JP5586278B2 - POSITIONING DATA EVALUATION DEVICE, POSITIONING DATA EVALUATION METHOD, AND POSITIONING DATA EVALUATION PROGRAM - Google Patents

Description

  The present invention relates to a positioning data evaluation apparatus, a positioning data evaluation method, and a positioning data evaluation program for detecting positioning data having a large measurement error from positioning data (positioning result) obtained by a positioning satellite system such as GPS (Global Positioning System). Is. The following description is for GPS, but it can be easily applied to other positioning satellite systems.

Conventionally, when GPS data (observation information) is analyzed in time series to obtain positioning data (positioning results), if it is determined that the measurement error may be large, the operation of the estimator is corrected at that time The analysis was continued without rejecting the solution. This is because, in the time series analysis, there are not enough determination indexes for detecting a solution with a large measurement error, and there is a possibility that a correct solution is rejected.
However, with this method, a solution with a large measurement error may remain in the measurement result.

In order to reject a solution with a large measurement error, there is a method of judging the wrong solution by comparing the altitudes of neighboring solutions with similar coordinates after analysis, and rejecting it, but this is also insufficient because it lacks certainty. Not a way.
For example, when an incorrect solution is determined based on a difference in altitude between neighboring solutions measured in adjacent lanes, it is often difficult to set a threshold for altitude difference.
Even in a section where a mistake FIX (an error in ambiguity estimation of the carrier phase observation amount) has occurred in the analysis of the GPS data, the altitude difference between the neighboring solutions is about 20 to 30 cm. Moreover, since this altitude difference includes an actual altitude difference that is not a measurement error, it is difficult to determine and reject an incorrect solution based on the altitude difference alone.

JP 2009-53059 A JP 2008-39691 A

  An object of the present invention is to make it possible to detect, for example, positioning data having a large measurement error from positioning data (positioning result) obtained by GPS.

The positioning data evaluation apparatus of the present invention is
The coordinate value and observation time solution measured using the carrier phase observation amount of the signal transmitted from each of the multiple positioning satellites, and the number of positioning satellites corresponding to the carrier phase observation amount used to measure the coordinate value A positioning data storage unit that stores a plurality of data including the number of used satellites shown as positioning data;
From a plurality of positioning data stored in the positioning data storage unit, a continuous data specifying unit for specifying a plurality of sets of positioning data whose observation time is continuous and the number of used satellites is a predetermined number as continuous data;
For each continuous data specified by the continuous data specifying unit, the immediately preceding data specifying that specifies the positioning data including the observation time immediately before the first observation time included in the continuous data as the immediately preceding data from the plurality of positioning data. And
Among the plurality of continuous data specified by the continuous data specifying unit, continuous data in which the number of used satellites of the immediately preceding data specified by the immediately preceding data specifying unit is less than a predetermined number is set as low-precision data with low coordinate value accuracy. And a low-accuracy data specifying unit for specifying.

  According to the present invention, for example, positioning data (low accuracy data) having a large measurement error can be detected from positioning data obtained by GPS.

FIG. 3 is a functional configuration diagram of the positioning device 100 according to the first embodiment. FIG. 3 is a diagram illustrating an example of hardware resources of the positioning device 100 according to the first embodiment. 4 is a flowchart showing a positioning data evaluation method of positioning device 100 according to the first embodiment. FIG. 2 is a configuration diagram of a measurement vehicle 200 in the first embodiment. 6 is a graph of a GPS positioning data group (the number of FIX satellites) in the first embodiment. FIG. 5 shows a display example of rejection candidates in the first embodiment. FIG. 6 is a functional configuration diagram of a positioning device 100 according to a second embodiment. 9 is a flowchart showing a positioning data evaluation method of positioning device 100 in the second embodiment. FIG. 10 shows a display example of rejection candidates in the second embodiment. FIG. 10 is a functional configuration diagram of a positioning device 100 according to a third embodiment. 10 is a flowchart showing a positioning data evaluation method of positioning device 100 in the third embodiment.

Embodiment 1 FIG.
A description will be given of a mode in which positioning data (rejection candidates described later) having a large measurement error is detected from positioning data obtained by GPS based on the number of used satellites (number of FIX satellites described later).

FIG. 1 is a functional configuration diagram of the positioning device 100 according to the first embodiment.
The positioning apparatus 100 in Embodiment 1 is demonstrated below based on FIG.

  The positioning device 100 (an example of a positioning data evaluation device) includes a continuous solution grouping unit 110, a rejection candidate specifying unit 120, a rejection candidate presenting unit 130, a rejection candidate rejection unit 140, a rejection continuous solution complementing unit 150, and a positioning data storage unit 190. Prepare.

The positioning data storage unit 190 (an example of a positioning data storage unit) stores a plurality of positioning data (GPS positioning data described later).
Positioning data includes coordinate values and observation times measured using carrier phase observation amounts of signals transmitted from each of a plurality of GPS satellites, and GPS satellites corresponding to carrier phase observation amounts used to measure the coordinate values. Data including the number of used satellites (the number of FIX satellites described later) indicating the number of satellites.

The continuous solution grouping unit 110 (an example of a continuous data specifying unit) specifies a plurality of pieces of continuous data (continuous solutions to be described later) from a plurality of positioning data stored in the positioning data storage unit 190.
Continuous data is a set of positioning data in which observation times are continuous and the number of used satellites remains constant at a predetermined number. Here, the continuous observation time means that the carrier phase observation amount is continuously measured. Therefore, the carrier phase observation amount used for the coordinate value measurement has the same ambiguity in the continuous data.

  Rejection candidate specifying unit 120 includes a front / rear solution extraction unit 121 and a rejection candidate extraction unit 122.

The preceding and following solution extraction unit 121 (an example of the immediately preceding data specifying unit and the immediately following data specifying unit) is, for each continuous data specified by the continuous solution grouping unit 110, an observation time immediately before the first observation time included in the continuous data. Is determined from a plurality of positioning data as immediately preceding data (immediately-described solution to be described later).
For each continuous data specified by the continuous solution grouping unit 110, the pre- and post-solution extraction unit 121 obtains positioning data including an observation time immediately after the last observation time included in the continuous data as immediate data (immediate solution described later). ) To identify from multiple positioning data.

Rejection candidate extraction unit 122 (an example of a low-accuracy data specifying unit) specifies low-precision data (rejection candidates to be described later) with low coordinate value accuracy from a plurality of continuous data specified by continuous solution grouping unit 110.
For example, the low-accuracy data is continuous data in which the number of used satellites of the immediately preceding data specified by the pre- and post-solution extraction unit 121 is less than a predetermined number.
The low-accuracy data is continuous data in which the number of used satellites of the immediately preceding data specified by the preceding and following solution extracting unit 121 and the number of used satellites of the immediately following data specified by the preceding and following solution extracting unit 121 are less than a predetermined number. is there.

  Rejection candidate presentation unit 130 (an example of a low-accuracy data display unit) displays low-accuracy data specified by rejection candidate extraction unit 122 on the display device.

Rejection candidate rejection unit 140 (an example of a low accuracy data deletion unit) deletes low accuracy data.
For example, the rejection candidate rejection unit 140 deletes the low-precision data designated by the user using the input device from the positioning data storage unit 190.

Rejection continuous solution complementing unit 150 (an example of a positioning data complementing unit) supplements the positioning data of the time corresponding to the low-accuracy data deleted by rejection candidate rejection unit 140.
For example, the rejection continuous solution complementing unit 150 complements positioning data using coordinate values measured by inertial navigation.

FIG. 2 is a diagram illustrating an example of hardware resources of the positioning device 100 according to the first embodiment.
2, the positioning device 100 includes a CPU 911 (Central Processing Unit) (also referred to as a microprocessor or a microcomputer). The CPU 911 is connected to the ROM 913, the RAM 914, the communication board 915, the display device 901, the keyboard 902, the mouse 903, the drive device 904, and the magnetic disk device 920 via the bus 912, and controls these hardware devices. The drive device 904 is a device that reads and writes a storage medium such as an FD (Flexible Disk Drive), a CD (Compact Disc), and a DVD (Digital Versatile Disc).

  The communication board 915 is wired or wirelessly connected to a communication network such as a LAN (Local Area Network), the Internet, or a telephone line.

  The magnetic disk device 920 stores an OS 921 (operating system), a window system 922, a program group 923, and a file group 924.

  The program group 923 includes programs that execute the functions described as “units” in the embodiment. The program is read and executed by the CPU 911. That is, the program causes the computer to function as “to part”, and causes the computer to execute the procedures and methods of “to part”.

  The file group 924 includes various data (input, output, determination result, calculation result, processing result, etc.) used in “˜part” described in the embodiment.

  In the embodiment, arrows included in the configuration diagrams and flowcharts mainly indicate input and output of data and signals.

  In the embodiment, what is described as “to part” may be “to circuit”, “to apparatus”, and “to device”, and “to step”, “to procedure”, and “to processing”. May be. That is, what is described as “to part” may be implemented by any of firmware, software, hardware, or a combination thereof.

FIG. 3 is a flowchart showing a positioning data evaluation method of positioning device 100 in the first embodiment.
A positioning data evaluation method of positioning device 100 in the first embodiment will be described below with reference to FIG.

  First, an outline of the positioning data evaluation method will be described.

The continuous solution grouping unit 110 groups the GPS positioning data at each time for each continuous solution (S110). A continuous solution is a set of positioning data in which observation times are continuous and the number of used satellites is a predetermined number.
The back-and-forth solution extraction unit 121 extracts the back-and-forth solution of the continuous solution from the GPS positioning data at each time (S120).
Rejection candidate extraction unit 122 identifies a continuous solution of rejection candidates based on the number of FIX satellites of the front and rear solutions (S130).
Rejection candidate presentation unit 130 presents a continuous solution of rejection candidates to the user (S140).
Rejection candidate rejection unit 140 rejects the rejection continuous solution designated by the user (S150).
The rejection continuous solution complementing unit 150 supplements the positioning data of the time corresponding to the rejection continuous solution (S160).

  Before describing the details of the positioning data evaluation method, the GPS positioning data stored in the positioning data storage unit 190 will be described.

FIG. 4 is a configuration diagram of the measurement vehicle 200 in the first embodiment.
For example, the GPS positioning data is acquired by a measurement vehicle 200 as shown in FIG.

The measurement vehicle 200 is provided with a top plate 201, and the top plate 201 is provided with three GPS receivers 210 a to 210 c and an inertia device 220.
The measurement vehicle 200 includes a vehicle speed detection device 230 and a self-positioning device 290.

The GPS receivers 210a to 210c receive the carrier wave (positioning signal) transmitted from the GPS satellite, and from the reception result, the pseudo distance to the GPS satellite, the carrier wave phase, the coordinate value of the GPS receiver 210a to 210c, the navigation message, etc. Obtain observation information.
Two of them are installed for the purpose of measuring the attitude of the measuring vehicle 200.
When each of the two vectors between adjacent receivers including the remaining one is measured, the relative position between the GPS receivers is constant, so the length of this vector is a constant value, and it is relatively easy to determine the estimation error. is there.

An inertial device 220 (IMU: Internal Measurement Unit) includes a gyro sensor and an acceleration sensor.
The gyro sensor measures the angular velocity in the triaxial direction xyz of the measuring vehicle 200, and the acceleration sensor measures the acceleration of the measuring vehicle 200 in the triaxial direction xyz.

  The vehicle speed detection device 230 (ODO: ODOmetry) measures the speed of the measurement vehicle 200.

The self-localization device 290 performs GPS positioning by measuring the relative position with a reference point receiver whose coordinate value is known based on the observation information acquired by the GPS receiver 210c using the carrier phase observation amount, and at each time The coordinate value of the measurement vehicle 200 is calculated.
At this time, the GPS receiver 210c needs to measure the carrier phase observation amount from a predetermined number or more (for example, four or five or more) GPS satellites. Further, the ambiguity needs to be estimated for the carrier phase observation amount. The ambiguity of the carrier phase observation amount means an integer part of the number of carrier wavelengths included in the distance from the GPS satellite to the GPS receiver.
Hereinafter, a GPS satellite corresponding to a carrier phase observation amount whose ambiguity is estimated is referred to as a “FIX satellite”.

  The self-localization device 290 calculates the coordinate value of the measurement vehicle 200 by performing strapdown calculation (inertial navigation) on the angular velocity / acceleration measured by the inertia device 220 when there are no more than a predetermined number of FIX satellites.

The self-localization device 290 may calculate the coordinate value in real time simultaneously with the traveling of the measuring vehicle 200 or may calculate the coordinate value as post-processing after the traveling of the measuring vehicle 200 ends.
The self location device 290 may not be a device provided in the measurement vehicle 200.

Hereinafter, it is assumed that data obtained by traveling the measurement vehicle 200 is stored in the positioning data storage unit 190 of the positioning device 100 (see FIG. 1).
For example, the positioning data storage unit 190 stores coordinate values calculated by GPS positioning (hereinafter referred to as GPS positioning data) and coordinate values calculated by inertial navigation (hereinafter referred to as IMU positioning data) in association with time. Has been.
The positioning data storage unit 190 includes observation information (hereinafter referred to as GPS observation data) acquired by the GPS receivers 210a to 210c, angular velocity / acceleration (hereinafter referred to as IMU data) measured by the inertial device 220, and a vehicle speed detection device. The vehicle speed measured by 230 is stored in association with the time.

  Details of the positioning data evaluation method (S110 to S160) will be described below.

  In S110, the continuous solution grouping unit 110 groups the GPS positioning data group based on the observation time and the number of FIX satellites.

First, the continuous solution grouping unit 110 sorts GPS positioning data groups by observation time and arranges them in time series.
Next, the continuous solution grouping unit 110 sets a plurality of continuous GPS positioning data in a time zone in which the number of FIX satellites is a predetermined number as one group.
That is, a plurality of GPS positioning data in which the observation times are continuous and the number of FIX satellites is a predetermined number form one group.
For example, the predetermined number is the minimum number of FIX satellites necessary for positioning based on GPS observation data (the minimum number of satellites described later).

  Hereinafter, each group is referred to as “continuous solution”.

  After S110, the process proceeds to S120.

In S120, the front and rear solution extraction unit 121 performs GPS positioning data indicating the observation time immediately before the continuous solution (hereinafter referred to as a previous solution) and GPS positioning data indicating the observation time immediately after the continuous solution (hereinafter, immediately after). Is extracted from the GPS positioning data group sorted in S110.
The front and rear solution extraction unit 121 extracts the immediately preceding solution and the immediately following solution for each continuous solution.
After S120, the process proceeds to S130.

In S130, the rejection candidate extraction unit 122 determines whether both the number of FIX satellites of the immediately preceding solution and the number of FIX satellites of the immediately following solution (hereinafter referred to as the number of preceding and following solution satellites) are equal to or greater than a predetermined minimum number of satellites. Judge every time.
The minimum number of satellites is the minimum number of FIX satellites required for positioning based on GPS observation data (pseudorange, carrier phase, etc.). The minimum number of satellites is, for example, 4 or 5, and differs depending on the positioning processing method of the system.

  The rejection candidate extraction unit 122 identifies a continuous solution in which the number of front and rear solution satellites is less than the minimum number of satellites as a rejection candidate continuous solution (a continuous solution that is highly likely to have low coordinate value accuracy).

However, the rejection candidate extraction unit 122 may specify the continuous solution of rejection candidates by comparing only the number of FIX satellites of the immediately preceding solution with the minimum number of satellites.
Further, the rejection candidate extraction unit 122 may identify a continuous solution of rejection candidates by comparing only the number of FIX satellites immediately after the solution with the minimum number of satellites.

FIG. 5 is a graph showing the number of FIX satellites in the GPS positioning data group in the first embodiment.
In FIG. 5, the horizontal axis indicates the elapsed time (seconds) from the start of GPS observation by the measurement vehicle 200 (see FIG. 4), and the vertical axis indicates the number of FIX satellites “×” or the number of common satellites “◯”.
The number of common satellites is the number of GPS satellites (common satellites) corresponding to the carrier phase observation amount that can be received by both the GPS receiver 210c of the measurement vehicle 200 and the reference point receiver that is the target of relative position measurement. is there.
The number of FIX satellites is the number of common satellites corresponding to the carrier phase observation amount for which ambiguity can be estimated. However, when the number of FIX satellites is less than the minimum number of satellites, the number of FIX satellites is set to “0”.

B in the figure is a continuous solution because time is continuous and the number of FIX satellites is the same as 5, which is the minimum number of satellites here (S110).
Both the immediately preceding solution X and the immediately following solution Y of the continuous solution B have the number of FIX satellites “0” (the number of FIX satellites <the minimum number of satellites) (S120).
For this reason, the continuous solution B is a continuous solution of rejection candidates (S130).

  Returning to FIG. 3, the description of the positioning data evaluation method will be continued.

  After S130, the process proceeds to S140.

In S140, rejection candidate presenting section 130 presents the user with the continuous solution of the rejection candidates specified in S130.
For example, the rejection candidate presenting unit 130 displays the observation time, the number of FIX satellites, and the coordinate values of the consecutive solutions of the rejection candidates on the display device by a method of arranging them in time series or a method shown as a horizontal diagram. The rejection candidate presenting unit 130 may present a continuous solution of rejection candidates to the user by printing or file output.

FIG. 6 is a horizontal diagram showing a display example of rejection candidates in the first embodiment.
In FIG. 6, “◯” is a plot of coordinate values (latitude and longitude) of GPS positioning data other than rejection candidates, and “×” is a plot of coordinate values (latitude and longitude) of GPS positioning data of rejection candidates. It is a thing.
A line represented by “◯” and “x” represents a route traveled by the measurement vehicle 200 (see FIG. 4).

As shown in FIG. 6, rejection candidate presenting section 130 may plot the coordinate values of the respective GPS positioning data by changing the notation (shape, color, blinking, etc.) between the rejection candidate and other than the rejection candidate (FIG. 3). S140).
Further, rejection candidate presenting section 130 may display the coordinate values (latitude, longitude, altitude) of the designated plot when the plot is designated with a mouse cursor or the like.

  Returning to FIG. 3, the description of the positioning data evaluation method will be continued.

  After S140, the process proceeds to S150.

In S150, the user refers to the continuous solution of the rejection candidates presented in S140, determines the continuous solution to be rejected, and designates the continuous solution to be rejected from the input device (keyboard, mouse, etc.) to the positioning device 100.
Hereinafter, the designated continuous solution is referred to as “rejected continuous solution”.

Rejection candidate rejection unit 140 receives the specification of the rejection continuous solution, and rejects the specified rejection continuous solution (data deletion, invalid flag setting, etc.).
After S150, the process proceeds to S160.

In S160, the rejection continuous solution complementing unit 150 supplements the positioning data in the observation time zone of the rejection continuous solution to the GPS positioning data in order to supplement the rejection continuous solution.
Further, the rejection continuous solution complementing unit 150 obtains GPS positioning data (for example, a solution before and after a rejection candidate) (hereinafter referred to as a non-positioning solution) at an observation time when GPS positioning could not be performed because the number of FIX satellites is less than the minimum number of satellites. Supplement the positioning data to supplement.

For example, the rejection continuous solution complementing unit 150 extracts inertial positioning data in the same time zone as the rejection continuous solution and a time zone in which there is no solution from the inertial positioning data group stored in the positioning data storage unit 190, and the extracted inertial positioning data To complement.
In addition, for example, the user re-runs the observation area in the same time zone (and the time zone without the solution) as the rejection continuous solution with the measurement vehicle 200 (see FIG. 4), and reacquires GPS observation data. The self-positioning device 290 of the measurement vehicle 200 newly generates GPS positioning data based on the reacquired GPS observation data. Rejection continuous solution complementing section 150 supplements newly generated GPS positioning data.
After S160, the positioning data evaluation method ends.

In S150 described above, the rejection candidate rejection unit 140 rejects all (or a part) of the rejection candidate continuous solutions determined by the rejection candidate extraction unit 122 instead of the rejection candidate continuous solutions designated by the user. You can dismiss it as
In this case, the positioning device 100 may not include the rejection candidate presentation unit 130.

  In S130, the reason why the consecutive candidate solutions for rejection are specified based on the number of FIX satellites of the front and rear solutions is as follows.

 When the number of FIX satellites of the immediately preceding solution is smaller than the minimum number of satellites, that is, when appropriate positioning data cannot be measured, it can be assumed that the continuous solution is a solution observed in an unstable GPS observation environment. This is because if it is stable, there should be positioning data at the previous time. Furthermore, since the number of FIX satellites of the continuous solution is the minimum number of satellites, there is no observation redundancy enough to determine the reliability of the continuous solution.

  That is, it can be said that a continuous solution without observation redundancy in an unstable environment is less reliable than a solution under other conditions, and there is a high possibility that an error has occurred.

Furthermore, it is often unreasonable that the number of FIX satellites is maintained at a minimum level.
In an unstable observation environment, the number of observation satellites (the number of common satellites) is likely to increase or decrease as shown in FIG. Nevertheless, the number of FIX satellites for which ambiguity can be estimated does not change because the estimated solution corresponding to this is incorrect, resulting in a contradiction with the observed amount of satellites that became visible, This is probably because the ambiguity cannot be estimated.
It should also be taken into account that even if the actual number of observation satellites is maintained at a minimum level, the estimated solution in such a poor environment may be wrong.

  In the first embodiment, for example, the following positioning data evaluation method has been described.

  For each epoch of the position measurement solution, a solution in which the ambiguity estimation may be wrong is detected using the transition state of the number of satellites used for position measurement.

In many cases, an evaluation index for error determination using information during time series analysis cannot be reliably determined by itself.
However, by combining time-series analysis and another evaluation index that can be measured when solutions for the entire area are obtained, reliability can be improved and solutions with large position measurement errors can be rejected. .

For example, it is determined whether or not it is a miss FIX solution on the condition that “(1) the number of satellites at FIX is 5” and “(2) the number of satellites does not change in consecutive FIX sections”.
If it is determined that the solution is a miss FIX solution, the measurement data in the miss FIX section can be rejected.

  Even when the reliability of each evaluation index is low, it is possible to improve the reliability of error detection by combining an evaluation index capable of detecting a miss FIX solution with an evaluation index such as matching analysis results.

Further, it is possible to narrow down the miss FIX section.
For example, it becomes easy to perform “(1) data reacquisition only for miss FIX section” and “(2) data correction only for miss FIX section”.

Embodiment 2. FIG.
A description will be given of a form in which a solution set in the same observation region as the rejection candidate continuous solution is presented to the user as determination material of the rejection continuous solution together with the rejection candidate continuous solution.

FIG. 7 is a functional configuration diagram of the positioning device 100 according to the second embodiment.
The positioning apparatus 100 includes a neighborhood solution set extraction unit 160 in addition to the configuration described in the first embodiment (see FIG. 1).

  The neighborhood solution set extraction unit 160 (an example of the neighborhood data identification unit) identifies a set of positioning data whose distance from the low-precision data (rejection candidate) is within a predetermined distance as neighborhood data (a neighborhood solution set described later). Since the neighborhood data is a comparison target of the low precision data, it is selected so as not to include the low precision data. In addition, it is desirable that the observation time is continuous within a range where the distance from the low-precision data (rejection candidate) is within a predetermined distance, but discontinuity of a predetermined number (for example, 1 second) or less is allowed. It ’s good.

  Rejection candidate presentation unit 130 (an example of a low accuracy data display unit) displays low accuracy data and neighboring data.

FIG. 8 is a flowchart showing a positioning data evaluation method of positioning device 100 in the second embodiment.
The positioning device 100 executes S170 in addition to S110 to S160 (see FIG. 3) described in the first embodiment.
Hereinafter, S170 will be described.

  S170 is executed after S130.

In S170, the neighborhood solution set extraction unit 160 excludes low-precision data from the GPS positioning data group, and specifies a plurality of GPS positioning data whose observation times are continuous within a predetermined time (for example, 1 second) as a solution set.
The neighborhood solution set extraction unit 160 determines coordinate values that represent continuous solutions of rejection candidates, and determines coordinate values that represent solution sets for each solution set.
Hereinafter, a coordinate value representative of a continuous solution or solution set of rejection candidates is referred to as a coordinate value of continuous solutions or solution sets of rejection candidates. The coordinate value of the continuous solution of the rejection candidate represents the position of the continuous solution of the rejection candidate, and the coordinate value of the solution set represents the position of the solution set.

For example, the neighborhood solution set extraction unit 160 selects any one of a plurality of coordinate values included in the rejection candidate continuous solution or the solution set as a rejection candidate continuous solution coordinate value or a solution set coordinate value. .
Further, for example, the neighborhood solution set extraction unit 160 calculates the center (average value) of a plurality of coordinate values included in the rejection candidate continuous solution or solution set as the coordinate value of the rejection candidate continuous solution or the solution set. .

The neighborhood solution set extraction unit 160 calculates, for each solution set, the distance from the rejection candidate continuous solution based on the coordinate values of the rejection candidate continuous solutions and the coordinate values of each solution set.
However, the neighborhood solution set extraction unit 160 calculates a distance in a plane based on the latitude and longitude of the coordinate values. That is, the neighborhood solution set extraction unit 160 calculates the distance without considering the altitude.

The neighborhood solution set extraction unit 160 compares the distance from the rejection candidate continuous solution with a predetermined distance threshold (for example, 10 meters), and identifies a solution set whose distance from the rejection candidate continuous solution is equal to or smaller than the distance threshold. To do.
Hereinafter, the identified solution set is referred to as a “neighboring solution set”.

The neighborhood solution set extraction unit 160 specifies a neighborhood solution set for each continuous solution of rejection candidates.
The neighborhood solution set extraction unit 160 may specify a neighborhood solution set for each coordinate value included in the rejection candidate continuous solution.

  After S170, the process proceeds to S140.

  In S140, rejection candidate presenting section 130 presents the neighborhood solution set identified in S170 to the user together with the continuous solutions of rejection candidates identified in S130.

  By presenting a set of neighboring solutions together with a continuous solution of rejection candidates, it becomes easy to determine a continuous rejection solution.

It is considered that the continuous solution of the rejection candidates and the neighborhood solution set are observed on the same road because they are close in distance.
For example, when the measurement vehicle 200 (see FIG. 4) reciprocates on the same road and acquires GPS observation information, the continuous solution of rejection candidates is a set of GPS positioning data based on the GPS observation information acquired on the forward path (or the return path). The neighborhood solution set is a set of GPS positioning data based on GPS observation information acquired on the return path (or the outbound path).

  Therefore, the user determines that the continuous solution of the rejection candidate is the rejection continuous solution when the altitude difference between the altitude of the continuous solution of the rejection candidate and the altitude of the neighborhood solution set is equal to or greater than a predetermined value (for example, 25 centimeters). To do. This is because the difference in altitude should be small on the same road.

The rejection candidate presenting unit 130 may calculate an altitude difference between the altitude of the continuous solution of the rejection candidates and the altitude of the neighborhood solution set, and may present the altitude difference in addition to the continuous solution of the rejection candidates and the neighborhood solution set.
The rejection candidate presenting unit 130 may present an altitude difference instead of the neighborhood solution set.

FIG. 9 is a horizontal diagram illustrating a display example of rejection candidates in the second embodiment.
In FIG. 9, “◯” is a plot of a plurality of coordinate values (latitude, longitude) included in the neighborhood solution set, and “×” is a plot of a plurality of coordinate values (latitude, longitude) included in the rejection candidate. It is a thing.

Assume that the measurement vehicle 200 (see FIG. 4) travels three times on a road having a plurality of lanes. The measurement vehicle 200 traveled in the first lane for the first and second times, and traveled in the second lane for the third time.
Since the number of FIX satellites may be less than the minimum number of satellites during the third run, a part of the continuous solutions when the third run is presented as a continuous candidate solution.

The altitude difference between the altitude “111.71 meters” of the first neighborhood solution set and the altitude “111.44 meters” of the third rejection candidate to the altitude “111.73 meters” of the second neighborhood solution set is a predetermined value. (For example, 0.25 meters) or more.
Therefore, the user determines that the third rejection candidate is a rejection continuous solution.

Even if there is only one neighborhood solution set specified by the neighborhood solution set extraction unit 160 (for example, the first neighborhood solution set is selected), a plurality of (eg, 1st and 2nd neighborhood solution sets) are selected. It may be a neighborhood solution set).
The neighborhood solution set extraction unit 160 may specify solution sets before and after the rejection candidate (for example, the third neighborhood solution set) as neighborhood solution sets. The neighborhood solution set extraction unit 160 may exclude the solution sets before and after the rejection candidate from the neighborhood solution set.

  In the second embodiment, for example, the following positioning data evaluation method has been described.

A solution that is expected to have a large position measurement error is extracted by comparing a solution having a possibility of estimation error with a nearby solution that is expected to have almost the same height.
Rejecting these solutions improves the reliability of the position measurement solution.

Embodiment 3 FIG.
A mode for specifying the reject continuous solution based on the number of front and rear solution satellites and the altitude difference between the neighboring solution sets will be described.

FIG. 10 is a functional configuration diagram of the positioning device 100 according to the third embodiment.
The rejection candidate specifying unit 120 of the positioning device 100 includes a neighborhood solution set extracting unit 123. The other configuration of the positioning device 100 is the same as that of the first embodiment (see FIG. 1).

  The neighborhood solution set extraction unit 123 (an example of the neighborhood data specifying unit) uses a set of positioning data whose distance from a low-precision data candidate (continuous solution of rejection candidates) is within a predetermined distance as neighborhood data (neighbor solution set). Identify.

Rejection candidate extraction unit 122 (an example of a low-accuracy data specification unit) converts low-accuracy data candidates (rejection candidate rejection data) from a plurality of continuous data (continuous solutions) that have consecutive data whose number of used satellites is less than a predetermined number. Specified as continuous solution).
The rejection candidate extraction unit 122 identifies the low-accuracy data candidates as low-accuracy data (continuous solutions of rejection candidates to be presented to the user) when the altitude difference between the low-accuracy data candidates and the neighborhood data is greater than or equal to a predetermined difference. To do.

FIG. 11 is a flowchart showing a positioning data evaluation method of positioning device 100 in the third embodiment.
The positioning device 100 executes S180 and S190 in addition to S110 to S160 (see FIG. 3) described in the first embodiment.
Hereinafter, S180 and S190 will be described.

  S180 is executed after S130.

In S180, the neighborhood solution set extraction unit 123 determines a coordinate value for each rejection candidate continuous solution and each solution set, and calculates a distance between the rejection candidate continuous solution and each solution set based on the determined coordinate values. A solution set whose distance from the rejection candidate continuous solution is equal to or smaller than the distance threshold is specified as a neighborhood solution set. The method for specifying the neighborhood solution set is the same as S170 (see FIG. 8) of the second embodiment.
After S180, the process proceeds to S190.

In S190, the rejection candidate extraction unit 122 calculates an altitude difference between the altitude of the rejection candidate and the altitude of the neighborhood solution set for each consecutive solution of the rejection candidates, and the calculated altitude difference is a predetermined altitude threshold (for example, 25 centimeters). ) The rejection candidates that are less than are excluded from the rejection candidates.
That is, the rejection candidate extraction unit 122 extracts, as rejection candidates, those that have an altitude difference equal to or higher than the altitude threshold among the consecutive solutions of rejection candidates identified in S130.
After S190, the process proceeds to S140, and rejection candidates are presented to the user.

  In the third embodiment, for example, the following positioning data evaluation method has been described.

A solution that is expected to have a large position measurement error is extracted by comparing a solution having a possibility of estimation error with a nearby solution that is expected to have almost the same height.
Rejecting these solutions improves the reliability of the position measurement solution.

  100 positioning device, 110 continuous solution grouping unit, 120 rejection candidate identification unit, 121 front and rear solution extraction unit, 122 rejection candidate extraction unit, 123 neighborhood solution set extraction unit, 130 rejection candidate presentation unit, 140 rejection candidate rejection unit, 150 rejection continuous Solution complementing unit, 160 Neighborhood solution set extracting unit, 190 Positioning data storage unit, 200 Measuring vehicle, 201 Top plate, 210a, 210b, 210c GPS receiver, 220 Inertial device, 230 Vehicle speed detecting device, 290 Self-positioning device, 901 Display device, 902 keyboard, 903 mouse, 904 drive device, 911 CPU, 912 bus, 913 ROM, 914 RAM, 915 communication board, 920 magnetic disk device, 921 OS, 922 window system, 923 program group, 924 file group.

Claims (9)

Indicates the coordinate value and observation time measured using the carrier phase observation amount of the signal transmitted from each of the positioning satellites, and the number of positioning satellites corresponding to the carrier phase observation amount used for the coordinate value measurement. A positioning data storage unit for storing a plurality of data including the number of used satellites as positioning data;
Continuously specifying a plurality of sets of positioning data having continuous observation times and the number of used satellites being the same as a predetermined number from a plurality of positioning data stored in the positioning data storage unit as continuous data A data identification part;
For each continuous data specified by the continuous data specifying unit, the immediately preceding data specifying that specifies the positioning data including the observation time immediately before the first observation time included in the continuous data as the immediately preceding data from the plurality of positioning data. And
Among the plurality of continuous data specified by the continuous data specifying unit, the continuous data whose number of used satellites of the immediately preceding data specified by the immediately preceding data specifying unit is less than the predetermined number is low-precision data whose coordinate value accuracy is low. A positioning data evaluation apparatus comprising: a low-precision data specifying unit that specifies The positioning data evaluation device further includes:
For each piece of continuous data specified by the continuous data specifying unit, the immediately following data specifying that specifies the positioning data including the observation time immediately after the last observation time included in the continuous data as the immediately following data from the plurality of positioning data. Part
The low-accuracy data specifying unit includes the number of used satellites of the immediately preceding data specified by the immediately preceding data specifying unit and the immediately following specified by the immediately following data specifying unit among the plurality of continuous data specified by the continuous data specifying unit. 2. The positioning data evaluation apparatus according to claim 1, wherein continuous data whose number of data using satellites is less than the predetermined number is specified as the low-precision data. The positioning data evaluation device further includes:
A low-precision data display unit for displaying low-precision data specified by the low-precision data specifying unit on a display device;
The positioning data evaluation apparatus according to claim 1, further comprising a low precision data deleting unit that deletes low precision data designated by a user using an input device from the positioning data storage unit. The positioning data evaluation device further includes:
A set of positioning data having continuous observation times is identified from the remaining positioning data excluding the low-precision data among the plurality of positioning data stored in the positioning data storage unit, and the positioning data for each set of specified positioning data Determining the coordinate value of the set of positioning data based on the coordinate value indicated by at least one of the positioning data included in the set of, and based on the coordinate value indicated by at least any of the positioning data included in the low-precision data A proximity data specifying unit that determines coordinate values of low-precision data and specifies a set of positioning data whose distance between the coordinate values and the low-precision data is within a predetermined distance as neighborhood data,
The positioning data evaluation apparatus according to claim 3, wherein the low precision data display unit displays the low precision data and the neighborhood data. The positioning data evaluation device further includes:
An inertial navigation storage unit for storing coordinate values measured by inertial navigation for each time;
Among the coordinate values stored in the inertial navigation storage unit, the coordinate value corresponding to the observation time of the low-accuracy data deleted by the low-accuracy data deletion unit is specified, and the positioning data storage is performed using the specified coordinate value as positioning data 5. A positioning data evaluation apparatus according to claim 3, further comprising a positioning data complementing section stored in the section. Indicates the coordinate value and observation time measured using the carrier phase observation amount of the signal transmitted from each of the positioning satellites, and the number of positioning satellites corresponding to the carrier phase observation amount used for the coordinate value measurement. A positioning data storage unit for storing a plurality of data including the number of used satellites as positioning data;
Continuously specifying a plurality of sets of positioning data having continuous observation times and the number of used satellites being the same as a predetermined number from a plurality of positioning data stored in the positioning data storage unit as continuous data A data identification part;
For each continuous data specified by the continuous data specifying unit, the immediately preceding data specifying that specifies the positioning data including the observation time immediately before the first observation time included in the continuous data as the immediately preceding data from the plurality of positioning data. And
Among the plurality of continuous data specified by the continuous data specifying unit, the continuous data whose number of used satellites of the immediately preceding data specified by the immediately preceding data specifying unit is less than the predetermined number is low-precision data whose coordinate value accuracy is low. and a low precision data identifying unit for identifying as a candidate,
A set of positioning data having continuous observation times is identified from the remaining positioning data excluding the low-precision data candidates among the plurality of positioning data stored in the positioning data storage unit, and for each specified positioning data set The coordinate value of the set of positioning data is determined based on the coordinate value indicated by at least one of the positioning data included in the set of positioning data, and the coordinate value indicated by at least one of the positioning data included in the low-precision data candidate wherein determining the coordinate values of the low-precision data candidates based on the the neighboring data identifying unit distance of the coordinate values of the low-precision data candidate is identified as the proximate data a set of positioning data is within the predetermined distance Prepared,
The low-precision data specifying unit specifies the low-precision data candidate as low-precision data when an altitude difference between the low-precision data candidate and the neighborhood data specified by the neighborhood data specifying unit is greater than or equal to a predetermined difference. A positioning data evaluation device characterized by: The positioning data evaluation device further includes:
A low-precision data deleting unit that deletes the low-precision data specified by the low-precision data specifying unit from the positioning data storage unit;
An inertial navigation storage unit for storing coordinate values measured by inertial navigation for each time;
Among the coordinate values stored in the inertial navigation storage unit, the coordinate value corresponding to the observation time of the low-accuracy data deleted by the low-accuracy data deletion unit is specified, and the positioning data storage is performed using the specified coordinate value as positioning data The positioning data evaluation apparatus according to claim 6, further comprising a positioning data complementing unit stored in the unit. The positioning data storage unit corresponds to the coordinate value and observation time measured using the carrier phase observation amount of the signal transmitted from each of the plurality of positioning satellites, and the carrier phase observation amount used for the coordinate value measurement. Multiple data including the number of satellites used indicating the number of positioning satellites is stored as positioning data.
The continuous data specifying unit continuously sets a set of positioning data having the same number as a predetermined number of observation satellites and the number of used satellites determined in advance from a plurality of positioning data stored in the positioning data storage unit. Specify multiple data,
For the continuous data specified by the continuous data specifying unit, the immediately preceding data specifying unit uses the positioning data including the observation time immediately before the first observation time included in the continuous data as the immediately preceding data, as the plurality of positioning data. Identified from
The low-precision data specifying unit sets coordinate values of continuous data in which the number of used satellites of the immediately preceding data specified by the immediately preceding data specifying unit is less than the predetermined number among the plurality of continuous data specified by the continuous data specifying unit. A positioning data evaluation method characterized by specifying low-precision data with low accuracy.   A positioning data evaluation program for causing a computer to execute the positioning data evaluation method according to claim 8.

Images