JP7278511B2 - Waveform estimation device, ionospheric delay amount estimation system, waveform estimation method, and waveform estimation program - Google Patents

Description

The present disclosure is a waveform estimation device for estimating the state of a continuum with a spatio-temporal spread, in particular, estimating the wave structure of the continuum when the state of the continuum is different from the normal state, an ionospheric delay amount An estimation system, a waveform estimation method, and a waveform estimation program.

Ionospheric delay amount used in a satellite positioning system that estimates the electron density when radio waves (electromagnetic waves), which are positioning signals from positioning satellites, pass through the ionosphere as a device for estimating the state of a continuum with a spatiotemporal spread. An estimating device and a sea surface estimating device in a marine radar device that irradiates a fan-shaped radar coverage area on the sea surface with radio waves (electromagnetic waves) and estimates the state of the sea surface from the radio waves reflected from the sea surface are known. there is

For example, Patent Literature 1 discloses technology related to a satellite positioning system. In Patent Document 1, the spatial coordinates of the intersection points of the transmission axis of the radio frequency signal transmitted by the transmission navigation satellite and the surface surrounding the earth, and the vertical total electron number determined at these intersection points, are calculated, and the ionosphere on the line-of-sight of the satellite is calculated. A method for calculating the delay is shown.
Furthermore, in Patent Document 1, when the ionosphere is extremely non-uniform, that is, when there is a strong disturbance, more target nodes, that is, monitor stations are increased than the target nodes in the case of weak disturbance, and the line-of-sight of the satellite A method for calculating the ionospheric delay of .

JP 2013-186127 A

In the conventional technology disclosed in Patent Document 1, when the state of the ionosphere, which is a continuum, is different from normal, the number of monitor stations that obtain observation values is increased, so the number of monitor stations cannot be increased. In this case, there is a problem that the estimation accuracy of the ionospheric delay decreases when the ionospheric state is different from the normal state.

The present disclosure provides accuracy in estimating the wave structure of a continuum even when the state of the continuum is different from the normal state without increasing the number of receiving points observing the observation points for the continuum with a spatio-temporal spread. It is an object of the present invention to obtain a waveform estimation device capable of improving the

The waveform estimation device according to the present disclosure obtains each of the observed values of the continuum at a plurality of observation points for a spatiotemporally wide continuum that has the property of becoming a plane wave structure when a state different from the normal state occurs, A cross-sectional projection unit that performs coordinate conversion processing to a one-dimensional spatial coordinate that is projected onto a first-order straight line parallel to the propagation direction of radio waves to each of a plurality of observation points, and a one-dimensional coordinate conversion processed by the cross-sectional projection unit A spatial DFT unit that performs a discrete Fourier transform on the observed values of the continuum at the spatial coordinates to obtain the spatial distribution plane wave function of the continuum, and a window function from the spatial distribution plane wave function of the continuum obtained by the spatial DFT unit A filter section that obtains the spatial distribution plane wave function of the continuum with noise removed, and the inverse discrete Fourier transform of the spatial distribution plane wave function of the continuum obtained by the filter section, with the noise removed, to obtain the spatial distribution function of the continuum. a waveform estimator having a spatial IDFT unit;

According to the present disclosure, when the state of the continuum is different from the normal state, the accuracy of estimating the wave structure of the continuum that spreads spatio-temporally is improved without increasing the number of receiving points that observe the observation points. can.

1 is a block diagram showing an ionospheric delay amount estimation system according to Embodiment 1; FIG. 1 is a block diagram showing a waveform estimation device according to Embodiment 1; FIG. FIG. 4 is a diagram for explaining coordinate conversion processing by a cross-sectional projection unit of the waveform estimation device according to Embodiment 1; 4 is a flowchart showing ionospheric delay amount distribution estimation processing of the waveform estimation device according to Embodiment 1. FIG. 4 is a diagram showing the total number of electrons in the ionosphere estimated by the waveform estimation device in Embodiment 1. FIG. 2 is a block diagram showing a waveform estimation device according to Embodiment 2; FIG. FIG. 10 is a diagram showing the spatial distribution of the total number of electrons in the ionosphere on which the discrete Fourier transform is performed by the spatial DFT section of the waveform estimation device according to Embodiment 2; FIG. 10 is a diagram showing a two-dimensional spatial distribution plane wave function obtained by the time DFT section of the waveform estimation device according to Embodiment 2; FIG. 10 is a diagram showing an image of filtering processing for a result by the time DFT unit of the waveform estimation device according to Embodiment 2; FIG. 11 is a block diagram showing a waveform estimation device according to Embodiment 3; FIG. 11 is a block diagram showing a waveform estimation device according to Embodiment 4; FIG. 11 is a block diagram showing a sea surface current velocity estimation system according to Embodiment 5; FIG. 14 is a diagram for explaining coordinate conversion processing by a cross-sectional projection unit of the waveform estimation device according to Embodiment 5;

Embodiment 1.
The ionospheric delay amount estimation system according to Embodiment 1 is a satellite such as an observation device that measures a distance from the propagation time of radio waves such as a GNSS (Global Navigation Satellite System), an earth observation satellite, and a space surveillance radar. It is a system used for a positioning system.
The ionospheric delay estimating apparatus in the ionospheric delay estimating system according to the first embodiment is particularly useful when the spatial distribution of the number of ionospheric electrons that causes propagation delay in the ionosphere, which is a continuum with a spatiotemporal spread, is uneven. In some cases, by utilizing the property that the spatial distribution of the ionospheric electron number has a wave structure, it is possible to estimate the wave structure of the ionosphere that spreads out from the observation point unit, which is the monitor station, and suppress the deterioration of the spatial distribution estimation accuracy. It is a device that
The amount of propagation delay of radio waves passing through the ionosphere increases in proportion to the total electron content (TEC) of the ionosphere on the propagation path. Hereinafter, the total number of electrons in the ionosphere on the propagation path is abbreviated as TEC.

An ionospheric delay amount estimation system according to Embodiment 1 will be described with reference to FIGS. 1 to 5. FIG.
As shown in FIG. 1, the ionospheric delay amount estimation system includes a positioning satellite 100 and N (N is a natural number of 2 or more) monitor stations each receiving radio waves from the positioning satellite 100 that have passed through different observation points. 200(1), monitor station 200(2), . . . monitor station 200(N), and waveform estimation device 300.

A plurality of monitor stations 200(1) to 200(N) are monitor stations present in the target area of the ionospheric delay amount estimation system according to the first embodiment.
Since the monitor station 200(1) to the monitor station 200(N) are monitor stations having the same configuration, in order to avoid complication of the explanation, the suffixes in parentheses will be omitted below and the monitor station 200 will be explained. .

The positioning satellite 100 is an artificial satellite such as a GPS satellite that periodically transmits positioning signals (radio waves) used for positioning. The positioning signal has a plurality of frequencies, and in this first embodiment, the positioning signal has two different frequencies, a frequency in the 1.6 GHz band and a frequency in the 1.2 GHz band.

The monitor station 200 serves as a reception point for receiving a positioning signal from the positioning satellite 100, which is located in the target area and whose coordinates are known. The monitor station 200 is an electronic control point installed by the Geospatial Information Authority of Japan. The monitor station 200 comprises a GNSS receiver.
The GNSS receiver receives positioning signals of two different frequencies from the positioning satellites 100, and generates observation data, such as pseudoranges, for each of the two positioning signals from the two positioning signals received. The position information indicating the coordinates of the monitor station 200 and the observation data generated by the monitor station 200 are transmitted to the waveform estimation device 300 via the network.

The waveform estimation device 300 accumulates observation data of positioning signals received from a plurality of monitor stations 200 for each area where a plurality of monitor stations 200 gather, estimates the spatial distribution of TECs based on the accumulated observation data, and estimates the ionospheric distribution. Obtain the spatial distribution of the amount of delay. That is, the ionospheric delay amount located between observation data is estimated from the accumulated observation data, and the spatial distribution of the ionospheric delay amount is obtained.
The waveform estimation device 300 includes an ionospheric electron number calculator 1, an ionospheric disturbance occurrence determination unit 2, an ionospheric curved surface model estimator 3, an ionospheric plane wave model estimator 4, an ionospheric delay amount calculator 5, and an ionospheric delay amount output. 6 and an ionospheric delay estimation device.

The ionospheric electron number calculation unit 1 accumulates observation data of positioning signals received from a plurality of monitor stations 200, and calculates the ionospheric delay amount between each monitor station 200 and the positioning satellite 100 based on the observation data from each monitor station 200. TEC is obtained from the calculated ionospheric delay amount.
Specifically, the amount of delay differs depending on the frequency of radio waves passing through the ionosphere, that is, the amount of ionospheric delay has frequency dependence. By calculating the ionospheric delay amount between each monitor station 200 and the positioning satellite 100 from the difference in frequency observation data, and multiplying the calculated ionospheric delay amount by a coefficient, the difference between each monitor station 200 and the positioning satellite 100 is calculated. Calculate the TEC between

TEC is the direction of propagation of radio waves from the positioning satellite 100 to the monitor station 200, that is, the line-of-sight total electron count (STEC) between the positioning satellite 100 and the monitor station 200 on the line of sight from the monitor station 200 to the positioning satellite 100. Alternatively, the ionosphere is assumed to be a single film, and all electrons are concentrated on the intersection of the straight line connecting the monitoring station 200 and the positioning satellite 100 and the ionospheric film assumed to be the single film in the vertical direction. Total electron count (VTEC) is used.
The TEC is calculated for each monitor station 200 , and the calculated TEC is the ionospheric observed value at the ionospheric observation point observed by the monitor station 200 . The calculated TEC is hereinafter referred to as the TEC observed value.

That is, the ionospheric electron number calculation unit 1 integrates observation data of a plurality of frequencies output from each of the plurality of monitor stations 200(1) to 200(N) that have received positioning signals from the positioning satellite 100, Based on observation data from each monitor station 200 of monitor stations 200(1) to 200(N), the number of total electrons in the ionosphere between each monitor station 200 and the positioning satellite 100, which is an observed value, is calculated.

The ionospheric disturbance occurrence determining unit 2 determines whether an ionospheric disturbance is occurring in the ionosphere in the target area based on the TEC calculated corresponding to each monitor station 200 by the ionospheric electron number calculating unit 1, that is, based on the TEC observation value. do.
The ionospheric disturbance occurrence determination by the ionospheric disturbance occurrence determination unit 2 is based on the magnitude of the variance of the TEC observation value. is determined to have occurred. Alternatively, a judgment is made based on the size of the variance of the position observation error of the TEC observation value, that is, if the variance of the position observation error of the TEC observation value is greater than the variance threshold, which is the judgment condition set by the threshold value, an ionospheric disturbance has occurred in the target area. determine that there is

That is, the ionospheric disturbance occurrence determination unit 2 determines whether or not an ionospheric disturbance has occurred based on the total number of electrons in the ionosphere calculated by the ionospheric electron number calculation unit 1 for the plurality of monitor stations 200 existing in the target area and the set determination condition. do.

When the ionospheric disturbance occurrence determining unit 2 determines that no ionospheric disturbance has occurred, the ionospheric curved surface model estimating unit 3 uses the position information (coordinates) of each monitor station 200 and the ionospheric electron number calculating unit 1 to correspond to each monitor station 200. A spatial distribution of TEC observation values is estimated using a curved surface model based on the TEC calculated by the above method, regression analysis is performed using the curved surface model, and a spatial distribution function of the TEC observation values using the curved surface model is obtained. The ionospheric curved surface model estimator 3 approximates the spatial distribution of the TEC observation values with a function and outputs it.
Polyhedral models of TEC observations can use, for example, polynomial surfaces, quadratic surfaces, and spherical harmonics. The ionospheric curved surface model estimator 3 obtains the curved surface model space distribution function of the TEC observation value by a generally known method.

In this way, when the ionospheric disturbance occurrence determining unit 2 determines that no ionospheric disturbance has occurred in the ionosphere, the ionospheric curved surface model estimating unit 3 performs observation corresponding to a plurality of monitor stations 200 arranged in the target area. A spatial distribution of TEC observations is estimated using a surface model based on TEC, which is a value, to obtain a surface model spatial distribution function of TEC observations.

When the ionospheric disturbance occurrence determination unit 2 determines that an ionospheric disturbance has occurred, the ionospheric plane wave model estimation unit 4 uses the position information (or latitude and longitude information: coordinates) of each monitor station 200 and the ionospheric electron number calculation unit 1 to determine each monitor Based on the TEC calculated for the station 200, the spatial distribution of the TEC observation values is estimated by the plane wave model, analysis is performed by the plane wave model, and the spatial distribution function of the TEC observation values by the plane wave model is obtained.
The ionospheric plane wave model estimator 4 is a waveform estimator that outputs the spatial distribution of TEC observation values as a function of the plane wave.

In this way, when the ionospheric disturbance occurrence determining unit 2 determines that an ionospheric disturbance is occurring in the ionosphere, the ionospheric plane wave model estimating unit 4 performs observation corresponding to a plurality of monitor stations 200 arranged in the target area. A spatial distribution of TEC observations is estimated using a plane wave model based on TEC, which is a value, and a spatial distribution function of TEC observations by the plane wave model is obtained.

Ionospheric disturbances that occur in the ionosphere are traveling ionospheric disturbances (TID) that have a plane wave structure, so the spatial distribution of TECs has the property of having a propagating plane wave structure.
The waveform estimating apparatus 300 according to Embodiment 1 utilizes the property that the spatial distribution of TEC observation values has a propagative plane wave structure, and when the ionospheric disturbance occurrence determining unit 2 determines that an ionospheric disturbance has occurred, the ionospheric plane wave model The estimation unit 4 obtains the spatial distribution function of the TEC observation values.

The ionospheric plane wave model estimator 4 includes a cross-sectional projection unit 41, a spatial DFT unit 42, a filter unit 43, and a spatial IDFT unit 44, as shown in FIG.
The cross-sectional projection unit 41 uses the position information (coordinates) of each monitor station 200 and the TEC calculated corresponding to each monitor station 200 by the ionospheric electron number calculation unit 1, and calculates corresponding to each monitor station 200. Utilizing the property that the spatial distribution of TEC observation values has a propagating plane wave structure, the TEC is converted into one-dimensional spatial coordinates projected onto a first-order straight line parallel to the traveling direction of the TID.

The coordinate conversion processing performed by the cross-sectional projection unit 41 will be described with reference to FIG. In FIG. 3, the x-axis and y-axis indicate a planar xy coordinate system, and the x'-axis and y'-axis indicate a planar coordinate system consisting of the x-axis and the y-axis. The x'-y' coordinate system is shown rotated in the
The xy coordinate system is a planar coordinate system obtained by projecting the spatial coordinates onto a plane. The x'-y' coordinate system is a coordinate system rotated by an angle φ of the direction of travel of the TID with respect to the xy coordinate system.
Also, by way of illustration, the six monitor stations 200(1)-200(6) are shown as ● in the xy coordinate system. Since the position coordinates of the monitor stations 200(1) to 200(6) correspond to the position coordinates of the observation points, the position coordinates of the monitor stations 200(1) to 200(6) are used as the position coordinates of the observation points.

It is assumed that the TID is a two-dimensional propagating plane wave, and its traveling direction is given as a parameter. Also, the TEC observation value is taken in the amplitude direction of the TID, and the spatial coordinate is a planar coordinate system projected onto a plane.
The displacement Ψ(k, v) at the position r=(x, y) of the TID whose amplitude is A and whose wave vector is k=(k cos φ, ksin φ) is expressed by the following equation (1).

Displacement Ψ(k, v) indicates that the TID is expressed as a one-dimensional sine wave by the coordinate transformation operation.
Therefore, the cross-sectional projection unit 41 projects the coordinates of each monitor station 200 onto a first-order straight line parallel to the traveling direction of the TID, that is, perpendicular to the equiphase surface of the plane wave, thereby converting the TEC observation value into a one-dimensional Convert to representation as a wave. Specifically, one-dimensional space coordinates are calculated based on the traveling direction parameter and the position coordinates of the monitor station 200 .

In short, the cross-sectional projection unit 41 obtains a one-dimensional spatial distribution of TEC observation values obtained by projecting the TEC calculated for each monitor station 200 onto a first-order straight line parallel to the traveling direction of the TID.
Projection points corresponding to the six monitor stations 200(1) to 200(6) coordinate-transformed by the cross-sectional projection unit 41 are shown as white x200(1) to 200(6).

As can be understood from FIG. 3, in the xy coordinate system, the monitor station 200(2) and the monitor station 200(3) have the same x value, but after coordinate conversion processing by the cross-sectional projection unit 41, Monitor station 200(2) and monitor station 200(3) have different values on the x' axis.
As a result, in the x'-y' coordinate system, the sampling number of monitor stations 200 existing in the target area is substantially increased, and the sampling density is increased.
The increased sampling density improves the accuracy of estimating the spatial distribution of TEC observations, even if the spatial distribution of TECs in the ionosphere is non-uniform.

The spatial DFT unit 42 performs a nonuniform discrete Fourier transform (DFT) on the TEC observation values at the one-dimensional spatial coordinates that have undergone the coordinate conversion processing by the cross-sectional projection unit 41, and obtains the spatial distribution plane wave function of the TEC observation values.
That is, the spatial DFT unit 42 transforms the TEC observation values in one-dimensional spatial coordinates that have undergone coordinate conversion processing by the cross-sectional projection unit 41 from the spatial axis to the spatial frequency axis by the nonuniform discrete Fourier transform, and converts the TEC observation values Find the spatial distribution plane wave function.

In other words, the spatial DFT unit 42 converts the TEC observation values on the spatial axis projected by the cross-sectional projection unit 41 into a spatial distribution plane wave of the TEC observation values on the spatial frequency axis as a set of sine waves consisting of a plurality of wavelengths. Convert to function.
The spatial DFT unit 42 calculates the spatial frequency from the TEC observation value in the one-dimensional space coordinate coordinate-transformed by the cross-sectional projection unit 41 and the TEC calculated corresponding to each monitor station 200 by the ionospheric electron number calculation unit 1. to obtain the spatial distribution plane wave function of the TEC observations.

The filter unit 43 uses a window function to extract the TID component from the spatial distribution plane wave function of the TEC observation value on the spatial frequency axis obtained by the spatial DFT unit 42, and extracts the noise-removed spatial distribution plane wave of the TEC observation value. Find a function.
That is, the TEC observation values obtained by the spatial DFT unit 42 contain noise of observation errors due to plane wave model errors, atmospheric conditions, multipaths, etc. These noises have high frequency (short wavelength) components.
The filter unit 43 removes the noise of these high-frequency components from the spatial distribution plane wave function of the TEC observation values on the spatial frequency axis obtained by the spatial DFT unit 42 using a window function.

The window function used in the filter unit 43 may extract only the peak with the largest amplitude, may extract wavelength components whose amplitude is greater than or equal to a threshold value, or may extract components whose spatial frequency is less than or equal to a threshold value. It may be operated like a low-pass filter.

The spatial IDFT unit 44 performs an inverse discrete Fourier transform on the spatial distribution plane wave function of the TEC observation values from which noise has been removed by the filter unit 43, and obtains the spatial distribution function of the TEC observation values.
That is, the spatial IDFT unit 44 converts the spatial distribution plane wave function of the TEC observation value from which noise has been removed by the filter unit 43 into a representation on the one-dimensional coordinate axis from the spatial frequency axis back to the spatial axis, and the filter on the one-dimensional coordinate axis. The spatial distribution function of the TEC calculated for each monitor station 200 by the ionospheric electron number calculator 1 before being projected by the cross-sectional projection unit 41 on the TEC observation value noise-removed by the unit 43 is obtained.

The ionospheric delay amount calculator 5 multiplies the spatial distribution function of the TEC observation value obtained by the ionospheric curved surface model estimating unit 3 or the spatial distribution function of the TEC observation value obtained by the ionospheric plane wave model estimating unit 4 by a coefficient to calculate the ionospheric Obtain the spatial distribution function of the amount of delay.

The ionospheric delay amount output unit 6 outputs the spatial distribution function of the ionospheric delay amount obtained by the ionospheric delay amount calculation unit 5 .
The spatial distribution function of the ionospheric delay amount output from the ionospheric delay amount output unit 6 is distributed to the user by a distribution method such as an Internet line or a satellite line using a distribution format such as a spatial distribution function or interpolation to grid points. be.

Next, the operation of waveform estimation apparatus 300 according to Embodiment 1 will be described based on FIG.
In step ST1, the ionospheric electron number calculation unit 1 accumulates observation data of a plurality of frequencies output from each of the plurality of monitor stations 200 that have received positioning signals from the positioning satellites 100, and Based on the observation data from the station 200, the TEC between each monitor station 200 and the positioning satellite 100, which is an observation value, is calculated, and the process proceeds to step ST2.

In step ST2, the ionospheric disturbance occurrence determining unit 2 analyzes the TEC calculated corresponding to each monitor station 200 by the ionospheric electron number calculating unit 1, that is, compares the calculated TEC with the set decision condition, Determine the presence or absence of disturbance.
If it is determined that no ionospheric disturbance has occurred, the process proceeds to step ST3, and if it is determined that the ionospheric disturbance has occurred, the process proceeds to step ST4.

In step ST3, the ionospheric curved surface model estimating unit 3 estimates the spatial distribution of the total number of ionospheric electrons using a curved surface model based on the TEC calculated for each monitor station 200 by the ionospheric electron number calculating unit 1. Regression analysis is performed on the obtained TEC using a curved surface model to obtain a spatial distribution function of the total electron number in the ionosphere based on the curved surface model, and the process proceeds to step ST5.

On the other hand, in step ST4, the ionospheric plane wave model estimating unit 4 estimates the spatial distribution of the TEC observation values by the plane wave model based on the calculated TEC, and obtains the spatial distribution function of the TEC observation values by the plane wave model. It is implemented by steps ST41 to ST44.

In step ST41, the positional information (coordinates) of each monitor station 200, that is, the positional information corresponding to the observation point, and the TEC calculated by the ionospheric electron number calculation unit 1 corresponding to each monitor station 200 by the cross-sectional projection unit 41 , the TEC calculated for each monitor station 200 is converted into one-dimensional spatial coordinates by projecting them onto a linear straight line parallel to the traveling direction of the TID, and the process proceeds to step ST42.

In step ST42, the spatial DFT unit 42 transforms the TEC observation values in the one-dimensional spatial coordinates from the spatial axis to the spatial frequency axis by nonuniform discrete Fourier transform, obtains the spatial distribution plane wave function of the TEC observation values, and proceeds to step ST43. move on.

In step ST43, the filter unit 43 uses a window function to extract propagating ionospheric disturbance components from the spatial distribution plane wave function of the TEC observation value obtained by the spatial DFT unit 42, removes noise, and removes the noise. Then, the spatial distribution plane wave function of the TEC observed value is obtained, and the process proceeds to step ST44.

In step ST44, the spatial IDFT unit 44 converts the spatial distribution plane wave function of the TEC observation values, the noise of which has been removed by the filter unit 43, into an expression on the spatial axis by an inverse discrete Fourier transform, and obtains the spatial distribution function of the TEC observation values. , go to step ST5.

In step ST5, the ionospheric delay amount calculator 5 calculates the spatial distribution function of the TEC observation value obtained by the ionospheric surface model estimating unit 3 in step ST3 or the TEC observation value obtained by the ionospheric plane wave model estimating unit 4 in step ST4. The spatial distribution function is multiplied by a coefficient to convert to the spatial distribution function of the ionospheric delay amount, and the process proceeds to step ST6.

In step ST6, the ionospheric delay amount output section 6 outputs the spatial distribution function of the ionospheric delay amount obtained by the ionospheric delay amount calculating section 5. FIG.
At this time, the spatial distribution function of the ionospheric delay amount is converted into a predetermined format and delivered to the user.

As described above, in the waveform estimation apparatus 300 according to the first embodiment, the ionospheric disturbance occurrence determining unit 2 determines whether or not an ionospheric disturbance has occurred. If the spatial distribution function of the TEC observation value is obtained by determining that the ionospheric disturbance has occurred, the ionospheric plane wave model estimating unit 4 obtains the spatial distribution function of the TEC observation value, and if it is determined that the ionospheric disturbance does not occur is the spatial distribution function of the TEC observation values obtained by the ionospheric curved surface model estimating unit 3, and when it is determined that the ionospheric disturbance has occurred, the spatial distribution function of the TEC observation values obtained by the ionospheric plane wave model estimating unit 4 is used to obtain the spatial distribution function of the ionospheric delay amount by the ionospheric delay amount calculator 5 .

The ionospheric electron number calculator 1, the ionospheric disturbance occurrence determination unit 2, the ionospheric curved surface model estimator 3, the ionospheric plane wave model estimator 4, and the ionospheric delay amount in the ionospheric delay amount estimator constituting the waveform estimator 300 according to Embodiment 1 The calculation unit 5 and the ionospheric delay amount output unit 6 may be configured in hardware or in software.

When the ionospheric delay amount estimating device is configured as software, the ionospheric electron number calculation unit 1, the ionospheric disturbance occurrence determination unit 2, the ionospheric surface model estimating unit 3, the ionospheric plane wave model estimating unit 4, the ionospheric delay amount calculating unit 5, and the ionospheric delay. The quantity output unit 6 is composed of a general computer, and is composed of a CPU (Central Processing Unit), a semiconductor memory (RAM: Random Access Memory), and a nonvolatile recording device (ROM: Read only memory), and is stored in the ROM A waveform estimation program is loaded into the RAM, and the CPU executes various processes based on the waveform estimation program loaded into the RAM. The ionospheric delay estimation device is driven by a general-purpose OS.

The recording medium for storing the waveform estimation program is not limited to the ROM, and may be a hard disk or the like.
Also, the waveform estimation program stored in the recording medium is as follows.

That is, the waveform estimation program is a procedure for calculating the TEC between each of the plurality of monitor stations and the positioning satellite based on the observation data of the plurality of frequencies output from each of the plurality of monitor stations that received the positioning signals from the positioning satellites. a procedure for judging whether or not an ionospheric disturbance has occurred according to judgment conditions set based on the calculated TEC; A procedure for estimating the distribution with a curved surface model and obtaining a spatial distribution function of the TEC observation values by the curved surface model, and when it is determined that an ionospheric disturbance has occurred, the spatial distribution of the TEC observation values is converted to a plane wave based on the calculated TEC. A procedure for estimating with a model and obtaining the spatial distribution function of the TEC observation value by the plane wave model, and the ionospheric delay amount by multiplying the spatial distribution function of the TEC observation value by the curved surface model or the spatial distribution function of the TEC observation value by the plane wave model by the coefficient and a procedure for outputting the spatial distribution function of the ionospheric delay amount.

FIG. 5 shows the spatial distribution of TEC observation values when an ionospheric disturbance occurs in the ionosphere in the waveform estimation device 300 according to the first embodiment. 5, the horizontal axis indicates the position, the vertical axis indicates the TEC, ● indicates the TEC observed value, the solid line indicates the spatial distribution of the TEC observed value estimated by the waveform estimation device 300, and the dotted line indicates the spatial distribution of the TEC observed value. Indicates true value.
As can be understood from FIG. 5, the spatial distribution of TEC observation values estimated by waveform estimation apparatus 300 according to Embodiment 1 is a value close to the true value.
Therefore, it is possible to prevent the estimation accuracy of the spatial distribution of the ionospheric delay amount between the monitor stations 200 from deteriorating.

As described above, the waveform estimation apparatus 300 according to Embodiment 1 includes the ionospheric disturbance occurrence determination unit 2 that determines whether or not an ionospheric disturbance has occurred. The estimating unit 3 obtains the spatial distribution function of the TEC observation value, and when it is determined that an ionospheric disturbance has occurred, the ionospheric plane wave model estimating unit 4 obtains the spatial distribution function of the TEC observation value. Without increasing the number of monitor stations 200, it is possible to suppress deterioration in the accuracy of estimating the spatial distribution of the ionospheric delay amount between the monitor stations 200. FIG.

Further, when the waveform estimation apparatus 300 according to Embodiment 1 determines that no ionospheric disturbance has occurred, the ionospheric surface model estimating unit 3 performs The spatial distribution function of the TEC observation value is obtained, and the estimation of the spatial distribution of the ionospheric delay amount between the monitor stations 200 in normal times is not spoiled.

Furthermore, since the ionospheric plane wave model estimating unit 4 is provided with a cross-sectional projection unit 41, a spatial DFT unit 42, a filter unit 43, and a spatial IDFT unit 44, the cross-sectional projection unit 41 corresponds to each monitor station 200. The calculated TEC is converted to one-dimensional spatial coordinates by projecting it onto a first-order straight line parallel to the traveling direction of the TID. and the spatial IDFT unit 44 obtains the spatial distribution function of the TEC observation values. Therefore, when an ionospheric disturbance occurs in the ionosphere, the TEC observation values from the monitor station 200 for obtaining the spatial distribution function of the TEC observation values are obtained by TIDs with wavelengths shorter than the spacing of the monitor stations 200 can be detected because the density of the monitor stations 200 in the area of interest can be substantially increased.

In short, when an ionospheric disturbance occurs in which the state of the ionosphere, which is a continuum, is different from the normal state, the plane wave model estimating unit 4 utilizes the property that the ionosphere in which the ionospheric disturbance occurs has a plane wave structure to generate a continuum. Since the spatial distribution of the body is estimated, the accuracy of estimating the wave structure of the continuum is improved.

Furthermore, since the plane wave model estimating unit 4 obtains the spatial distribution function of the observed values by substantially increasing the observed values, there is no need to increase the number of observation points in the target region. Even in a target region in which it is impossible to estimate the spatial distribution of the continuum when a state different from the normal state occurs, it is possible to suppress a decrease in accuracy in estimating the spatial distribution of the continuum.

Embodiment 2.
A waveform estimation device 300A in the ionospheric delay amount estimation system according to Embodiment 2 will be described with reference to FIGS. 6 to 9. FIG.
Waveform estimating apparatus 300A according to Embodiment 2 further adds data holding unit 45, time DFT unit 46, and time IDFT unit 47 to ionospheric plane wave model estimating unit 4 in waveform estimating apparatus 300A according to Embodiment 1. This is the plane wave model estimating section 4A.
Other configuration requirements are the same or similar.
In FIG. 6, the same reference numerals as those shown in FIGS. 1 and 2 indicate the same or corresponding parts.

A data holding unit 45 holds the spatial distribution plane wave function of the TEC observation value obtained by the spatial DFT unit 42 .
That is, as shown in FIG. 7, the data holding unit 45 holds the spatial distribution plane wave function of the TEC observation value expressed on the spatial frequency axis determined by the spatial DFT unit 42 for multiple times.
In FIG. 7, the x-axis represents the spatial frequency, the y-axis represents the TEC observation value, the z-axis represents time, and the curves F1 to Ft are the spatial distribution plane wave functions of the TEC observation values obtained by the spatial DFT unit 42 at each time. is shown.

The temporal DFT unit 46 calculates the spatial distribution plane wave function of the TEC observation values obtained by the spatial DFT unit 42 and the spatial distribution plane wave function of the TEC observation values obtained by the plurality of spatial DFT units 42 held in the data holding unit 45. A nonuniform discrete Fourier transform is performed on each of them in the direction of the time axis to obtain the spatial distribution plane wave function of the two-dimensional TEC observation value and the moving speed of the TID.

The spatial distribution plane wave function of the two-dimensional TEC observation value obtained by performing the temporal DFT processing by the temporal DFT unit 46 on the spatial distribution plane wave function of the TEC observation value for multiple hours obtained by the spatial DFT unit 42 It is shown in FIG.
In FIG. 8, the xy coordinate system of the plane by the x-axis and the y-axis indicates two-dimensional axes of space frequency and time frequency, and the Z-axis indicates TEC.
In short, the temporal DFT unit 46 obtains a two-dimensional spatial distribution plane wave function of TEC observation values obtained by the spatial DFT unit 42 by adding a time axis to the spatial distribution plane wave function of TEC observation values.

Also, the moving speed of the TID can be treated as the moving speed of the plane wave, and the time DFT unit 46 obtains the moving speed of the TID from the temporal frequency/spatial frequency.
That is, the determination of the moving speed of the TID can be regarded as determination of the time frequency, and there are three specific methods for determining the moving speed of the TID as follows.
A method of uniformly adopting the maximum peak temporal frequency and extracting it along the spatial frequency axis.
How to determine the temporal frequency of the maximum peak for each spatial frequency.
A method of determining the temporal frequency by weighting multiple peaks for each spatial frequency.

The moving speed of the TID obtained by the time DFT unit 46 by any one of the three methods described above is combined with the spatial distribution function of the ionospheric delay amount obtained by the ionospheric delay amount calculating unit 5 and the ionospheric delay amount output unit 6 output from

On the other hand, the spatial distribution plane wave function of the two-dimensional TEC observation value obtained by the time DFT unit 46 is the TID component extracted by the filter unit 43 using a two-dimensional window function, and the noise is removed from the TEC observation value is the spatial distribution plane wave function of .
That is, the filter unit 43 performs filtering on the spatial distribution plane wave function of the two-dimensional TEC observation value using a two-dimensional window function, and removes the high-frequency component noise from the two-dimensional Remove from the spatial distribution plane wave function of the TEC observations.

As shown in the schematic diagram of FIG. 9, the filter processing by the filter unit 43 is performed by filtering the spatial distribution plane wave function of the two-dimensional TEC observation value using a two-dimensional window function, and filtering the filtered TEC observation value. Only the peak with the largest amplitude is extracted from the spatial distribution plane wave function.
In FIG. 9, the horizontal axis indicates the spatial frequency, the vertical axis indicates the temporal frequency, the hatched portion surrounded by the rectangle indicates the two-dimensional window function, and ● indicates the spatial distribution of the TEC observation value with the largest amplitude. shows the plane wave function.

The two-dimensional window function used in the filter unit 43 may extract wavelength components whose amplitude is equal to or greater than a threshold, or may operate like a low-pass filter to extract components whose spatial frequency is equal to or less than a threshold. .

The temporal IDFT unit 47 performs an inverse discrete Fourier transform along the time-frequency axis on the spatial distribution plane wave function of the two-dimensional TEC observation value from which the noise has been removed by the filter unit 43 .
The spatial IDFT unit 44 converts the spatial distribution plane wave function of the TEC observation value obtained by the temporal IDFT unit 47 into an inverse discrete Fourier transform, that is, a representation on a one-dimensional coordinate axis returning from the spatial frequency axis to the spatial axis, and the current time That is, a one-dimensional spatial distribution plane wave function, which is the spatial distribution plane wave function of the TEC observation value obtained by the spatial DFT unit 42 at the latest time, is obtained.

The ionospheric delay amount calculator 5 multiplies the spatial distribution function of the TEC observation value obtained by the ionospheric curved surface model estimating unit 3 or the spatial distribution function of the TEC observation value obtained by the ionospheric plane wave model estimating unit 4 by a coefficient to calculate the ionospheric Obtain the spatial distribution function of the amount of delay.
The spatial distribution function of the ionospheric delay calculated by the ionospheric delay calculating unit 5 is output from the ionospheric delay output unit 6 together with the moving speed of the TID calculated by the time DFT unit 46, as described above.

Waveform estimation apparatus 300A according to Embodiment 2 also has the same effect as waveform estimation apparatus 300 according to Embodiment 1. In addition, when it is determined that an ionospheric disturbance has occurred in the ionosphere, the TEC observation value Information on the moving speed of the TID can be added to the spatial distribution function, and even if the time interval provided by the spatial distribution function of the ionospheric delay amount to the user is lengthened, the estimation accuracy of the spatial distribution of the ionospheric delay amount between the monitor stations 200 is improved. can be suppressed.

Embodiment 3.
A waveform estimation device 300B in the ionospheric delay amount estimation system according to Embodiment 3 will be described with reference to FIG.
Waveform estimation apparatus 300B according to Embodiment 3 is composed of ionospheric plane wave model estimation unit 4 in waveform estimation apparatus 300 according to Embodiment 1, which is composed of cross-sectional projection unit 41, spatial DFT unit 42, filter unit 43, and spatial IDFT unit 44. The plane wave model estimating unit is a plurality of parallel processing plane wave model estimating units 4B (1) to 4B (M), and the TEC observation values obtained by the plurality of plane wave model estimating units 4B (1) to 4B (M) The ionospheric plane wave model estimating section 4B further includes a selecting section 48 for selecting a plausible TEC observation value spatial distribution function according to a selection condition set from the spatial distribution functions of .
Other configuration requirements are the same. Note that M is a natural number of 2 or more.
In FIG. 10, the same reference numerals as those shown in FIGS. 1 and 2 indicate the same or corresponding parts.

Plane wave model estimating units 4B(1) to 4B(M) include cross-sectional projection units 41(1) to 41(M), spatial DFT units 42(1) to 42(M), and filter units 43(1) to 43(1). 43(M) and spatial IDFT units 44(1) to 44(M). The plane wave model estimators 4B(1) to 4B(M) each constitute a waveform estimator.
The plane wave model estimating units 4B(1) to 4B(M) are set to different parameters, and obtain the spatial distribution function of the TEC observation values by the plane wave model based on the different parameters.

The parameters set in each of the plane wave model estimating units 4B(1) to 4B(M) are the traveling direction of the TID, the number of monitor stations 200 used for estimation, the size of the target area of the monitor stations 200 used for estimation, or the filter They are different parameters set by at least one condition of the window function used in the part 43 .

A selection unit 48 selects a plausible spatial distribution function of TEC observation values according to a selection condition set from the spatial distribution functions of TEC observation values obtained by the plurality of plane wave model estimating units 4B(1) to 4B(M).
The selection condition set in the selection unit 48 is the amplitude of the spatial distribution plane wave function of the TEC observation value obtained by the spatial DFT units 42(1) to 42(M) in the plane wave model estimation units 4B(1) to 4B(M). The spatial distribution function of the TEC observation value obtained by the plane wave model estimator 4B having the largest amplitude is selected as the plausible spatial distribution function of the TEC observation value.

In addition, the selection condition set in the selection unit 48 is the TEC observation value of the monitor station not used for waveform estimation, and the TEC observation obtained by the plane wave model estimation unit 4B that minimizes the error with respect to the TEC observation value. The spatial distribution function of the values may be selected as the spatial distribution function of the plausible TEC observations.
Note that the selection unit 48 is not limited to one selection unit, and may be a plurality of selection units.

In the waveform estimation device 300B according to Embodiment 3, for example, when the direction of travel of the TID is unknown, the parameter set in each of the plane wave model estimation units 4B(1) to 4B(M) is the direction of travel of the TID, and the cross section The traveling directions of the TID at different angles are virtually given as parameters to each of the upper projection parts 41(1) to 41(M). Each of the cross-sectional projection units 41(1) to 41(M) performs coordinate conversion processing to one-dimensional space coordinates projected onto a primary straight line parallel to the traveling direction of different TIDs.

The selection unit 48 selects a plausible spatial distribution function of TEC observation values according to selection conditions set from the spatial distribution functions of TEC observation values obtained by the plurality of plane wave model estimation units 4B(1) to 4B(M).
Therefore, even if the direction of travel of the TID is unknown, a plausible spatial distribution function of TEC observations can be selected.

When the TID traveling direction is known, the known TID traveling direction is given as a parameter to each of the cross-sectional projection units 41(1) to 41(M). Coordinate transformation processing to one-dimensional spatial coordinates projected onto a parallel primary straight line is performed.

Waveform estimation apparatus 300B according to Embodiment 3 also has the same effects as waveform estimation apparatus 300 according to Embodiment 1. In addition, a plurality of plane wave model estimation units 4B (1 ) ~ 4B (M) It is possible to select a plausible spatial distribution function of the TEC observation value by the selection condition set from the spatial distribution function of the TEC observation value obtained by 4B (M), and even when the parameters are unknown, the plane wave model We obtain the spatial distribution function of the plausible TEC observations by
For example, even if the direction of travel of the TID is unknown, a plausible spatial distribution function of the TEC observations by the plane wave model can be obtained.

Embodiment 4.
A waveform estimation device 300C in the ionospheric delay amount estimation system according to Embodiment 4 will be described with reference to FIG.
A waveform estimation apparatus 300C according to the fourth embodiment is provided with an ionospheric disturbance occurrence determination section 2A instead of the ionospheric disturbance occurrence determination section 2 in the waveform estimation apparatus 300 according to the first embodiment.

That is, the ionospheric disturbance occurrence determination unit 2 in the waveform estimation device 300 according to Embodiment 1 determines whether an ionospheric disturbance has occurred based on the TEC calculated for each monitor station 200 by the ionospheric electron number calculation unit 1. is determined, and the ionospheric curved surface model estimating unit 3 or the ionospheric plane wave model estimating unit 4 obtains the spatial distribution function of the TEC observation value.

On the other hand, the ionospheric disturbance occurrence determination unit 2A in the waveform estimation device 300C according to the fourth embodiment determines whether the spatial distribution plane wave function of the TEC observation value in the ionospheric plane wave model estimation unit 4 matches the plane wave model. The ionospheric delay amount calculator 5 calculates the spatial distribution of the TEC observation values obtained by the ionospheric curved surface model estimator 3 based on the presence or absence of the ionospheric disturbance generated by the ionospheric disturbance occurrence determiner 2A. The spatial distribution function of the ionospheric delay amount is obtained by selecting the function or the spatial distribution function of the TEC observation value obtained by the ionospheric plane wave model estimator 4 .
Other configuration requirements are the same.
In FIG. 11, the same reference numerals as those shown in FIGS. 1 and 2 indicate the same or corresponding parts.

The ionospheric curved surface model estimating unit 3 and the ionospheric plane wave model estimating unit 4 each convert the TEC calculated corresponding to each monitor station 200 by the ionospheric electron number calculating unit 1 into the ionospheric curved surface model as described in the first embodiment. An estimator 3 obtains a spatial distribution function of TEC observation values based on a curved surface model, and an ionospheric plane wave model estimator 4 obtains a spatial distribution function of TEC observation values based on a plane wave model.

The ionospheric disturbance occurrence determining unit 2A determines whether or not an ionospheric disturbance has occurred based on whether the spatial distribution plane wave function of the TEC observation value in the ionospheric plane wave model estimating unit 4 conforms to the plane wave model.
When the magnitude of the amplitude of the spatial distribution plane wave function of the TEC observation value obtained by the spatial DFT unit 42 is greater than the threshold, the ionospheric disturbance occurrence determination unit 2A determines whether or not the ionospheric disturbance has occurred. It is determined that a disturbance has occurred. Alternatively, when the error of the spatial distribution plane wave function of the TEC observation value obtained by the spatial DFT unit 42 with respect to the TEC observation value of the monitor station not used for waveform estimation is larger than the threshold value, an ionospheric disturbance occurs in the ionosphere in the target area. It is determined that

When the ionospheric disturbance occurrence determining unit 2A determines that no ionospheric disturbance has occurred, the ionospheric delay amount calculating unit 5 multiplies the spatial distribution function of the TEC observation value obtained by the ionospheric curved surface model estimating unit 3 by a coefficient to obtain an ionospheric delay. Find the spatial distribution function of a quantity.
On the other hand, when the ionospheric disturbance occurrence determining unit 2A determines that an ionospheric disturbance has occurred, the ionospheric delay amount calculating unit 5 multiplies the spatial distribution function of the TEC observation value obtained by the ionospheric plane wave model estimating unit 4 by a coefficient. Obtain the spatial distribution function of the ionospheric delay.

Waveform estimation apparatus 300C according to Embodiment 4 also has the same effect as waveform estimation apparatus 300 according to Embodiment 1. FIG.
It should be noted that waveform estimation apparatuses 300A to 300C according to Embodiments 2 to 4 can also be configured with a general computer in the case of software configuration, similarly to waveform estimation apparatus 300 according to Embodiment 1. FIG.

Waveform estimation apparatuses 300, 300A to 300C according to Embodiments 1 to 4 are suitable for use in high-accuracy satellite positioning systems.
A satellite positioning terminal is further provided in the ionospheric delay amount estimation system according to Embodiments 1 to 4, and the spatial distribution function of the ionospheric delay amount obtained by the waveform estimation devices 300 and 300A to 300C is distributed to the positioning terminal, By estimating and correcting the ionospheric delay at the position of the positioning terminal, it can be used as a high-precision satellite positioning system that can be used even when ionospheric disturbances occur.

By applying the waveform estimation apparatuses 300 and 300A to 300C according to Embodiments 1 to 4 to a high-accuracy satellite positioning system, it is possible to suppress a decrease in positioning accuracy when an ionospheric disturbance occurs in the ionosphere.

Embodiment 5.
A sea surface current velocity estimation system according to Embodiment 5 will be described with reference to FIGS. 12 and 13. FIG.
The sea surface current velocity estimation system according to Embodiment 5 irradiates a fan-shaped radar coverage area on the sea surface with radio waves (electromagnetic waves), and uses reflected radio waves from a plurality of observation points on the sea surface to determine the state of the sea surface. This is an example of application to a marine radar device that measures the current velocity on the sea surface.
As a marine radar device, generally, an antenna, a transmitter/receiver, and a signal processor are used to measure the current velocity on the sea surface by radio waves.

A sea surface current velocity estimation system according to Embodiment 5 includes, as a tsunami estimation device, a waveform estimation device that obtains a spatial distribution function of observed values, which are current velocities at observation points, as a tsunami estimation device that outputs that a tsunami has occurred.
The tsunami estimation device in the sea surface current velocity estimation system according to the fifth embodiment is designed to estimate the current velocity and The discharge, which is the product of the water depth at the observation point on the sea surface, is a wave structure, and this wave structure is a plane wave structure like the propagating ionospheric disturbance (TID) that occurs in the ionosphere.
A waveform estimating device 300D, which is a tsunami estimating device according to the fifth embodiment, includes a tsunami plane wave model estimating unit 4D having the same configuration as the ionospheric plane wave model estimating unit 4 in the waveform estimating device 300 according to the first embodiment.

A sea surface current velocity estimation system according to Embodiment 5 in which the waveform estimation device 4D is applied to a tsunami estimation device will be described below.
The sea surface current velocity estimation system according to Embodiment 5 includes a transmitter/receiver unit 100D and a receiving point 200D in a marine radar apparatus that receives radio waves reflected from N observation points (N is a natural number of 2 or more) on the sea surface. (1) to 200D(N) and a waveform estimation device 300D.
Since the plurality of receiving points 200D(1) to 200D(N) are receiving points of the same configuration for receiving radio waves reflected from different observation points on the sea surface, in order to avoid complication of the explanation, the following ( ) The subscript of is omitted, and the explanation is given as a receiving point 200D.

The transceiver unit 100D is a part of a transceiver used in a general marine radar system.
The transmitter/receiver unit 100D receives the radio waves reflected from the observation point for each cell, which is the resolution processing within the radar coverage area, which is the target area, shown in FIG.
In FIG. 13, the sector indicates the radar coverage, the mesh within the radar coverage indicates the resolution cell, the area indicated by the solid-line square frame indicates the target area to be processed by the waveform estimation device 300D, and the ● indicates the sector. Sea surface observation points in the radar coverage are shown.

Multiple receiving points 200D are part of a typical marine radar system transceiver.
A plurality of receiving points 200D each correspond to a plurality of observation points based on accession signals (radio waves) corresponding to a plurality of observation points in the radio waves received from the transmitter/receiver unit 100D. Generate observation data such as

The waveform estimation device 300D accumulates observation data from a plurality of reception points 200D, and obtains a spatial distribution function of current velocity on the sea surface by a plane wave model from the accumulated observation data.
As shown in FIG. 10, the waveform estimation device 300D is a tsunami estimation device that includes a surface current velocity calculation unit 1D, a tsunami plane wave model estimation unit 4D, and a sea surface current velocity output unit 6D.

The surface current velocity calculator 1D is part of a signal processor of a general marine radar device.
The surface flow velocity calculator 1D calculates the flow velocity in the line-of-sight direction at a plurality of observation points based on observation data from a plurality of reception points 200D.

The tsunami plane wave model estimation unit 4D is based on the position information (coordinates) of each observation point obtained from each reception point 200D and the flow velocity in the line-of-sight direction calculated corresponding to each reception point 200D by the surface flow velocity calculation unit 1D. Then, the spatial distribution of the observed velocity is estimated by the plane wave model, the analysis is performed by the plane wave model, and the spatial distribution function of the observed velocity by the plane wave model is obtained.
The tsunami plane wave model estimator 4D is a waveform estimator that outputs the spatial distribution of current velocity observation values as a function of the plane wave.

The tsunami plane wave model estimation unit 4D includes a cross-sectional projection unit 41D, a spatial DFT unit 42D, a filter unit 43D, and a spatial IDFT unit 44D.
The cross-sectional projection unit 41D uses the position information (coordinates) of each observation point obtained from each reception point 200D and the flow velocity in the line-of-sight direction calculated corresponding to each observation point by the surface flow velocity calculation unit 1D, and uses each reception The flow velocity in the line-of-sight direction calculated corresponding to each observation point by the point 200D is calculated on a first-order straight line parallel to the line-of-sight direction using the property that the spatial distribution of the flow velocity on the sea surface of the tsunami has a propagating plane wave structure. Coordinate conversion processing to one-dimensional spatial coordinates projected onto is performed.

The coordinate conversion processing performed by the cross-sectional projection unit 41D will be described with reference to FIG.
In FIG. 13, the x-axis and y-axis indicate a planar xy coordinate system, and the x'-axis and y'-axis indicate a planar coordinate system consisting of the x-axis and the y-axis. shows the rotated x'-y' coordinate system.
The xy coordinate system is a planar coordinate system obtained by projecting the spatial coordinates onto a plane. The x'-y' coordinate system is a coordinate system rotated by an angle φ' of the direction of travel of the TID with respect to the xy coordinate system.
Also, as an example, each observation point that receives the reflected radio wave from each reception point 200D is indicated by ●.

The cross-sectional projection unit 41D observes the flow velocity in the line-of-sight direction calculated corresponding to each observation point by each receiving point 200D on a linear straight line parallel to the line-of-sight direction, which is a parameter, that is, on the x' axis. Coordinate transformation processing to one-dimensional spatial coordinates for projecting point coordinates and flow velocity vectors is performed.

The spatial DFT unit 42D performs a non-uniform dispersion Fourier transform (DFT) on the flow velocity observation value, which is the flow velocity vector in the one-dimensional space coordinate coordinate-transformed by the cross-sectional projection unit 41D, to obtain a spatial distribution plane wave of the flow velocity observation value. Find a function.
That is, the spatial DFT unit 42D transforms the flow velocity observation value in one-dimensional spatial coordinates, which has undergone coordinate transformation processing by the cross-sectional projection unit 41D, from the spatial axis to the spatial frequency axis by the nonuniform dispersion Fourier transform, and converts the flow velocity observation value. Find the spatial distribution plane wave function.

The filter unit 43D uses a low-pass filter that removes the noise component serving as a window function from the spatial distribution plane wave function of the flow velocity observation value on the spatial frequency axis obtained by the spatial DFT unit 42D to remove noise from the flow velocity observation value space. Find the distribution plane wave function.

The spatial IDFT section 44D performs an inverse discrete Fourier transform on the spatial distribution plane wave function of the flow velocity observation value from which noise has been removed by the filter section 43D, and obtains the spatial distribution function of the flow velocity observation value.
That is, the spatial IDFT unit 44D converts the spatial distribution plane wave function of the flow velocity observation value from which noise has been removed by the filter unit 43D into a representation on the one-dimensional coordinate axis, and the flow velocity from which the noise has been removed by the filter unit 43 on the one-dimensional coordinate axis. Observed values are calculated for each observation point obtained from each receiving point 200D by the surface flow velocity calculation unit 1D before being projected by the cross-sectional projection unit 41D. Find the distribution function.

The sea surface current velocity output unit 6D outputs the spatial distribution function of the current velocity obtained by the tsunami plane wave model estimation unit 4D.
The spatial distribution function of the current velocity output from the sea surface current velocity output unit 6D is displayed as the current velocity on display means such as a monitor.
The user can recognize whether or not a tsunami is occurring by viewing the flow velocity displayed by the display means.

When the tsunami estimation device, which is the waveform estimation device 300D according to the fifth embodiment, has a software configuration, the surface current velocity calculation unit 1D, the tsunami plane wave model estimation unit 4D, and the sea surface current velocity output unit 6D are the same as those according to the first embodiment. Similar to the waveform estimation device 300, it is composed of a general computer.

Note that the tsunami estimation apparatus, which is the waveform estimation apparatus 300D according to Embodiment 5, uses the flow velocities in the line-of-sight direction corresponding to the plurality of observation points from the plurality of reception points 200D to calculate the spatial distribution function of the flow velocities in the line-of-sight direction. However, the spatial distribution function of the flow velocity in the line-of-sight direction may be obtained using the flow rate in the line-of-sight direction corresponding to the plurality of observation points from the plurality of reception points 200D that indirectly indicate the flow velocity.
That is, since the flow rate is the product of the flow velocity and the water depth at the sensor observation point, it indirectly indicates the flow rate.

Waveform estimating apparatus 300D according to Embodiment 5 configured in this manner, when a tsunami occurs, does not increase the number of receiving points 200D that observe observation points, and can The estimation accuracy of the spatial distribution function of the velocity vector can be improved.

It should be noted that it is possible to freely combine each embodiment, modify any component of each embodiment, or omit any component from each embodiment.

A waveform estimation device according to the present disclosure is suitable for use in an ionospheric delay amount estimation system in a high-precision satellite positioning system and a sea surface current velocity estimation system in an ocean radar device.

100 positioning satellite, 100D transceiver unit, 200(1) to 200(N) monitor station, 200D receiving point, 300, 300A to 300D waveform estimation device, 1 ionospheric electron number calculation unit, 1D surface current speed calculation unit, 2, 2A Ionospheric disturbance occurrence determination unit, 3 ionospheric curved surface model estimation unit, 4, 4A to 4C ionosphere plane wave model estimation unit, 4D tsunami plane wave model estimation unit, 41, 41(1) to 41(M), 41D section projection unit, 42 , 42(1) to 42(M), 42D spatial DFT section, 43, 43(1) to 43(M), 43D filter section, 44, 44(1) to 44(M), 44D spatial IDFT section, 45 Data holding unit 46 Time DFT unit 47 Time IDFT unit 4B(1) to 4B(M) Plane wave model estimation unit 48 Selection unit 5, 5A Ionosphere delay amount calculation unit 6 Ionosphere delay amount output unit 6D Sea Surface velocity output section.

Claims (5)

Each of the observed values of the continuum at a plurality of observation points for a continuum with a spatio-temporal spread that has the property of becoming a plane wave structure when a state different from the normal state occurs is transmitted to each of the plurality of observation points. a cross-sectional projection unit that performs coordinate conversion processing into one-dimensional spatial coordinates that are projected onto a first-order straight line parallel to the traveling direction of radio waves;
a spatial DFT unit for obtaining a spatial distribution plane wave function of the continuum by performing a discrete Fourier transform on the observed values of the continuum at one-dimensional spatial coordinates coordinate-transformed by the cross-sectional projection unit;
a filter unit that obtains a spatial distribution plane wave function of the continuum obtained by removing noise from the spatial distribution plane wave function of the continuum using a window function from the spatial distribution plane wave function of the continuum obtained by the spatial DFT unit;
a waveform estimating unit having a waveform estimating unit having a spatial IDFT unit that performs an inverse discrete Fourier transform on the spatial distribution plane wave function of the continuum obtained by the filter unit and obtains the spatial distribution function of the continuum. . a data holding unit that holds the spatial distribution plane wave function of the continuum obtained by the spatial DFT unit;
a time DFT unit for obtaining a two-dimensional spatial distribution plane wave function for the continuum by performing a Fourier transform in the time axis direction on the spatial distribution plane wave function for the continuum at a plurality of times held in the data holding unit;
a time IDFT unit that performs an inverse discrete Fourier transform along the time-frequency axis on the two-dimensional spatial distribution plane wave function of the continuum obtained by the filtering unit to obtain the spatial distribution function of the continuum;
further comprising
The spatial distribution plane wave function of the continuum obtained by the spatial DFT unit used in the filter unit is a two-dimensional spatial distribution plane wave function of the continuum obtained by the time DFT unit,
The window function in the filter unit is a two-dimensional window function,
The denoised continuum spatial distribution plane wave function obtained by the filter unit used in the spatial IDFT unit is the spatial distribution function of the continuum obtained by the temporal IDFT unit,
The waveform estimation device according to claim 1 . each having a plurality of waveform estimation units that are processed in parallel using different parameters;
a selection unit that selects a plausible spatial distribution plane function of the continuum according to a selection condition set from the spatial distribution plane functions of the continuum obtained by the plurality of waveform estimating units;
The waveform estimation device according to claim 1, comprising : The observed value of the continuum for which the coordinate conversion process is performed by the cross-sectional projection unit is the flow velocity in the line-of-sight direction of the sea surface,
The cross-sectional projection unit performs coordinate conversion processing to one-dimensional space coordinates by projecting the coordinates of the observation point and the flow velocity vector of the flow velocity onto a primary straight line parallel to the direction of the line of sight.
The waveform estimation device according to claim 1, which is a tsunami estimation device. A waveform estimating device according to any one of claims 1 to 3 , and a plurality of monitor stations that receive positioning signals from positioning satellites and output observation data of a plurality of frequencies to the waveform estimating device. system for estimating ionospheric delay.

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