoring station or monitoring center). For this reason, the advantage of the real-time kinematic method that results can be obtained immediately in the field cannot be utilized.

  Moreover, in the structure of patent document 1 and patent document 2, since a ground monitoring station or a monitoring center is required, there exists a problem that it is expensive. Further, when the analysis is performed at the ground monitoring station or the monitoring center, since the analysis is requested by an expert having expertise, the cost is also increased in this respect.

  Furthermore, the configurations of Patent Document 1 and Patent Document 2 above are alternative configurations of static positioning or kinematic positioning. For example, it is desired to obtain an intermediate analysis result between static positioning and kinematic positioning. However, such analysis results could not be obtained on site.

  Moreover, since the configurations of Patent Literature 1 and Patent Literature 2 are alternative configurations as described above, only one result of static positioning and kinematic positioning can be obtained. Therefore, for example, even if it is desired to compare the analysis results of static positioning and kinematic positioning, since only one of the analysis results is obtained, the above comparison cannot be performed.

  The present invention has been made in view of the above circumstances, and its main purpose is to provide a GNSS analysis system capable of performing on-site baseline analysis utilizing the characteristics of both the kinematic method and the static method. is there.

Means and effects for solving the problems

  The problems to be solved by the present invention are as described above. Next, means for solving the problems and the effects thereof will be described.

According to the first aspect of the present invention, a GNSS analysis system having the following configuration is provided. That is, the GNSS analysis system includes one or more GNSS measurement devices and a GNSS analysis device. The GNSS analysis apparatus includes a GNSS receiver, an other station observation data acquisition unit, a data processing unit, and a time series acquisition unit. The GNSS receiving unit receives radio waves from a GNSS satellite and acquires own station observation data. The other station observation data acquisition unit acquires other station observation data that is observation data output from the GNSS measurement device that has received a radio wave from a GNSS satellite. The data processing unit may obtain a positioning result by processing the pre-Symbol own station observation data and other stations observed data. The time-series acquisition unit acquires the time series before Symbol positioning result. The data processing unit performs kinematic baseline analysis multiple times based on the local station observation data and other station observation data acquired within a predetermined session processing time, and averages the results of the multiple baseline analysis. A session processing unit that executes session processing for obtaining the positioning result. The time series acquisition unit acquires the time series of the positioning results by repeatedly executing the session processing every session processing time. Then, the time-series acquisition unit acquires a plurality of the time series having different said session processing time.

In this way, it is not necessary to transfer the observation data to an external monitoring center or the like by obtaining observation data output by the GNSS measurement device and obtaining a positioning result in the GNSS analysis device. The result can be obtained. In addition, by performing the process for obtaining the average of the results of the baseline analysis by the kinematic method as described above (the session process), it is possible to compensate for the disadvantage of the kinematic method that the accuracy is low. Then, by obtaining a plurality of time series with different session processing times as described above, a positioning result can be obtained with desired accuracy or responsiveness. That is, if the session processing time is set short, the responsiveness is improved instead of the decrease in accuracy. On the other hand, if the session processing time is set longer, the accuracy improves instead of reducing the responsiveness. Thus, since a plurality of time series having different characteristics can be obtained, the time series can be compared with each other, and the positioning result can be appropriately evaluated.

According to the 2nd viewpoint of this invention, the GNSS analyzer of the following structures is provided. That is, the GNSS analysis apparatus includes a GNSS reception unit, an other station observation data acquisition unit, a data processing unit, and a time series acquisition unit. The GNSS receiving unit receives radio waves from a GNSS satellite and acquires own station observation data. The other station observation data acquisition unit acquires other station observation data that is observation data output from a GNSS measurement device that has received a radio wave from a GNSS satellite. The data processing unit may obtain a positioning result by processing the pre-Symbol own station observation data and other stations observed data. The time-series acquisition unit acquires the time series before Symbol positioning result. The data processing unit performs kinematic baseline analysis multiple times based on the local station observation data and other station observation data acquired within a predetermined session processing time, and averages the results of the multiple baseline analysis. A session processing unit that executes session processing for obtaining the positioning result. The time series acquisition unit acquires the time series of the positioning results by repeatedly executing the session processing every session processing time. Then, the time-series acquisition unit acquires a plurality of the time series having different said session processing time.

In this way, it is not necessary to transfer the observation data to an external monitoring center or the like by obtaining observation data output by the GNSS measurement device and obtaining a positioning result in the GNSS analysis device. The result can be obtained. In addition, by performing the process for obtaining the average of the results of the baseline analysis by the kinematic method as described above (the session process), it is possible to compensate for the disadvantage of the kinematic method that the accuracy is low. Then, by obtaining a plurality of time series with different session processing times as described above, a positioning result can be obtained with desired accuracy or responsiveness. That is, if the session processing time is set short, the responsiveness is improved instead of the decrease in accuracy. On the other hand, if the session processing time is set longer, the accuracy improves instead of reducing the responsiveness. Thus, since a plurality of time series having different characteristics can be obtained, the time series can be compared with each other, and the positioning result can be appropriately evaluated.

  The GNSS analyzer is preferably configured as follows. That is, the data processing unit is a static processing unit that performs a static process for obtaining a positioning result by performing a baseline analysis by a static method based on own station observation data and other station observation data acquired within a predetermined static processing time. Is provided. The time series acquisition unit acquires the time series of the positioning results by repeatedly executing the static processing every static processing time. The static processing time is set longer than the session processing time.

  That is, the baseline analysis by the static method has a characteristic that the accuracy is inferior although the accuracy is high. Therefore, by configuring so that session processing is performed at a cycle shorter than the analysis cycle of the static method, it is possible to obtain a result that is more responsive than the static method. Further, when the analysis result by the session process is insufficient in accuracy, the analysis result by the static method can be referred to.

  In the GNSS analysis apparatus, the other station observation data acquisition unit preferably acquires the other station observation data by wireless communication.

  As described above, since the communication between the GNSS analysis device and the GNSS measurement device is wireless communication, it is not necessary to install a communication line and the like, so that the device can be easily installed.

  The GNSS analyzer preferably includes a solar cell as a power supply source.

  Thus, by using a solar cell as the power source, the trouble of wiring the power cord or the like when installing the GNSS analyzer is eliminated, and the installation work is simplified. Further, if the configuration is such that the operation is performed only with the battery, the observable time is limited, but the observation can be continued for a long period of time by employing the solar cell as described above and using a self-supporting power source.

  The GNSS analyzer preferably includes a result output unit that outputs the time series.

  Thereby, the analysis result can be confirmed on the spot.

  In the GNSS analyzer, the result output unit is preferably a display device capable of displaying the time series.

  Thereby, the fluctuation | variation (time series) of a positioning result can be grasped | ascertained visually.

According to the third aspect of the present invention, the following GNSS analysis program is provided. That is, this GNSS analysis program causes a computer to execute processing including a GNSS reception step, an other station observation data acquisition step, a data processing step, and a time series acquisition loop. In the GNSS reception step, radio waves from GNSS satellites are received to acquire own station observation data. In the other station observation data acquisition step, other station observation data that is observation data output from a GNSS measurement station that has received a radio wave from a GNSS satellite is acquired. In the data processing step, obtaining a positioning result by processing the pre-Symbol own station observation data and other stations observed data. In the time series retrieval loop, acquires a time series of pre-Symbol positioning result. In the data processing step, a base line analysis by a kinematic method is performed a plurality of times based on own station observation data and other station observation data acquired within a predetermined session processing time, and the results of the plurality of base line analyzes are averaged. Session processing for obtaining the positioning result. In the time series acquisition loop, the session process is repeatedly executed for each session processing time, thereby acquiring a time series of the positioning results. Then, in the time-series acquisition loop to obtain a plurality of the time series having different said session processing time.

Thus, by obtaining the observation data output from the GNSS measurement station and obtaining the positioning result, it is not necessary to transfer the observation data to an external monitoring center or the like, and the result can be obtained on site. In addition, by performing the process for obtaining the average of the results of the baseline analysis by the kinematic method as described above (the session process), it is possible to compensate for the disadvantage of the kinematic method that the accuracy is low. Then, by obtaining a plurality of time series with different session processing times as described above, an analysis result can be obtained with desired accuracy or responsiveness. That is, if the session processing time is set short, the responsiveness is improved instead of the decrease in accuracy. On the other hand, if the session processing time is set longer, the accuracy improves instead of reducing the responsiveness. As described above, since a plurality of results having different characteristics can be obtained, the positioning result can be appropriately evaluated.

The figure which shows schematic structure of the field analysis type GNSS system which concerns on one Embodiment of this invention. The block diagram which shows the functional structure of a field analysis type GNSS system. The flowchart which shows the flow of a baseline analysis process. The flowchart which shows the flow of a static process. The flowchart which shows the flow of a session process. The figure which shows schematic structure of the conventional GNSS system which employ | adopted static analysis. The figure which shows schematic structure of the conventional GNSS system which employ | adopted real-time kinematic analysis. The graph which shows the displacement given to the measurement station in the case of experiment. The graph which shows the time series of the positioning result by 10 minute session processing. The graph which shows the time series of the coronation result by 20 minutes session processing. The graph which shows the time series of the coronation result by 30 minute session processing. The graph which shows the time series of the coronation result by static processing. The graph which shows the time series of the coronal result by 60 minute session processing.

  Next, embodiments of the present invention will be described with reference to the drawings. FIG. 1 shows a schematic configuration of a field analysis type GNSS system (GNSS analysis system) according to an embodiment of the present invention. The field analysis type GNSS system includes a reference station (GNSS analysis device) 2 and a measurement station (GNSS measurement device) 3.

  The measurement station 3 is configured to receive a radio wave from a GNSS satellite by the GNSS antenna 30 and transmit observation data to the reference station 2. The reference station 2 is configured to obtain the relative position (baseline vector) of the measurement station 3 based on the observation data transmitted from the measurement station 3.

  Although only one measuring station 3 is illustrated in FIG. 1 and the like, a plurality of measuring stations 3 may exist. In that case, the reference station 2 obtains a baseline vector for each of the plurality of measurement stations 3.

  In the field analysis type GNSS system 1, for example, when monitoring ground displacement at a site where there is a risk of landslide, the measurement station 3 is appropriately installed at a place where landslide is likely to occur. The reference station 2 is installed at a fixed point that is not affected by landslides. Then, by monitoring the change of the baseline vector of each measurement station 3 at the reference station 2, the displacement of the ground can be detected.

  As shown in FIG. 1, the reference station 2 has a configuration in which a GNSS antenna 20, a solar cell 21, and a housing 22 are integrally attached to a pole 23, and can be easily carried. It is like that. Similarly, the measurement station 3 has a configuration in which the GNSS antenna 30, the solar cell 31, and the housing 32 are integrally attached to the pole 33, so that the measurement station 3 can be easily carried. Yes. As described above, the reference station 2 and the measurement station 3 are integrated with the pole and are compact, and can be easily installed on the site simply by standing the pole on the ground.

  Next, a detailed configuration of the measurement station 3 will be described with reference to FIG.

  The GNSS antenna 30 provided in the measurement station 3 is configured to receive a GNSS radio wave transmitted from a GNSS satellite. In addition, as GNSS, GPS (Global Positioning System: Global positioning system) can be used, for example.

  In addition, a GNSS receiver 34 and a wireless transmitter 35 are accommodated in the housing 32 provided in the measurement station 3.

  The GNSS receiver 34 is configured to acquire observation data based on the GNSS radio wave received by the GNSS antenna 30. In the field analysis type GNSS system 1 of the present embodiment, an interference positioning method (specifically, static analysis and real-time kinematic analysis) is adopted as a method for obtaining the baseline vector of the measurement station 3. Although this interference positioning method is well known, detailed description thereof is omitted, but it is a method for obtaining a base line vector based on a phase difference between carrier waves of GNSS radio waves received by the measurement station 3 and the reference station 2. Therefore, the observation data includes information regarding the phase of the carrier wave of the GNSS radio wave received by the GNSS antenna 30.

  The wireless transmission unit 35 is configured to wirelessly transmit the observation data acquired by the GNSS reception unit 34 to the reference station 2. As described above, since the observation data is communicated wirelessly, the wiring of the data communication line and the like are not required, so that the measurement station 3 and the reference station 2 can be easily installed.

  In the GNSS analysis system as in the present embodiment, the distance between the measurement station 3 and the reference station 2 is often relatively short (about 200 m to 300 m), depending on the monitoring target. Therefore, in the field analysis GNSS system of the present embodiment, the wireless transmission unit 35 is a wireless LAN that is a simple wireless data transmission path, and the communicable range is relatively short (about 200 m to 300 m). Thus, by using the wireless transmission unit 35 as a relatively short-distance wireless LAN, it is possible to reduce the component cost of the wireless transmission unit 35 and to reduce the power consumption by wireless communication.

  The solar cell 31 provided in the measurement station 3 is configured to supply power to the GNSS receiver 34, the wireless transmitter 35, and the like. In this way, by using the solar cell 31 as the power source of the measuring station 3, it is not necessary to supply power from the outside with a power cord or the like, so there is no need to wire the power cord or the like, and the measuring station 3 can be simply Can be installed. Moreover, since it can generate electric power with the solar cell 31, compared with the case where only a battery is used as a power supply, the measurement for a long time is attained. In particular, in the present embodiment, since the wireless transmission unit 35 is a short-distance wireless LAN, power consumption due to wireless communication is suppressed, so that it is possible to sufficiently cover the power with solar cells.

  Next, the detailed configuration of the reference station 2 will be described with reference to FIG.

  The GNSS antenna 20 provided in the reference station 2 is configured to receive the GNSS radio wave transmitted from the GNSS satellite, similarly to the GNSS antenna 30 provided in the measurement station 3. In addition, a GNSS receiving unit 24, a wireless receiving unit (another station observation data acquiring unit) 25, an analysis processing unit 26, and a result output unit 27 are accommodated in the housing 22 included in the reference station 2. ing.

  The GNSS receiver 24 is configured to acquire observation data based on the GNSS radio wave received by the GNSS antenna 20. The observation data includes information regarding the phase of the carrier wave of the GNSS radio wave received by the GNSS antenna 20.

  The wireless reception unit 25 is configured to receive (acquire) observation data wirelessly transmitted by the wireless transmission unit 35 of each reference station 2. The wireless reception unit 25 is configured as a wireless LAN, similar to the wireless transmission unit 35 of the reference station 2. In the following description, the observation data acquired by the reference station 2 itself by receiving the GNSS radio wave (observation data acquired by the GNSS receiving unit 24) is referred to as own-station observation data and has been wirelessly transmitted from each reference station 2. The observation data (observation data acquired by the wireless reception unit 25) is called other station observation data.

  The analysis processing unit 26 includes hardware such as a CPU, a ROM, and a RAM, and software such as a GNSS analysis program stored in the ROM, and the hardware and the software operate in cooperation. Thus, the base line analysis based on the local station observation data and the other station observation data is performed to obtain the base line vector of each measurement station 3. In the present embodiment, a small and low power consumption type CPU is adopted as the CPU of the analysis processing unit 26.

  In this embodiment, since the observation data in each measurement station 3 is collected in the reference station 2 by wireless communication, the analysis processing unit 26 can obtain the baseline vector of each measurement station 3. Therefore, since it is not necessary to transfer observation data to a remote monitoring center or the like in order to perform baseline analysis, the monitoring center or the like is not necessary.

  The result output unit 27 is configured as a display device such as a liquid crystal display, for example, and is configured to display the displacement of each measurement station 3 according to the result of the baseline analysis by the analysis processing unit 26. As described above, in the field analysis type GNSS system of the present embodiment, the result of the baseline analysis can be confirmed in the field. For example, other devices (extensometers, inclinometers, etc.) for measuring changes in the ground Can be compared on the spot. That is, data collection suitable for the current business can be performed.

  The solar cell 21 provided in the reference station 2 is configured to supply power to the GNSS receiving unit 24, the wireless receiving unit 25, the analysis processing unit 26, the result output unit 27, and the like. Thus, since the power source of the reference station 2 is the solar battery 21, it is not necessary to supply power from the outside by a power cord or the like, so that there is no need to wire the power cord or the like, and the reference station 2 is simply installed. be able to. Moreover, since it can generate electric power with the solar cell 21, compared with the case where only a battery is used as a power supply, the measurement for a long time is attained. In particular, in the present embodiment, by adopting a small and low power consumption type CPU for the analysis processing unit 26, the power consumption in the analysis processing unit 26 is suppressed, so that the solar cell can sufficiently cover the power. It has become.

  Next, the processing contents in the analysis processing unit 26 will be described in detail.

  The analysis processing unit 26 executes the GNSS analysis program on the hardware, thereby performing the baseline analysis processing shown in the flowchart of FIG. 3 and obtaining the baseline vector of each measurement station 3. The GNSS analysis program includes a GNSS reception step, another station observation data acquisition step, a data processing step, and a time series acquisition loop.

  The baseline analysis process executed by the analysis processing unit 26 is mainly performed in a time series acquisition loop including steps S101 to S108 shown in the flow of FIG. By this loop processing, a time series of positioning results (described later) can be acquired. Therefore, it can be said that the analysis processing unit 26 functions as the time-series acquisition unit 40.

  The time series acquisition unit 40 executes the GNSS reception step and the other station observation data acquisition step of the GNSS analysis program at the beginning of the time series acquisition loop process (step S101). In the GNSS reception step, the analysis processing unit 26 acquires the local station observation data acquired by the GNSS reception unit 24. In the other station observation data acquisition step, the analysis processing unit 26 acquires the observation data (other station observation data) of each measurement station 3 received by the wireless reception unit 25. Thereby, new observation data (own station observation data and other station observation data) are sequentially accumulated.

  In this embodiment, in step S101, observation data for 10 minutes (own station observation data and other station observation data) is configured to be accumulated. Until the observation data for 10 minutes is accumulated, the time-series acquisition loop enters a standby state in step S101. When the observation data for 10 minutes is acquired in step S101, the time series acquisition unit 40 executes the processing from step S102 to step S108, and then returns to step S101. That is, in this embodiment, the time series acquisition loop is configured to be executed at a 10-minute cycle.

  Inside the time series acquisition loop, the analysis processing unit 26 performs a data processing step (steps S102, S104, S106, S108) for performing a data process based on the own station observation data and the other station observation data to obtain a positioning result. To do. Therefore, it can be said that the analysis processing unit 26 also has a function as the data processing unit 41.

  The analysis processing unit 26 as the data processing unit 41 processes the observation data (own station observation data and other station observation data) by two processing methods, session processing (described later) and static processing, and obtains the positioning result. It is configured so that it can be obtained. Therefore, it can be said that the analysis processing unit 26 as the data processing unit 41 serves as both the session processing unit 29 and the static processing unit 28.

  Each data processing step (steps S102, S104, S106, and S108) executed by the data processing unit 41 is not necessarily executed in the period of the time series acquisition loop (every 10 minutes). Is executed. Specifically, the session process (10-minute session process) in step S102 is executed at a cycle of 10 minutes. The session process (20-minute session process) in step S104 is executed at a cycle of 20 minutes. The session process (30-minute session process) in step S106 is executed in a cycle of 30 minutes. And the static process of step S108 is comprised so that it may be performed with a 60 minute period. Hereinafter, it demonstrates along the flowchart of FIG.

  When the observation data for 10 minutes is acquired in step S101, the session processing unit 29 executes the session processing step (10-minute session processing) of step S102. Accordingly, the session processing in step S102 is repeatedly executed at the period of the time series acquisition loop (that is, every 10 minutes). Note that the session processing repetition time is referred to as session processing time. Therefore, it can be said that the session processing time of this 10-minute session processing is 10 minutes.

  Subsequently, the time series acquisition unit 40 determines whether or not it is the execution cycle of the 20-minute session process (step S103). Specifically, since the 20-minute session process is executed in a 20-minute cycle, it is determined whether 20 minutes have elapsed since the immediately preceding 20-minute session process. If 20 minutes have elapsed, the session processing unit 29 executes the session processing step (20-minute session processing) in step S104. On the other hand, if it is determined in step S103 that 20 minutes have not elapsed, the process proceeds to S105 without performing the 20-minute session process. With the above process, the 20-minute session process is repeatedly executed every 20 minutes. Therefore, it can be said that the session processing time of this 20-minute session processing is 20 minutes.

  Subsequently, the time-series acquisition unit 40 determines whether or not it is a 30-minute session process execution cycle (step S105). Specifically, since the 30-minute session process is executed in a cycle of 30 minutes, it is determined whether or not 30 minutes have elapsed since the previous 30-minute session process. If 30 minutes have elapsed, the session processing unit 29 executes the session processing step (30-minute session processing) in step S106. On the other hand, if it is determined in step S105 that 30 minutes have not elapsed, the process proceeds to S107 without performing the 30-minute session process. With the above process, the 30-minute session process is repeatedly executed every 30 minutes. Therefore, it can be said that the session processing time of this 30-minute session processing is 30 minutes.

  Subsequently, the time-series acquisition unit 40 determines whether or not it is a static process execution cycle (step S107). Specifically, since the static process is executed in a cycle of 60 minutes, it is determined whether 60 minutes have passed since the last static process. If 60 minutes have elapsed, the static processing unit 28 executes the static processing step of step S108. On the other hand, if it is determined in step S107 that 60 minutes have not elapsed, the process returns to S101 without performing static processing. With the above processing, the static processing is repeatedly executed every 60 minutes. In addition, the repetition time of this static process is called static process time. Therefore, in this embodiment, it can be said that the static processing time is 60 minutes.

  As described above, the baseline analysis process is a loop between step S101 and step S108, and is configured to be automatically and repeatedly executed. Since the baseline analysis process is automated in this way, it is not necessary to request an expert to perform the baseline analysis as in the conventional static analysis, so that the number of personnel can be reduced and the cost can be reduced.

  Next, static processing in the static processing unit 28 will be described with reference to the flowchart of FIG.

  The static processing unit 28 performs baseline analysis (static analysis) by the static method based on the observation data (own station observation data and other station observation data) accumulated during the most recent static processing time, and the positioning result (baseline). (Vector) is obtained (step S201). In this embodiment, since the static processing time is 60 minutes, the static processing unit 28 obtains a positioning result by the static processing based on the observation data accumulated in the latest 60 minutes.

  Subsequently, the static processing unit 28 causes the result output unit 27 to display the positioning result obtained in step S201 (step S202). As described above, when the positioning result by the static analysis is obtained, it is immediately displayed on the result output unit 27, so that the latest analysis result can be confirmed on the spot.

  Finally, the static processing unit 28 records the positioning result by the static analysis in an appropriate storage device (step S323), and ends the static processing.

  As described above, the time series acquisition unit 40 is configured to repeatedly execute the static processing every 60 minutes (static processing time), and therefore acquires the positioning result by the static processing every 60 minutes. Can do. That is, the positioning result by static processing can be acquired in a time series at intervals of 60 minutes.

  Next, session processing in the session processing unit 29 will be described with reference to the flowchart of FIG. As described above, in the present embodiment, the 10-minute session process is repeatedly executed at a 10-minute period, the 20-minute session process at a 20-minute period, and the 30-minute session process at a 30-minute period.

  First, the session processing unit 29 performs baseline analysis (kinematic analysis) by a real-time kinematic method based on the observation data (own station observation data and other station observation data) to obtain the baseline vector of each measurement station 3 ( Step S301).

  As is well known, according to the real-time kinematic method, baseline analysis can be performed in real time at intervals of 1 second or less. That is, if there is observation data for one second, kinematic analysis can be performed. Note that performing baseline analysis using observation data for one second is called a one-second epoch.

  The session processing unit 29 performs the kinematic analysis based on the observation data accumulated during the most recent session processing time. Specifically, in the case of 10-minute session processing, kinematic analysis is performed based on observation data accumulated during the last 10 minutes. In the case of 20-minute session processing, kinematic analysis is performed based on observation data accumulated during the most recent 20 minutes. In the case of 30-minute session processing, kinematic analysis is performed based on observation data accumulated during the last 30 minutes.

  Since kinematic analysis can be executed if there is observation data for one second, if observation data for 10 to 30 minutes is accumulated as described above, kinematic analysis can be performed multiple times. it can. Therefore, the session processing unit 29 is configured to execute kinematic analysis a plurality of times in step S301.

  For example, when a 10-minute session process is executed with a 1-second epoch, kinematic analysis is performed 600 times in step S301. When a 20-minute session process is executed with a 1-second epoch, 1200 kinematic analyzes are performed in step S301. When a 30-minute session process is executed with a 1-second epoch, 1800 kinematic analyzes are performed in step S301.

  In the kinematic analysis according to the present embodiment, the analysis is performed based on the observation data accumulated in advance as described above. Therefore, it can be considered that the kinematic analysis is not the “real-time” kinematic method in the original meaning of words. However, apart from the real-time property, the kinematic analysis of the present embodiment is the same as the conventional real-time kinematic method.

  Subsequently, the session processing unit 29 executes a process of averaging the results of the plurality of times of kinematic analysis (step S302). The session processing unit 29 adopts this averaged value as a positioning result by the session processing. By obtaining the average in this way, the disadvantage of kinematic analysis that accuracy is low can be solved to some extent. In the averaging process, the result of kinematic analysis for a plurality of times may be simply arithmetically averaged. However, the average value is not limited to this, and it is only necessary to obtain an average value by some statistical process. In addition, it is not necessary to average all the results obtained in step S301. For example, the data obtained when the residual is high may be deleted before performing the averaging process.

  Next, the session processing unit 29 causes the result output unit 27 to display the positioning result by the session processing (result of the above average processing) (step S303). In this way, when an analysis result is obtained in each session process, it is immediately displayed on the result output unit 27, so that the latest analysis result can be confirmed on the spot.

  Finally, the session processing unit 29 records the positioning result by the session processing (result of the above average processing) in an appropriate storage device (step S304), and ends the session processing.

  And since the analysis process part 26 is comprised so that the said session process may be repeatedly performed for every session process time (10 minutes, 20 minutes, or 30 minutes), the positioning result by a session process for every said session process time Can be obtained. That is, the positioning result by the 10-minute session process can be acquired in time series at 10-minute intervals. In addition, the positioning result by the 20-minute session process can be acquired in time series at 20-minute intervals. Moreover, the positioning result by a 30-minute session process can be acquired in the time series of a 30-minute space | interval.

  Here, the 10-minute session process has a shorter repetition time than the 20-minute session process, and thus is quicker, but is considered to be inferior in terms of accuracy because the average range is narrow. Similarly, the 20-minute session process has a shorter repetition time than the 30-minute session process, and thus is excellent in quickness, but is considered to be inferior in terms of accuracy since the averaged range is narrow. In addition, the repetition time of each session process (session processing time, 10 minutes, 20 minutes and 30 minutes in this embodiment) is set shorter than the repetition time of static processing (static processing time, 60 minutes in this embodiment). Has been. Accordingly, the static process is considered to have high accuracy although it is inferior in speed to each session process.

  Therefore, the inventors of the present application conducted an experiment to measure the displacement using the field analysis type GNSS system of the present embodiment in order to confirm whether or not the above result is actually obtained. Hereinafter, experimental results will be described with reference to FIGS.

  The experiment was performed while changing the position of the measurement station 3 in order to confirm how much the positioning result follows the displacement of the measurement station 3. Specifically, as shown in the graph of FIG. 8, positioning is performed by moving the measuring station 3 by a predetermined distance in the east-west direction every hour.

  FIG. 9 is a graph showing a time series of positioning results obtained by the 10-minute session process. As shown in the graph of FIG. 9, the positioning result by the 10-minute session process has many plots per unit time (high speed), but there are many plots that are out of the accurate values (low accuracy). Recognize.

  On the other hand, in FIG. 12, a time series of positioning results by static processing is shown in a graph. As shown in FIG. 12, it can be seen that the positioning result by the static process can obtain an almost accurate positioning result although the number of plots per unit time is small (the speed is low).

  Further, as shown in FIGS. 10 and 11, it can be seen that the 20-minute session process and the 30-minute session process are intermediate results between the 10-minute session process and the static process. As described above, it was confirmed that a plurality of results with different accuracy and quickness can be obtained by acquiring time series of positioning results with different repetition times.

  Therefore, for example, in order to detect a fine ground displacement in the initial stage of landslide, it is only necessary to monitor high-precision positioning results such as static processing and 30-minute session processing, and in order to detect rapid ground displacement, What is necessary is just to monitor the positioning result by 10 minute session processing and 20 minute session processing which are excellent in quickness. As described above, the positioning results can be flexibly used according to the purpose, so that the features of both the kinematic analysis and the static analysis can be utilized.

  In addition, in the field analysis type GNSS system of this embodiment, a method called session processing is introduced into kinematic analysis, and by performing multiple session processing with different repetition times, kinematic analysis and static analysis are performed. An analysis result of an intermediate character can be obtained. For example, in the case where the accuracy is insufficient in the 10-minute session process, but the accuracy as high as the static analysis is not necessary, the result of the 20-minute session process or the 30-minute session process may be referred to. In this way, by introducing session processing to kinematic analysis, the clear difference between the results of kinematic analysis and static analysis has faded, and it is possible to handle kinematic analysis and static analysis in a unified manner to some extent. It has become.

  In addition, since positioning results with different speediness and accuracy can be displayed on the result output unit 27, comparison with detection results of other devices (extensometers, inclinometers, etc.) should be appropriately performed at the site. Can do.

  Moreover, in the field analysis type GNSS system of this embodiment, the graph which shows the time series (history) of a positioning result about each of 10-minute session processing, 20-minute session processing, 30-minute session processing, and static processing is shown in the result output part 27. It can be displayed on the screen. Specifically, a time series graph as shown in FIGS. 9 to 12 is displayed on the result output unit 27.

  That is, in order to determine the presence / absence of displacement, time-series information on how the positioning result changes with the passage of time is required. For example, only the latest positioning result is output to the result output unit 27. However, it is not possible to determine whether or not there is a landslide. In this regard, by displaying the time series of the positioning results as a graph as described above, it is possible to visually grasp the presence or absence of displacement (for example, the presence or absence of landslide).

  Furthermore, in the field analysis type GNSS system of the present embodiment, as described in the flow of FIG. 3, the 10-minute session process, the 20-minute session process, the 30-minute session process, and the static process are executed in one loop. doing. With this configuration, the time series of positioning results by 10-minute session processing, the time series of positioning results by 20-minute session processing, the time series of positioning results by 30-minute session processing, and the time series of positioning results by static processing are simultaneously parallel. Is acquired. This is different from the configurations of Patent Document 1 and Patent Document 2 in which only one of the static analysis and the kinematic analysis is acquired.

  And by configuring as described above, it is possible to acquire time series with different repetition times on-site, so that the time series can be compared with each other. For example, by comparing the time series graphs of FIGS. 9 to 11 displayed on the result output unit 27, the movements of each time series can be compared with each other. Accordingly, it is possible to comprehensively determine whether or not there is a displacement while considering the trade-off between the accuracy and speed of each time series.

  Next, a modification of the above embodiment will be described.

  In the above embodiment, static processing is executed every 60 minutes in addition to session processing for 10, 20, and 30 minutes. However, the static processing every 60 minutes may be omitted, and 60-minute session processing (session processing repeatedly executed every 60-minute session processing time) may be performed instead.

  That is, whether static processing is performed every 60 minutes or 60 minutes session processing is the same in that baseline analysis is performed based on observation data for 60 minutes. Then, if an appropriate process is performed in the averaging process in the session process, it is considered that an analysis result having no great difference can be obtained between the 60-minute session process and the 60-minute static process. Therefore, it can be said that there is no essential difference between the 60-minute session process and the 60-minute static process. As described above, the difference in the analysis method whether the static method or the kinematic method is adopted for the baseline analysis is not an essential problem in the present invention.

  The time series of the positioning results by the 60-minute session process is shown in the graph of FIG. As can be seen by comparing the graphs of FIG. 13 and FIG. 12, positioning results comparable to the static processing can be obtained even in the 60-minute session processing.

  As described above, the reference station 2 of the present embodiment includes the GNSS receiving unit 24, the wireless receiving unit 25, the data processing unit 41, and the time series acquisition unit 40. The GNSS receiver 24 receives radio waves from GNSS satellites and acquires own station observation data. The wireless reception unit 25 acquires other station observation data that is observation data output from the measurement station 3 that has received the radio wave from the GNSS satellite. The data processing unit 41 processes the own station observation data and the other station observation data acquired within a predetermined repetition time and obtains positioning results (steps S102, S104, S106, S108). The time series acquisition unit 40 repeatedly executes the data processing step for each repetition period, and acquires the time series of the positioning results. The time series acquisition unit 40 acquires a plurality of time series with different repetition times (10 minutes, 20 minutes, 30 minutes, and 60 minutes).

  The field analysis type GNSS system of the present embodiment includes a reference station 2 and one or more measurement stations 3.

  In addition, the GNSS analysis program of the present embodiment causes the reference station 2 to execute processing including a GNSS reception step, another station observation data acquisition step, a data processing step, and a time series acquisition loop. In the GNSS reception step, radio waves from GNSS satellites are received to acquire own station observation data. In the other station observation data acquisition step, other station observation data that is observation data output from a measurement station that has received a radio wave from a GNSS satellite is acquired. In the data processing step, the local station observation data and the other station observation data acquired within a predetermined repetition time are processed to obtain a positioning result. In the time series acquisition loop, the data processing step is repeatedly executed at each repetition time to acquire the time series of the positioning results. In the time series acquisition loop, a plurality of the time series having different repetition times are acquired.

  In this way, the observation data output by the measurement station 3 is acquired by the reference station 2, and the measurement result is obtained in the reference station 2 without the need to transfer the observation data to an external monitoring center or the like. Can be obtained. Then, by obtaining a plurality of time series having different repetition times as described above, a positioning result can be obtained with desired accuracy or responsiveness. That is, if the repetition time is set short, the responsiveness is improved instead of the decrease in accuracy. On the other hand, if the repetition time is set longer, the accuracy improves instead of reducing the responsiveness. Thus, since a plurality of time series having different characteristics can be obtained, the time series can be compared with each other, and the positioning result can be appropriately evaluated.

  Further, the reference station 2 of the present embodiment is configured as follows. That is, the data processing unit 41 performs a baseline analysis by the kinematic method based on the own station observation data and the other station observation data acquired within a predetermined session processing time a plurality of times, and the results of the plurality of baseline analyzes are obtained. A session processing unit 29 is provided that executes session processing that averages and obtains the positioning result. The time series acquisition unit 40 acquires the time series of the positioning results by repeatedly executing the session processing every session processing time.

  That is, the kinematic method of baseline analysis is superior in quick response, but has a characteristic that the accuracy is lower than that of the static method of baseline analysis. Therefore, by performing a process for obtaining the average of the results of the baseline analysis by the kinematic method (the session process described above), it is possible to compensate for the disadvantage of the kinematic method that the accuracy is low.

  Further, the reference station 2 of the present embodiment is configured as follows. That is, the data processing unit 41 performs a static process for obtaining a positioning result by performing a baseline analysis by a static method based on the local station observation data and the other station observation data acquired within a predetermined static processing time. 28. The time series acquisition unit 40 acquires the time series of the positioning results by repeatedly executing static processing every static processing time. The static processing time is set longer than the session processing time.

  That is, the baseline analysis by the static method has a characteristic that the accuracy is inferior although the accuracy is high. Therefore, by configuring so that session processing is performed at a cycle shorter than the analysis cycle of the static method, it is possible to obtain a result that is more responsive than the static method. Further, when the analysis result by the session process is insufficient in accuracy, the analysis result by the static method can be referred to.

  Further, in the reference station 2 of the present embodiment, the wireless reception unit 25 acquires other station observation data through wireless communication.

  As described above, since communication between the reference station 2 and the measurement station 3 is wireless communication, installation of a communication line or the like becomes unnecessary, so that installation of the apparatus is facilitated.

  In addition, the reference station 2 of the present embodiment includes a solar cell 21 as a power supply source.

  Thus, by using the solar cell 21 as the power source, the trouble of wiring the power cord or the like when installing the reference station 2 is eliminated, and the installation work is simplified. Further, if the configuration is such that the operation is performed only with the battery, the observable time is limited, but the observation can be continued for a long period of time by adopting the solar cell 21 as described above and using a self-supporting power source. .

  Further, the reference station 2 of this embodiment includes a result output unit 27 that outputs the time series.

  Thereby, the analysis result can be confirmed on the spot.

  In addition, the result output unit 27 of the present embodiment is a display device that can display a time series.

  Thereby, the fluctuation | variation (time series) of a positioning result can be grasped | ascertained visually.

  The preferred embodiment of the present invention has been described above, but the above configuration can be modified as follows, for example.

  Although the analysis processing unit 26 has been described as being configured by hardware and software, all or part of the functions may be realized by dedicated hardware.

  In the above embodiment, the wireless LAN is adopted as the wireless communication method, but any appropriate wireless communication method other than the wireless LAN can be used. However, a configuration in which the reference station 2 and the measurement station 3 communicate with each other by wire instead of wirelessly may be used.

  Moreover, in the said embodiment, although the power supply of the reference | standard station 2 and the measurement station 3 was said to be a solar cell, it is needless to say that a rechargeable battery may be used supplementarily. Of course, if long-term observation is not performed, the solar cell may be omitted and power may be supplied only by the battery.

  In the said embodiment, although the repetition time (1st time) of the static process was 60 minutes, it is not limited to this. In the above embodiment, the session processing repetition time (second time) is 10 minutes, 20 minutes, and 30 minutes, but is not limited thereto. Further, the number of types of session processing has been described as the above three types, but is not limited thereto, and may be one or more types.

  The result output unit 27 has been described as a liquid crystal display. However, the present invention is not limited to this.

  In the above embodiment, the baseline analysis process is performed in the reference station 2 which is a fixed point. However, instead of this configuration, the baseline analysis may be performed in each of one or more measurement stations 3. In this case, it can be understood that the reference station is a GNSS measurement device and each measurement station is a GNSS analysis device. Even in this case, the effect of the present invention can be exhibited that a baseline analysis can be performed on-site utilizing the characteristics of both the kinematic method and the static method. However, if it is configured to collect the observation data from the measurement station 3 in the reference station 2 and execute the baseline analysis as in the above embodiment, the displacement of the plurality of measurement stations 3 can be collectively confirmed by the reference station 2. Therefore, it is particularly suitable.

  The configuration of the present invention is not limited to monitoring ground displacement, but can be used for various surveys.

1 Local analysis type GNSS system (GNSS analysis system)
2 Reference station (GNSS analyzer)
3 measuring stations (GNSS measuring equipment)
21 solar cell 24 GNSS receiver 25 wireless receiver (other station observation data acquisition unit)
28 Static processing section 29 Session processing section

Claims (8)

One or more GNSS measuring devices;
A GNSS analyzer,
A GNSS analysis system comprising:
The GNSS analyzer is
A GNSS receiver that receives radio waves from a GNSS satellite and obtains local station observation data;
An other station observation data acquisition unit that acquires other station observation data that is observation data output from the GNSS measurement device that has received radio waves from a GNSS satellite;
A data processing unit for obtaining a positioning result before Symbol own observation data and processing other stations observed data,
And the time-series acquisition unit for acquiring a time series of previous Symbol positioning results,
With
The data processing unit performs kinematic baseline analysis multiple times based on the local station observation data and other station observation data acquired within a predetermined session processing time, and averages the results of the multiple baseline analysis. A session processing unit that executes session processing for obtaining the positioning result.
The time series acquisition unit acquires the time series of the positioning results by repeatedly executing the session processing every session processing time,
The time series acquisition unit acquires a plurality of the time series with different session processing times . A GNSS receiver that receives radio waves from a GNSS satellite and obtains local station observation data;
An other station observation data acquisition unit that acquires other station observation data that is observation data output from a GNSS measurement device that has received radio waves from a GNSS satellite;
A data processing unit for obtaining a positioning result before Symbol own observation data and processing other stations observed data,
And the time-series acquisition unit for acquiring a time series of previous Symbol positioning results,
With
The data processing unit performs kinematic baseline analysis multiple times based on the local station observation data and other station observation data acquired within a predetermined session processing time, and averages the results of the multiple baseline analysis. A session processing unit that executes session processing for obtaining the positioning result.
The time series acquisition unit acquires the time series of the positioning results by repeatedly executing the session processing every session processing time,
The time series acquisition unit acquires a plurality of the time series with different session processing times . The GNSS analyzer according to claim 2 ,
The data processing unit includes a static processing unit that performs static processing to obtain a positioning result by performing a baseline analysis by a static method based on local station observation data and other station observation data acquired within a predetermined static processing time. ,
The time series acquisition unit acquires the time series of the positioning results by repeatedly executing the static processing every static processing time,
The GNSS analysis apparatus, wherein the static processing time is set longer than the session processing time. The GNSS analyzer according to claim 2 or 3 ,
The GNSS analysis apparatus, wherein the other station observation data acquisition unit acquires the other station observation data by wireless communication. A GNSS analyzer according to any one of claims 2 to 4 ,
A GNSS analysis device comprising a solar cell as a power supply source. A GNSS analysis apparatus according to any one of claims 2 to 5 ,
A GNSS analyzer comprising a result output unit for outputting the time series. The GNSS analyzer according to claim 6 ,
The result output unit is a display device capable of displaying the time series. A GNSS reception step of receiving radio waves from a GNSS satellite and acquiring local station observation data;
Other station observation data acquisition step of acquiring other station observation data that is observation data output from a GNSS measurement device that has received radio waves from a GNSS satellite;
A data processing step of obtaining the positioning result before Symbol own observation data and processing other stations observed data,
And the time series retrieval loop to get the time sequence before Symbol positioning results,
Causes the computer to execute processing including
In the data processing step, the base line analysis by the kinematic method is performed a plurality of times based on the own station observation data and the other station observation data acquired within a predetermined session processing time, and the results of the plurality of base line analyzes are averaged. Session processing to obtain the positioning results
In the time series acquisition loop, the session processing is repeatedly executed for each session processing time, thereby acquiring the time series of the positioning results,
In the time series acquisition loop, a plurality of the time series having different session processing times are acquired.

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