Patent Description:
Some wind speed prediction devices that predict a wind speed in an observation region include a wind speed prediction device (hereinafter referred to as a "conventional wind speed prediction device") that predicts a wind speed in an observation region by simulating the wind speed using a weather model (see Patent Literature <NUM>). The simulation of the wind speed is three-dimensional calculation processing.

Patent Literature <NUM> discloses a method for determining the flow of a fluid in a volume of interest, including steps of remotely measuring, at a plurality of measurement points distributed along at least three axes having different spatial orientations passing through the volume of interest, the radial velocity of the fluid in the vicinity of the measurement points, and for calculating the velocity of the fluid at a plurality of calculation points distributed in a grid in the volume of interest, wherein the calculation of the velocity of the fluid includes the use of a mechanical behavior model of the fluid.

Non-Patent Literature <NUM> briefly reviews procedures employed to retrieve vector wind information from single-Doppler radar observations. In particular, those procedures implying a linearity hypothesis for the wind field are shown to be particular cases of a method termed VVP (Volume Velocity Processing). This method, which makes full use of radar velocity data filling a volume, is first tested on simulated observations in order to assess its accuracy, then applied to actual data and shown to yield unbiased parameters of the horizontal vector wind field, as well as an estimate of the hydrometeor fall velocity and several control parameters.

In Non-Patent Literature <NUM>, first, a Doppler velocity dealiasing technique is developed for difficult aliasing problems. A dealiasing algorithm is described that automatically processes one radial at a time by comparing the radial with a previous or surrounding radial. This technique has worked reliably on numerous Doppler radar datasets for severe storm environments observed by an X-band Doppler radar. Second, an analysis technique for the retrieval of the mesoscale (<NUM> -<NUM>) wind field, such as the VVP ( Volume Velocity Processing ), is extended. This extended VVP analysis has adaptability for a nonlinear wind field better than the original method. This algorithm can compute both estimates and residual variances simultaneously for several analysis volumes, and select the optimal horizontal wind and its divergence which minimizes the residual variance. The horizontal wind field estimated has a larger scale of the observation resolution and this estimate aids in tracking the entire movement of rainfall distribution.

Patent Literature <NUM> discloses a system and method for determining wind velocity. The LIDAR <NUM> transmits a plurality of laser pulses. The paths of the laser pulses surround a center line that does not coincide with a vertical axis intersecting the LIDAR , i.e., an off-vertical scan. Each laser pulse reflects off particles in the air at a given location. This location is the intersection of the path of each LIDAR pulse and the target altitude. The target altitude is the altitude at which the wind velocity is to be determined. The reflected pulses are received by the LIDAR. The invention groups the received LIDAR pulses according to the altitude at which they were reflected, as opposed to the distance each pulse travels. Grouping the received pulses in this manner enables the invention to perform an off-vertical scan that accurately determines the wind velocity at a target altitude. The received laser pulses have an associated Doppler shift. The Doppler shift is a measure of the relative radial wind velocity at the target location. The invention measures the Doppler shift from a plurality of received laser pulses reflected from the target altitude. These measurements enable the invention to determine the wind velocity at the target location.

The conventional wind speed prediction device disclosed in Patent Literature <NUM> performs three-dimensional calculation processing, and thus has a problem that a calculation load may increase.

The present disclosure has been made to solve the above problems, and an object thereof is to obtain a wind speed prediction device and a wind speed prediction method capable of predicting a wind speed without performing three-dimensional calculation processing.

A wind speed prediction device according to the present disclosure is set forth in claim <NUM>. A wind speed prediction method according to the present disclosure is set forth in claim <NUM>.

According to the present disclosure, a wind speed can be predicted without performing three-dimensional calculation processing.

Hereinafter, in order to describe the present disclosure in more detail, modes for carrying out the present disclosure will be described with reference to the accompanying drawings.

<FIG> is a configuration diagram illustrating a radar device <NUM> including a wind speed prediction device <NUM> according to a first embodiment.

The radar device <NUM> illustrated in <FIG> includes a beam transmitting and receiving unit <NUM> and a wind speed prediction device <NUM>.

<FIG> is an explanatory diagram illustrating a plurality of beams emitted to space from the beam transmitting and receiving unit <NUM>. In the example of <FIG>, the observation region is present in the space. The observation region is, for example, a flight area in which a flying object is scheduled to fly. The flying object is, for example, a drone or a helicopter.

<FIG> is an explanatory diagram illustrating a plurality of beams in a case where the position of the flight area is directly above the beam transmitting and receiving unit <NUM> in the vertical direction.

<FIG> is an explanatory diagram illustrating a plurality of beams in a case where the position of the flight area is deviated from directly above the beam transmitting and receiving unit <NUM> in the vertical direction.

The beam transmitting and receiving unit <NUM> includes, for example, a beam generating unit, a beam transmitter, a radiation direction switching unit, an antenna, and a beam receiver. In <FIG>, notations of the beam generating unit, the beam transmitter, the radiation direction switching unit, the antenna, and the beam receiver are omitted.

As illustrated in <FIG>, the beam transmitting and receiving unit <NUM> emits each of a plurality of beams having mutually different elevation angles θn (n = <NUM>,. , N), which are angles formed by the line-of-sight direction and the horizontal direction, into space. N is an integer of <NUM> or more.

That is, as illustrated in <FIG>, when the flight area is present directly above in the vertical direction, the beam transmitting and receiving unit <NUM> emits beams in different directions at respective elevation angles θn by performing beam scanning at the respective elevation angles θn.

In <FIG>, N = <NUM>, and each of the beam with the elevation angle θ<NUM>, the beam with the elevation angle θ<NUM>, and the beam with the elevation angle θ<NUM> is emitted from the beam transmitting and receiving unit <NUM> to space. In <FIG>, beams are emitted in four directions at the respective elevation angles θn. In <FIG>, black circles indicate observation points of the wind speed.

Further, as illustrated in <FIG>, when the position of the flight area is deviated from directly above in the vertical direction, the beam transmitting and receiving unit <NUM> emits beams at respective elevation angles θn while switching the elevation angles θn.

In <FIG>, N = <NUM>, and beams of elevation angles θ<NUM> to θ<NUM> are emitted from the beam transmitting and receiving unit <NUM> to space. For simplification of the drawing, only the elevation angles θ<NUM> to θ<NUM> are illustrated in <FIG>, and the illustration of the elevation angles θ<NUM> to θ<NUM> is omitted. In <FIG>, a beam is emitted in one direction at each elevation angle θn. In <FIG>, black circles indicate observation points of the wind speed.

Each of <FIG> illustrates an example of obtaining wind speed distributions in three two-dimensional planes. However, this is merely an example, and wind speed distributions in one or two two-dimensional planes may be obtained, or wind speed distributions in four or more two-dimensional planes may be obtained.

As the beam emitted from the beam transmitting and receiving unit <NUM>, for example, in addition to continuous wave (CW) pulsed light, frequency-modulated pulsed light can be used.

The beam transmitting and receiving unit <NUM> receives each beam scattered in space as a scattering signal.

The beam transmitting and receiving unit <NUM> converts each scattering signal from an analog signal to a digital signal, and outputs the digital signal to the wind speed prediction device <NUM>.

Further, the beam transmitting and receiving unit <NUM> outputs angle information indicating the elevation angle θn of each beam emitted to space to the wind speed prediction device <NUM>.

In the radar device <NUM> illustrated in <FIG>, it is assumed that the beam transmitting and receiving unit <NUM> includes a beam generating unit, a beam transmitter, a radiation direction switching unit, an antenna, and a beam receiver. However, the beam transmitting and receiving unit <NUM> is only required to emit each of a plurality of beams having different elevation angles θn into space and receive each beam scattered in the space as a scattering signal, and may have any configuration.

<FIG> is a configuration diagram illustrating the wind speed prediction device <NUM> according to the first embodiment.

<FIG> is a hardware configuration diagram illustrating hardware of the wind speed prediction device <NUM> according to the first embodiment.

The wind speed prediction device <NUM> illustrated in <FIG> includes a scattering signal acquiring unit <NUM>, a Doppler frequency calculating unit <NUM>, a first wind speed distribution estimating unit <NUM>, a second wind speed distribution estimating unit <NUM>, and a wind speed prediction unit <NUM>.

The scattering signal acquiring unit <NUM> is implemented by, for example, a scattering signal acquiring circuit <NUM> illustrated in <FIG>.

The scattering signal acquiring unit <NUM> acquires each of digital signals sθn,j(t) from the beam transmitting and receiving unit <NUM> as each of scattering signals after being scattered in space. j = <NUM>,. j is the scan number of beam scanning at the elevation angle θn. In the example of <FIG>, since beams are emitted in four directions at each elevation angle θn, J = <NUM>. In the example of <FIG>, since the beam is emitted in one direction at each elevation angle θn, J = <NUM>. t is a variable indicating time.

Further, the scattering signal acquiring unit <NUM> acquires the angle information indicating the elevation angle θn of each beam emitted into space by the beam transmitting and receiving unit <NUM>.

The scattering signal acquiring unit <NUM> outputs each of the digital signals sθn,j(t) and the angle information to the Doppler frequency calculating unit <NUM>.

The Doppler frequency calculating unit <NUM> is implemented by, for example, a Doppler frequency calculating circuit <NUM> illustrated in <FIG>.

The Doppler frequency calculating unit <NUM> acquires each of the digital signals sθn,j(t) and the angle information from the scattering signal acquiring unit <NUM>.

Before performing fast Fourier transformation (FFT) on each digital signal sθn,j(t) in the hit direction, the Doppler frequency calculating unit <NUM> sets a range bin width as the distance resolution of each digital signal sθn,j(t) according to the elevation angle θn indicated by the angle information. That is, the Doppler frequency calculating unit <NUM> sets an FFT length Lθn corresponding to the range bin width.

The FFT length Lθn is set shorter as the elevation angle θn of the beam emitted to space is wider, and is set longer as the elevation angle θn of the beam emitted to the space is narrower.

In the example of <FIG>, the FFT length Lθ1 of the digital signal sθ1,j(t) corresponding to the beam at the elevation angle θ<NUM> is longer than the FFT length Lθ2 of the digital signal sθ2,j(t) corresponding to the beam at the elevation angle θ<NUM>, and the FFT length Lθ2 of the digital signal sθ2(t) corresponding to the beam at the elevation angle θ<NUM> is longer than the FFT length Lθ3 of the digital signal sθ3,j(t) corresponding to the beam at the elevation angle θ<NUM>.

The Doppler frequency calculating unit <NUM> converts each of the digital signals sθn,j(t) into frequency domain signals rθn,j(f) by performing FFT on the digital signals sθn,j(t) acquired by the scattering signal acquiring unit <NUM> in the hit direction. f is a variable indicating a frequency.

The Doppler frequency calculating unit <NUM> calculates the respective Doppler frequencies dpfθn,j,Rbm in a plurality of range bins Rb<NUM> to RbM from the signals rθn,j(f) in the frequency domain. m = <NUM>,. , M, and M is an integer of <NUM> or more.

<FIG> illustrates an example of obtaining wind speed distributions in three two-dimensional planes. As illustrated in <FIG>, in a case of obtaining wind speed distributions in three two-dimensional planes, the Doppler frequency calculating unit <NUM> calculates the Doppler frequencies dpfθn,j,Rbm in the range bins Rb<NUM>, Rb<NUM>, and Rb<NUM> from the signals rθn,j(f) in the frequency domain.

In the wind speed prediction device <NUM> illustrated in <FIG>, it is assumed that M is an integer of <NUM> or more. Here, M is not limited to an integer of <NUM> or more, and M = <NUM> may be set.

When M = <NUM>, the Doppler frequency calculating unit <NUM> calculates only the Doppler frequency dpfθn,j,Rb1 of one range bin Rb<NUM> including the observation region from the frequency domain signal rθn,j(f).

The Doppler frequency calculating unit <NUM> outputs the Doppler frequencies dpfθn,j,Rbm of the respective range bins Rbm to the first wind speed distribution estimating unit <NUM>.

The first wind speed distribution estimating unit <NUM> is implemented by, for example, a first wind speed distribution estimating circuit <NUM> illustrated in <FIG>.

The first wind speed distribution estimating unit <NUM> estimates a wind speed distribution uRbm(x, y) in a two-dimensional plane corresponding to each range bin Rbm using a volume velocity processing (VVP) method from a plurality of Doppler frequencies dpfθ1,j,Rbm to dpfθN,j,Rbm in each range bin Rbm calculated by the Doppler frequency calculating unit <NUM>.

When M is <NUM>, the first wind speed distribution estimating unit <NUM> estimates the wind speed distribution uRb1(x, y) in the two-dimensional plane corresponding to the range bin Rb<NUM> as the two-dimensional plane including the observation region, and outputs the wind speed distribution uRb1(x, y) in the two-dimensional plane to the wind speed prediction unit <NUM>.

When M is <NUM> or more, the first wind speed distribution estimating unit <NUM> outputs the wind speed distribution uRbm(x, y) in the two-dimensional plane corresponding to each range bin Rbm to the second wind speed distribution estimating unit <NUM>.

The second wind speed distribution estimating unit <NUM> is implemented by, for example, a second wind speed distribution estimating circuit <NUM> illustrated in <FIG>.

The second wind speed distribution estimating unit <NUM> estimates a wind speed distribution uRbm'(x, y) in a two-dimensional plane between a plurality of two-dimensional planes from the wind speed distributions uRb1(x, y) to uRbM(x, y) in the plurality of two-dimensional planes estimated by the first wind speed distribution estimating unit <NUM>. For example, the wind speed distribution uRb1'(x, y) in the two-dimensional plane is a wind speed distribution in the two-dimensional plane between the two-dimensional plane corresponding to the range bin Rb<NUM> and the two-dimensional plane corresponding to the range bin Rb<NUM>. The wind speed distribution uRb2'(x, y) in the two-dimensional plane is a wind speed distribution in the two-dimensional plane between the two-dimensional plane corresponding to the range bin Rb<NUM> and the two-dimensional plane corresponding to the range bin Rb<NUM>.

The second wind speed distribution estimating unit <NUM> outputs the wind speed distributions uRb1'(x, y) to uRbM-<NUM>'(x, y) in the two-dimensional plane between the plurality of two-dimensional planes to the wind speed prediction unit <NUM>.

The wind speed prediction unit <NUM> is implemented by, for example, a wind speed prediction circuit <NUM> illustrated in <FIG>.

When M is <NUM>, the wind speed prediction unit <NUM> predicts a wind speed u(t) in the observation region from the wind speed distribution uRb1(x, y) in the two-dimensional plane estimated by the first wind speed distribution estimating unit <NUM> using the two-dimensional Navier-Stokes equation (hereinafter referred to as a "two-dimensional N-S equation"). The observation region is, for example, an area including a flight area in which the flying object is scheduled to fly.

When M is <NUM> or more, the wind speed prediction unit <NUM> selects the wind speed distribution in the two-dimensional plane including the flight area as the observation region from the wind speed distributions uRb1(x, y) to uRbM(x, y) in the plurality of two-dimensional planes estimated by the first wind speed distribution estimating unit <NUM> and the wind speed distributions uRb1'(x, y) to uRbM-<NUM>'(x, y) in the two-dimensional plane estimated by the second wind speed distribution estimating unit <NUM>.

The wind speed prediction unit <NUM> predicts the wind speed u(t) in the flight area from the wind speed distribution in the selected two-dimensional plane using the two-dimensional N-S equation.

In <FIG>, it is assumed that each of the scattering signal acquiring unit <NUM>, the Doppler frequency calculating unit <NUM>, the first wind speed distribution estimating unit <NUM>, the second wind speed distribution estimating unit <NUM>, and the wind speed prediction unit <NUM>, which are components of the wind speed prediction device <NUM>, is implemented by dedicated hardware as illustrated in <FIG>. That is, it is assumed that the wind speed prediction device <NUM> is implemented by the scattering signal acquiring circuit <NUM>, the Doppler frequency calculating circuit <NUM>, the first wind speed distribution estimating circuit <NUM>, the second wind speed distribution estimating circuit <NUM>, and the wind speed prediction circuit <NUM>.

Each of the scattering signal acquiring circuit <NUM>, the Doppler frequency calculating circuit <NUM>, the first wind speed distribution estimating circuit <NUM>, the second wind speed distribution estimating circuit <NUM>, and the wind speed prediction circuit <NUM> corresponds to, for example, a single circuit, a composite circuit, a programmed processor, a parallel-programmed processor, an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or a combination thereof.

The components of the wind speed prediction device <NUM> are not limited to those implemented by dedicated hardware, and the wind speed prediction device <NUM> may be implemented by software, firmware, or a combination of software and firmware.

Software or firmware is stored in a memory of the computer as a program. The computer means hardware that executes a program, and corresponds to, for example, a central processing unit (CPU), a central processing device, a processing device, an arithmetic device, a microprocessor, a microcomputer, a processor, or a digital signal processor (DSP).

<FIG> is a hardware configuration diagram of a computer in a case where the wind speed prediction device <NUM> is implemented by software, firmware, or the like.

In a case where the wind speed prediction device <NUM> is implemented by software, firmware, or the like, a program for causing a computer to execute each processing procedure performed in the scattering signal acquiring unit <NUM>, the Doppler frequency calculating unit <NUM>, the first wind speed distribution estimating unit <NUM>, the second wind speed distribution estimating unit <NUM>, and the wind speed prediction unit <NUM> is stored in a memory <NUM>. Then, a processor <NUM> of the computer executes the program stored in the memory <NUM>.

Further, <FIG> illustrates an example in which each of the components of the wind speed prediction device <NUM> is implemented by dedicated hardware, and <FIG> illustrates an example in which the wind speed prediction device <NUM> is implemented by software, firmware, or the like. However, this is merely an example, and some components in the wind speed prediction device <NUM> may be implemented by dedicated hardware, and the remaining components may be implemented by software, firmware, or the like.

Next, the operation of the radar device <NUM> illustrated in <FIG> will be described.

<FIG> is a flowchart illustrating a wind speed prediction method which is a processing procedure performed by the wind speed prediction device <NUM>.

As illustrated in <FIG>, the beam transmitting and receiving unit <NUM> emits each of a plurality of beams having different elevation angles θn (n = <NUM>,. , N) to space.

As illustrated in <FIG>, when the position of the flight area is deviated from directly above in the vertical direction, the beam transmitting and receiving unit <NUM> emits beams at respective elevation angles θn while switching the elevation angles θn. The beam emitted from the beam transmitting and receiving unit <NUM> is, for example, pulsed light.

Each beam emitted from the beam transmitting and receiving unit <NUM> is backscattered by fine particles such as aerosol floating in space. For example, when a plurality of fine particles is present in the line-of-sight direction of one beam, one beam is backscattered by each fine particle. The backscattered beam returns to the beam transmitting and receiving unit <NUM> as a scattering signal. Since the distances from the beam transmitting and receiving unit <NUM> to the plurality of fine particles are different from each other, the times at which the respective scattering signals return to the beam transmitting and receiving unit <NUM> are different from each other.

The beam transmitting and receiving unit <NUM> converts each scattering signal from an analog signal into a digital signal sθn,j(t) (n = <NUM>,. , N: j = <NUM>,. , J), and outputs the digital signal sθen,j to the wind speed prediction device <NUM>.

Further, the beam transmitting and receiving unit <NUM> outputs the angle information indicating the elevation angle θn of each beam emitted to space to the wind speed prediction device <NUM>.

The scattering signal acquiring unit <NUM> acquires each of the digital signals sθn,j(t) from the beam transmitting and receiving unit <NUM> (step ST1 in <FIG>).

Further, the scattering signal acquiring unit <NUM> acquires the angle information indicating the elevation angle θn of each beam from the beam transmitting and receiving unit <NUM>.

The Doppler frequency calculating unit <NUM> acquires each of the digital signals sθn,j(t) from the scattering signal acquiring unit <NUM>, and acquires each angle information from the scattering signal acquiring unit <NUM>.

Before FFT each of the digital signals sθn,j(t) in the hit direction, the Doppler frequency calculating unit <NUM> sets the FFT length Lθn of each of the digital signals sθn,j(t) according to the elevation angle θn indicated by the angle information (step ST2 in <FIG>). The FFT length Lθn corresponds to a range bin width of the scattering signal.

That is, the Doppler frequency calculating unit <NUM> sets the FFT length Lθn of the digital signal sθn,j(t) in such a way that the range bin width corresponding to the FFT length Lθn is proportional to <NUM>/sin (θn).

In a case where the FFT lengths Lθn of the respective digital signals sθn,j(t) are the same, when the elevation angles θn are different, as illustrated in <FIG>, the altitudes of a plurality of observation points of the same range bin Rbm are different from each other.

On the other hand, in a case where the FFT lengths Lθn of the respective digital signals sθn,j(t) are set according to the elevation angle θn, as illustrated in <FIG>, the altitudes of the plurality of observation points of the same range bin Rbm are the same altitude even if the elevation angles θn are different.

In the radar device <NUM> illustrated in <FIG>, the FFT length Lθn is set shorter as the elevation angle θn is wider, and the FFT length Lθn is set longer as the elevation angle θn of the scattering signal is narrower, so that a plurality of observation points in the same range bin Rbm have the same altitude.

<FIG> is an explanatory diagram illustrating an observation point of the Doppler frequency.

<FIG> is an explanatory diagram illustrating that the altitudes of a plurality of observation points of the same range bin Rbm are different from each other when the elevation angle θn is different.

<FIG> is an explanatory diagram illustrating that a plurality of observation points in the same range bin Rbm have the same altitude even when the elevation angle θn changes.

When the FFT length Lθn is set to be short, the width of the range bin Rbm becomes narrow and the distance resolution becomes high. On the other hand, when the FFT length Lθn is set to be long, the width of the range bin Rbm becomes wide and the distance resolution becomes low.

The Doppler frequency calculating unit <NUM> converts each digital signal sθn,j(t) into a frequency domain signal rθn,j(f) by performing FFT with an FFT length of Lθn in the hit direction for each digital signal sθn,j(t) (step ST3 in <FIG>).

The Doppler frequency calculating unit <NUM> calculates the respective Doppler frequencies dpfθn,j,Rbm in the plurality of range bins Rb<NUM> to RbM from the signals rθn,j(f) in the frequency domain (step ST4 in <FIG>).

Since the processing itself of calculating the Doppler frequencies dpfθn,j,Rbm of the range bin Rbm is a known technique, detailed description thereof will be omitted.

Note that calculation accuracy of the Doppler frequencies dpfθn,j,Rbm may be lowered due to a low signal to noise ratio (SNR) of the digital signal sθn,j(t). In such a case, the Doppler frequency calculating unit <NUM> may increase the calculation accuracy of the Doppler frequencies dpfθn,j,Rbm, for example, by performing the following processing.

For example, the Doppler frequency calculating unit <NUM> acquires digital signals sθn,j(t) related to a plurality of pulsed beams having the same elevation angle θn and different hit numbers, and converts the digital signals sθn,j(t) related to the plurality of beams into frequency domain signals rθn,j(f). Then, the Doppler frequency calculating unit <NUM> coherently integrates the signals rθn,j(f) in the plurality of frequency domains to increase the calculation accuracy of the Doppler frequencies dpfθn,j,Rbm. Since the processing itself for enhancing the calculation accuracy of the Doppler frequencies dpfθn,j,Rbm is a known technique, detailed description thereof will be omitted.

The first wind speed distribution estimating unit <NUM> acquires the Doppler frequencies dpfθn,j,Rbm of the respective range bins Rbm from the Doppler frequency calculating unit <NUM>.

The first wind speed distribution estimating unit <NUM> estimates the wind speed distribution uRbm(x, y) in the two-dimensional plane corresponding to each range bin Rbm from the plurality of Doppler frequencies dpfθ1,j,Rbm to dpfθN,j,Rbm in each range bin Rbm using the VVP method (step ST5 in <FIG>).

Hereinafter, estimation processing of the wind speed distribution uRbm(x, y) in the two-dimensional plane by the first wind speed distribution estimating unit <NUM> will be specifically described.

<FIG> is an explanatory diagram illustrating positions (x, y, z) of observation points of the wind speed.

The position (x, y, z) of the observation point of the wind speed is expressed by polar coordinates centered on the position O of the beam transmitting and receiving unit <NUM> included in the radar device <NUM> as expressed by the following Expression (<NUM>).

In Expression (<NUM>), θ is the elevation angle of a beam. φ is an angle formed by a line segment connecting the center point O' of the x-y plane where the observation point is present and the position (x, y, z) of the observation point and the y axis. r is a distance between the position O of the beam transmitting and receiving unit <NUM> and the position of the observation point (x, y, z).

For example, when the terrain of the ground surface vertically below the observation point is not a special terrain but a general terrain, there is no practical problem in observing the wind affecting the flying object as long as the wind speed prediction device <NUM> can observe the wind speed in a direction parallel to the two-dimensional plane even if the wind speed prediction device <NUM> cannot observe the wind speed in the vertical direction with respect to the two-dimensional plane where the observation point is present.

The general terrain corresponds to a flat terrain, an inclined terrain, a terrain having small irregularities, or the like. The special terrain corresponds to a terrain having a valley bottom, a terrain having a cliff with a large difference in elevation, or the like.

Accordingly, in the wind speed prediction device <NUM> illustrated in <FIG>, the first wind speed distribution estimating unit <NUM> ignores the wind speed in the vertical direction, and a true wind speed vector u at the observation point is expressed as the following Expression (<NUM>).

In Expression (<NUM>), ux represents a component in a direction parallel to the x-axis of the wind speed vector u, and uy represents a component in a direction parallel to the y-axis of the wind speed vector u.

The first wind speed distribution estimating unit <NUM> performs Taylor expansion of the wind speed vector u centered on the center point O' with respect to x and y on the assumption that the wind speed u<NUM> at the center point O' of the x-y plane is expressed as the following Expression (<NUM>). For example, when the third and subsequent terms are ignored, the following approximate Expression (<NUM>) holds. <MAT> <MAT>.

Since what is observed by the radar device <NUM> is the speed in the line-of-sight direction of the wind speed at the observation point, an observed wind speed ur(θ, φ) is expressed as the following Expression (<NUM>). <MAT> <MAT> <MAT>.

The first wind speed distribution estimating unit <NUM> acquires the observed wind speeds ur(θ<NUM>, φ<NUM>) to ur(θK, φK) of K beams, and substitutes the acquired observed wind speeds ur(θ<NUM>, φ<NUM>) to ur(θK, φK) into the following Expression (<NUM>) to estimate p illustrated in Expression (<NUM>). K is an integer of <NUM> or more. The K beams are K pieces of pulsed light in which sets of the elevation angle θ and the angle φ are different from each other.

A symbol "†" denotes pseudo-inverse matrix in Expression <NUM> In Expression (<NUM>), † is a symbol representing a pseudo-inverse matrix.

Among the elements of p illustrated in Expression (<NUM>), the fourth, seventh, and eighth elements from the top are expressed as the sum of two parameters, and thus are uncertain elements.

The first wind speed distribution estimating unit <NUM> determines the uncertain elements by equally allocating the parameter of the element of p estimated by Expression (<NUM>).

When the fourth element from the top among the elements of p is p<NUM>, the first wind speed distribution estimating unit <NUM> determines p<NUM> as in the following Expression (<NUM>), for example.

When the seventh element from the top among the elements of p is p<NUM>, the first wind speed distribution estimating unit <NUM> determines p<NUM> as in the following Expression (<NUM>), for example.

When the eighth element from the top among the elements of p is p<NUM>, the first wind speed distribution estimating unit <NUM> determines p<NUM> as in the following Expression (<NUM>), for example. <MAT> <MAT> <MAT>.

As described above, since all the coefficients u<NUM>, ∂u/∂x, ∂u/∂y, ∂<NUM>u/∂x<NUM>, ∂<NUM>u/∂x∂y, and ∂<NUM>u/∂y<NUM> illustrated in the approximate Expression (<NUM>) are determined, the first wind speed distribution estimating unit <NUM> can obtain the wind speed vector u(x, y) at each observation point from the approximate Expression (<NUM>).

When the wind speed vector u(x, y) at each observation point can be obtained, the first wind speed distribution estimating unit <NUM> can obtain the wind speed distribution uRbm(x, y) in the two-dimensional plane corresponding to each range bin Rbm.

Here, the first wind speed distribution estimating unit <NUM> approximates the Taylor expansion of the wind speed vector u(x, y) by 0th to 2nd order terms. However, this is merely an example, and the first wind speed distribution estimating unit <NUM> may approximate the Taylor expansion of the wind speed vector u(x, y) with terms of <NUM> degree to <NUM> degrees or more.

When M is <NUM>, the first wind speed distribution estimating unit <NUM> outputs the wind speed distribution uRb1(x, y) in the two-dimensional plane corresponding to the range bin Rb<NUM> to the wind speed prediction unit <NUM>.

The second wind speed distribution estimating unit <NUM> acquires the wind speed distribution uRbm(x, y) in the two-dimensional plane corresponding to each range bin Rbm from the first wind speed distribution estimating unit <NUM>.

The second wind speed distribution estimating unit <NUM> estimates a wind speed distribution uRbm'(x, y) in a two-dimensional plane between the plurality of two-dimensional planes from the wind speed distributions uRb1(x, y) to uRbM(x, y) in the plurality of two-dimensional planes (step ST6 in <FIG>).

The second wind speed distribution estimating unit <NUM> outputs the wind speed distributions uRb1'(x, y) to uRbM-<NUM>'(x, y) in the two-dimensional planes to the wind speed prediction unit <NUM>.

Hereinafter, estimation processing of the wind speed distribution uRbm'(x, y) in the two-dimensional plane by the second wind speed distribution estimating unit <NUM> will be specifically described.

For example, when estimating the wind speed distribution uRbm'(x, y) in the two-dimensional plane between the two-dimensional plane in which the wind speed distribution is uRbm(x, y) and a two-dimensional plane in which the wind speed distribution is uRbm+<NUM>(x, y), the second wind speed distribution estimating unit <NUM> calculates the distance Lm-m' in the vertical direction from the two-dimensional plane in which the wind speed distribution uRbm'(x, y) is estimated to the two-dimensional plane in which the wind speed distribution is uRbm(x, y).

Further, the second wind speed distribution estimating unit <NUM> calculates a distance L(m+<NUM>)-m' in the vertical direction from the two-dimensional plane in which the wind speed distribution uRbm'(x, y) is estimated to the two-dimensional plane in which the wind speed distribution is uRbm+<NUM>(x, y).

The second wind speed distribution estimating unit <NUM> calculates a weighting coefficient wm for the wind speed distribution uRbm(x, y) in the two-dimensional plane and a weighting coefficient wm+<NUM> for the wind speed distribution uRbm+<NUM>(x, y) in the two-dimensional plane on the basis of the distance Lm-m' and the distance L(m+<NUM>)-m' as expressed in the following Expressions (<NUM>) to (<NUM>). <MAT> <MAT> <MAT>.

The second wind speed distribution estimating unit <NUM> estimates the wind speed distribution uRbm'(x, y) in the two-dimensional plane between the two-dimensional plane in which the wind speed distribution is uRbm(x, y) and the two-dimensional plane in which the wind speed distribution is uRbm+<NUM>(x, y) on the basis of the weighting coefficient wm and the weighting coefficient wm+<NUM> as expressed in the following Expression (<NUM>).

Here, the second wind speed distribution estimating unit <NUM> estimates the wind speed distribution uRbm'(x, y) in the two-dimensional plane as a weighted average based on the distance from the two-dimensional plane in which the wind speed distribution uRbm'(x, y) is estimated. However, this is merely an example, and for example, the second wind speed distribution estimating unit <NUM> compares the distance Lm-m' with the distance L(m+<NUM>)-m'. When the distance Lm-m' is shorter than the distance L(m+<NUM>)-m', the second wind speed distribution estimating unit <NUM> may use the wind speed distribution uRbm(x, y) in the two-dimensional plane as the wind speed distribution uRbm'(x, y) in the two-dimensional plane, and when the distance Lm-m' is equal to or longer than the distance L(m+<NUM>)-m', the second wind speed distribution estimating unit <NUM> may use the wind speed distribution uRbm+<NUM>(x, y) in the two-dimensional plane as the wind speed distribution uRbm'(x, y) in the two-dimensional plane.

Further, here, the second wind speed distribution estimating unit <NUM> estimates the wind speed distribution uRbm'(x, y) in one two-dimensional plane as the wind speed distribution in the two-dimensional plane between the two-dimensional plane in which the wind speed distribution is uRbm(x, y) and the two-dimensional plane in which the wind speed distribution is uRbm+<NUM>(x, y). However, this is merely an example, and the second wind speed distribution estimating unit <NUM> may estimate wind speed distributions uRbm'(x, y) of two or more two-dimensional planes having different positions in the vertical direction as the wind speed distribution in the two-dimensional plane between the two-dimensional plane in which the wind speed distribution is uRbm(x, y) and the two-dimensional plane in which the wind speed distribution is uRbm+<NUM>(x, y).

When M is <NUM>, the wind speed prediction unit <NUM> acquires the wind speed distribution uRb1(x, y) in the two-dimensional plane from the first wind speed distribution estimating unit <NUM>.

When M is <NUM> or more, the wind speed prediction unit <NUM> acquires the wind speed distributions uRb1(x, y) to uRbM(x, y) in the plurality of two-dimensional planes from the first wind speed distribution estimating unit <NUM>, and acquires wind speed distributions uRb1'(x, y) to uRbM-<NUM>'(x, y) in the two-dimensional plane from the second wind speed distribution estimating unit <NUM>.

When M is <NUM>, the wind speed prediction unit <NUM> predicts the wind speed u(t) in the observation region in the two-dimensional plane from the wind speed distribution uRb1(x, y) in the two-dimensional plane using the two-dimensional N-S equation (step ST7 in <FIG>).

When M is <NUM> or more, the wind speed prediction unit <NUM> selects the wind speed distribution in any two-dimensional plane from among the wind speed distributions uRb1(x, y) to uRbm(x, y) in the plurality of two-dimensional planes and the wind speed distributions uRb1'(x, y) to uRbM-<NUM>'(x, y) in the two-dimensional planes.

When the observation point of the prediction target of the wind speed u(t) is present in the observation region in the two-dimensional plane corresponding to the range bin Rbm, the wind speed prediction unit <NUM> selects the wind speed distribution uRbm(x, y). When the observation point of the prediction target of the wind speed u(t) is present in the observation region in the two-dimensional plane corresponding to the range bin Rbm', the wind speed prediction unit <NUM> selects the wind speed distribution uRbm'(x, y).

The wind speed prediction unit <NUM> predicts the wind speed u(t) in the observation region in the selected two-dimensional plane from the wind speed distribution in the selected two-dimensional plane using the two-dimensional N-S equation (step ST7 in <FIG>).

Hereinafter, prediction processing of the wind speed u(t) performed by the wind speed prediction unit <NUM> will be specifically described.

Wind is generally considered an uncompressed fluid. The two-dimensional N-S equation regarding the uncompressed fluid is expressed by the following Expressions (<NUM>) and (<NUM>). <MAT> <MAT>.

In Expression (<NUM>), u is a wind speed vector, v is a viscosity coefficient, ρ is a density, p is a pressure, f is an external force vector, and t is a time variable.

Since the viscosity coefficient v is very small, the viscosity of the wind can be ignored. In addition, the term of the external force vector F can also be ignored. Therefore, under the condition that each of the viscosity of the wind and the external force is absent, Expression (<NUM>) is expressed as the following Expression (<NUM>), and Expression (<NUM>) is expressed as the following Expression (<NUM>). <MAT> <MAT>.

The first term on the right side of Expression (<NUM>) is referred to as an advection term, and the second term on the right side is referred to as a pressure term.

When the wind speed vector u is a two-dimensional vector u = [ux, uy]T, Expression (<NUM>) is expressed as the following Expressions (<NUM>) and (<NUM>). <MAT> <MAT> <MAT>.

When Expression (<NUM>) is used, Expression (<NUM>) is expressed as the following Expression (<NUM>), and Expression (<NUM>) is expressed as the following Expression (<NUM>). <MAT> <MAT>.

When the wind speed vector u is discretized with respect to time by the difference method, Expression (<NUM>) is expressed as the following Expression (<NUM>), and Expression (<NUM>) is expressed as the following Expression (<NUM>). <MAT> <MAT>.

In the Expressions (<NUM>) and (<NUM>), g and g + <NUM> are symbols indicating time steps.

By using an intermediate variable ux*, Expression (<NUM>) can be divided into two Expressions as the following Expressions (<NUM>) and (<NUM>).

In addition, by using an intermediate variable uy*, Expression (<NUM>) can be divided into two Expressions as the following Expressions (<NUM>) and (<NUM>). <MAT> <MAT> <MAT> <MAT>.

Expression (<NUM>) is transformed as Expression (<NUM>), and Expression (<NUM>) is transformed as Expression (<NUM>). <MAT> <MAT>.

Expression (<NUM>) is expressed as Expression (<NUM>) below when differentiated in the x direction, and Expression (<NUM>) is expressed as Expression (<NUM>) below when differentiated in the y direction. <MAT> <MAT>.

When the left sides of Expressions (<NUM>) and (<NUM>) are added to each other and the right sides of Expressions (<NUM>) and (<NUM>) are added to each other, the following Expression (<NUM>) is obtained.

According to Expression (<NUM>), ∇·ug+<NUM> = <NUM> needs to be satisfied for the estimated wind speed vector u at the next time step g + <NUM>. Therefore, the following Expression (<NUM>) is obtained as the Poisson's equation regarding pressure from Expression (<NUM>).

The wind speed prediction unit <NUM> discretizes the wind speed vector ug = [uxg, uyg]T at the current time step g in the spatial direction.

The wind speed prediction unit <NUM> calculates the intermediate variable ux* by substituting the discretized uxg into Expression (<NUM>), and calculates the intermediate variable uy* by substituting the discretized uyg into Expression (<NUM>).

The wind speed prediction unit <NUM> calculates the pressure p from Expression (<NUM>) using the intermediate variable ux* and the intermediate variable uy*.

The wind speed prediction unit <NUM> calculates a wind speed vector uxg+<NUM> of the next time step g + <NUM> from Expression (<NUM>) using the intermediate variable ux * and the pressure p.

The wind speed prediction unit <NUM> calculates a wind speed vector uyg+<NUM> of the next time step g + <NUM> from Expression (<NUM>) using the intermediate variable uy* and the pressure p.

The wind speed u(t) predicted by the wind speed prediction unit <NUM> is [uxg+<NUM>, uyg+<NUM>]T, and the wind speed u(t) is displayed on, for example, a display (not illustrated).

A conventional wind speed prediction device performs a simulation using a weather model in order to predict a wind speed in an observation region, and the simulation using the weather model is three-dimensional calculation processing. For example, when the number of observation points in the three-dimensional observation region is Cx × Cy × Cz, and C = Cx = Cy = Cz, the calculation amount order is approximately proportional to C<NUM>.

On the other hand, the calculation processing of the wind speed prediction device <NUM> illustrated in <FIG> is two-dimensional calculation processing. For example, when the number of two-dimensional planes is M, the number of observation points in the observation region present in the two-dimensional plane is Cx × Cy, and C = Cx = Cy, the calculation amount order is approximately proportional to C<NUM> × M. When M = C, the calculation amount order of the wind speed prediction device <NUM> illustrated in <FIG> is substantially the same as the calculation amount order of the conventional wind speed prediction device.

However, it is assumed that three-dimensional calculation processing uses a three-dimensional N-S equation that does not ignore vertical wind. In the three-dimensional N-S equation, it is difficult to greatly expand the interval between the observation points in the vertical direction, and the maximum value of the interval between the observation points at which the three-dimensional N-S equation can be solved is determined as a Courant condition in the vertical direction.

On the other hand, in the two-dimensional N-S equation ignoring the vertical wind, which is the two-dimensional calculation processing, since there is no Courant condition in the vertical direction, it is possible to satisfy Cz >> M. For example, when (M/Cz) = <NUM>/Q, the calculation amount order of the wind speed prediction device <NUM> illustrated in <FIG> is approximately <NUM>/Q of the calculation amount order of the conventional wind speed prediction device. Q is a value of about <NUM> to <NUM>.

As described above, for example, when the terrain of the ground surface vertically below the observation point is not a special terrain but a general terrain, there is no practical problem in observing the wind affecting the flying object as long as the wind speed prediction device <NUM> can observe the wind speed in the direction parallel to the two-dimensional plane even if the wind speed prediction device <NUM> cannot observe the wind speed in the vertical direction with respect to the two-dimensional plane where the observation point is present.

Even if the terrain of the ground surface vertically below the observation point is a special terrain, the wind speed in the direction parallel to the two-dimensional plane can be used as useful information for observing the wind affecting the flying object.

In a first embodiment described above, the wind speed prediction device <NUM> includes the scattering signal acquiring unit <NUM> to acquire a scattering signal that is each of a plurality of beams after being emitted to space and scattered in the space, the beams having mutually different elevation angles, which are angles formed by a line-of-sight direction and a horizontal direction, the Doppler frequency calculating unit <NUM> to set a range bin width as distance resolution of each of scattering signals acquired by the scattering signal acquiring unit <NUM> according to an elevation angle of each of the beams emitted to space, and calculate a Doppler frequency of a range bin corresponding to a two-dimensional plane including an observation region from the each of the scattering signals, the first wind speed distribution estimating unit <NUM> to estimate a wind speed distribution in the two-dimensional plane from a plurality of Doppler frequencies calculated by the Doppler frequency calculating unit <NUM> using a VVP method, and the wind speed prediction unit <NUM> to predict a wind speed in the observation region from the wind speed distribution in the two-dimensional plane estimated by the first wind speed distribution estimating unit <NUM> using a two-dimensional Navier-Stokes equation. Therefore, the wind speed prediction device <NUM> can predict the wind speed without performing three-dimensional calculation processing.

In the wind speed prediction device <NUM> illustrated in <FIG>, the first wind speed distribution estimating unit <NUM> estimates the wind speed distribution uRbm(x, y) in the two-dimensional plane corresponding to each range bin Rbm. However, the wind speed distribution uRbm(x, y) estimated by the first wind speed distribution estimating unit <NUM> may slightly deviate from the actual wind speed distribution due to the influence of observation noise. The first wind speed distribution estimating unit <NUM> may smooth the wind speed distribution uRbm(x, y) in the time direction in order to suppress the deviation due to the influence of the observation noise.

The smoothing of the wind speed distribution uRbm(x, y) in the time direction can be implemented by fusing a fluid movement model such as a two-dimensional N-S equation and the estimated wind speed distribution uRbm(x, y). The fusion of the fluid movement model and the wind speed distribution uRbm(x, y) is called data assimilation.

For example, it is assumed that the true wind speed distribution uRbm(x, y) at the previous time step g-<NUM> is represented by ut=tg-<NUM>, and the true wind speed distribution uRbm(x, y) at the current time step g is represented by ut=tg. The two-dimensional N-S equation is a fluid model that can nonlinearly describe the relationship between ut=tg-<NUM> and ut=tg, and if a nonlinear function is represented by f(·), the following Expression (<NUM>) holds.

The data assimilation processing is processing performed using a data assimilation function As(·) as expressed in the following Expression (<NUM>). That is, the data assimilation processing calculates a smoothed u(x, y; t=tg) bar of the current time step g by adding u(x, y; t=tg) which is the wind speed distribution uRbm(x, y) of the current time step g and f(u(x, y; t=tg-<NUM>) bar) obtained by time-developing the wind speed distribution uRbm(x, y) of the previous time step g-<NUM> to the current time step g. In the text of the specification, since it is not possible to attach a symbol "-" above a character due to the electronic application, for example, it is written as a u(x, y; t=tg) bar.

Here, the first wind speed distribution estimating unit <NUM> performs the data assimilation processing using the data assimilation function As(·). However, this is merely an example, and the first wind speed distribution estimating unit <NUM> may perform the data assimilation processing by, for example, a particle filter using a two-dimensional N-S equation or an ensemble Kalman filter using the two-dimensional N-S equation. In addition, the first wind speed distribution estimating unit <NUM> may perform the data assimilation processing by an extended Kalman filter in which the two-dimensional N-S equation is approximated to a linear function or a variational method using the two-dimensional N-S equation.

In the wind speed prediction device <NUM> according to the first embodiment, the wind speed prediction unit <NUM> selects the wind speed distribution in any two-dimensional plane from among the wind speed distributions uRb1(x, y) to uRbM(x, y) in the plurality of two-dimensional planes and the wind speed distributions uRb1'(x, y) to uRbM-<NUM>'(x, y) in the two-dimensional planes.

In a second embodiment, a wind speed prediction device <NUM> including a wind speed prediction unit <NUM> will be described, the wind speed prediction unit <NUM> estimating a wind speed distribution in a two-dimensional plane including a flight area in which a flying object is scheduled to fly as an observation region from the wind speed distributions uRb1(x, y) to uRbm(x, y) in the plurality of two-dimensional planes and the wind speed distributions uRb1'(x, y) to uRbM-<NUM>'(x, y) in the two-dimensional planes.

<FIG> is a configuration diagram illustrating the wind speed prediction device <NUM> according to the second embodiment. In <FIG>, the same reference numerals as those in <FIG> denote the same or corresponding parts, and thus description thereof is omitted.

<FIG> is a hardware configuration diagram illustrating hardware of the wind speed prediction device <NUM> according to the second embodiment. In <FIG>, the same reference numerals as those in <FIG> denote the same or corresponding parts, and thus description thereof is omitted.

The wind speed prediction device <NUM> illustrated in <FIG> includes a scattering signal acquiring unit <NUM>, a Doppler frequency calculating unit <NUM>, a first wind speed distribution estimating unit <NUM>, a second wind speed distribution estimating unit <NUM>, and the wind speed prediction unit <NUM>.

The wind speed prediction unit <NUM> estimates a wind speed distribution in a two-dimensional plane including a flight area as an observation region from the wind speed distributions uRb1(x, y) to uRbM(x, y) in the plurality of two-dimensional planes estimated by the first wind speed distribution estimating unit <NUM> and the wind speed distributions uRb1'(x, y) to uRbM-<NUM>'(x, y) in the two-dimensional plane estimated by the second wind speed distribution estimating unit <NUM>.

The wind speed prediction unit <NUM> predicts the wind speed u(t) in the flight area from the estimated wind speed distribution in the two-dimensional plane using the two-dimensional N-S equation.

Each of the scattering signal acquiring circuit <NUM>, the Doppler frequency calculating circuit <NUM>, the first wind speed distribution estimating circuit <NUM>, the second wind speed distribution estimating circuit <NUM>, and the wind speed prediction circuit <NUM> corresponds to, for example, a single circuit, a composite circuit, a programmed processor, a parallel-programmed processor, ASIC, FPGA, or a combination thereof.

In a case where the wind speed prediction device <NUM> is implemented by software, firmware, or the like, a program for causing a computer to execute each processing procedure in the scattering signal acquiring unit <NUM>, the Doppler frequency calculating unit <NUM>, the first wind speed distribution estimating unit <NUM>, the second wind speed distribution estimating unit <NUM>, and the wind speed prediction unit <NUM> is stored in the memory <NUM> illustrated in <FIG>. Then, the processor <NUM> illustrated in <FIG> executes the program stored in the memory <NUM>.

Next, the operation of the wind speed prediction device <NUM> illustrated in <FIG> will be described. The wind speed prediction device <NUM> is similar to the wind speed prediction device <NUM> illustrated in <FIG> except for the wind speed prediction unit <NUM>, and thus only the operation of the wind speed prediction unit <NUM> will be described here.

Here, for convenience of description, it is assumed that the flight area is present in a two-dimensional plane between a two-dimensional plane in which the wind speed distribution is uRbm(x, y) and a two-dimensional plane in which the wind speed distribution is uRbm'(x, y).

The wind speed prediction unit <NUM> calculates a distance Lp-m in the vertical direction from the two-dimensional plane in which the flight area is present to the two-dimensional plane in which the wind speed distribution is uRbm(x, y).

Further, the wind speed prediction unit <NUM> calculates a distance Lp-m' in the vertical direction from the two-dimensional plane in which the flight area is present to the two-dimensional plane in which the wind speed distribution is uRbm'(x, y).

The wind speed prediction unit <NUM> calculates a weighting coefficient wp-m for the wind speed distribution uRbm(x, y) in the two-dimensional plane and a weighting coefficient wp-m' for the wind speed distribution uRbm'(x, y) in the two-dimensional plane on the basis of the distance Lp-m and the distance Lp-m' as expressed in the following Expressions (<NUM>) to (<NUM>). <MAT> <MAT> <MAT>.

The wind speed prediction unit <NUM> estimates the wind speed distribution uRbp(x, y) of the two-dimensional plane where the flight area is present on the basis of the weighting coefficient wp-m and the weighting coefficient wp-m' as expressed in the following Expression (<NUM>).

The wind speed prediction unit <NUM> predicts the wind speed u(t) in the flight area from the estimated wind speed distribution uRbp(x, y) in the two-dimensional plane using the two-dimensional N-S equation. The prediction processing of the wind speed u(t) performed by the wind speed prediction unit <NUM> is similar to the prediction processing of the wind speed u(t) performed by the wind speed prediction unit <NUM> illustrated in <FIG>.

In a third embodiment, a wind speed prediction device <NUM> including a time notification unit <NUM> that calculates a time t at which the wind speed u(t) predicted by the wind speed prediction unit <NUM> becomes equal to or higher than the threshold Th and gives a notification of the time t will be described.

<FIG> is a configuration diagram illustrating the wind speed prediction device <NUM> according to the third embodiment. In <FIG>, the same reference numerals as those in <FIG> and <FIG> denote the same or corresponding parts, and thus description thereof is omitted.

<FIG> is a hardware configuration diagram illustrating hardware of the wind speed prediction device <NUM> according to the third embodiment. In <FIG>, the same reference numerals as those in <FIG> and <FIG> denote the same or corresponding parts, and thus description thereof is omitted.

The wind speed prediction device <NUM> illustrated in <FIG> includes a scattering signal acquiring unit <NUM>, a Doppler frequency calculating unit <NUM>, a first wind speed distribution estimating unit <NUM>, a second wind speed distribution estimating unit <NUM>, the wind speed prediction unit <NUM>, and the time notification unit <NUM>.

The time notification unit <NUM> is implemented by, for example, a time notification circuit <NUM> illustrated in <FIG>.

The time notification unit <NUM> specifies the time t at which the wind speed u(t) predicted by the wind speed prediction unit <NUM> becomes equal to or higher than the threshold Th.

The time notification unit <NUM> gives a notification of the specified time t to, for example, a flying object or a control tower monitoring a flight state of the flying object.

<FIG> illustrates an example in which the time notification unit <NUM> is applied to the wind speed prediction device <NUM> illustrated in <FIG>. However, this is merely an example, and the time notification unit <NUM> may be applied to the wind speed prediction device <NUM> illustrated in <FIG>.

In <FIG>, it is assumed that each of the scattering signal acquiring unit <NUM>, the Doppler frequency calculating unit <NUM>, the first wind speed distribution estimating unit <NUM>, the second wind speed distribution estimating unit <NUM>, the wind speed prediction unit <NUM>, and the time notification unit <NUM>, which are components of the wind speed prediction device <NUM>, is implemented by dedicated hardware as illustrated in <FIG>. That is, it is assumed that the wind speed prediction device <NUM> is implemented by the scattering signal acquiring circuit <NUM>, the Doppler frequency calculating circuit <NUM>, the first wind speed distribution estimating circuit <NUM>, the second wind speed distribution estimating circuit <NUM>, the wind speed prediction circuit <NUM>, and the time notification circuit <NUM>.

Each of the scattering signal acquiring circuit <NUM>, the Doppler frequency calculating circuit <NUM>, the first wind speed distribution estimating circuit <NUM>, the second wind speed distribution estimating circuit <NUM>, the wind speed prediction circuit <NUM>, and the time notification circuit <NUM> corresponds to, for example, a single circuit, a composite circuit, a programmed processor, a parallel-programmed processor, ASIC, FPGA, or a combination thereof.

In a case where the wind speed prediction device <NUM> is implemented by software, firmware, or the like, a program for causing a computer to execute each processing procedure in the scattering signal acquiring unit <NUM>, the Doppler frequency calculating unit <NUM>, the first wind speed distribution estimating unit <NUM>, the second wind speed distribution estimating unit <NUM>, the wind speed prediction unit <NUM>, and the time notification unit <NUM> is stored in the memory <NUM> illustrated in <FIG>. Then, the processor <NUM> illustrated in <FIG> executes the program stored in the memory <NUM>.

Next, the operation of the wind speed prediction device <NUM> illustrated in <FIG> will be described. The wind speed prediction device <NUM> is similar to the wind speed prediction device <NUM> illustrated in <FIG> except for the time notification unit <NUM>, and thus only the operation of the time notification unit <NUM> will be described here.

The time notification unit <NUM> acquires the predicted wind speed u(t) from the wind speed prediction unit <NUM> every time the wind speed prediction unit <NUM> predicts the wind speed u(t).

Every time the predicted wind speed u(t) is acquired, the time notification unit <NUM> compares the wind speed u(t) with the threshold Th. The threshold Th is, for example, a lower limit value of the wind speed that may affect the flight of the flying object. The threshold Th may be stored in the internal memory of the time notification unit <NUM> or may be given from the outside.

The time notification unit <NUM> specifies the time t at which the wind speed u(t) is equal to or higher than the threshold Th on the basis of the comparison result between the wind speed u(t) and the threshold Th.

In the third embodiment described above, the wind speed prediction device <NUM> illustrated in <FIG> includes the time notification unit <NUM> that specifies the time at which the wind speed predicted by the wind speed prediction unit <NUM> becomes equal to or higher than the threshold and gives a notification of the specified time t. Therefore, the wind speed prediction device <NUM> illustrated in <FIG> can predict the wind speed without performing three-dimensional calculation processing, as does the wind speed prediction device <NUM> illustrated in <FIG>. In addition, it is possible to notify the time when wind that may affect the flight of the flying object blows.

The present disclosure is suitable for a wind speed prediction device, a wind speed prediction method, and a radar device.

Claim 1:
A wind speed prediction device (<NUM>), comprising:
a scattering signal acquiring unit (<NUM>) to acquire a scattering signal that is each of a plurality of beams after being emitted to space and scattered in the space, the beams having mutually different elevation angles, which are angles formed by a line-of-sight direction and a horizontal direction;
a Doppler frequency calculating unit (<NUM>) to set a range bin width as distance resolution of each of scattering signals acquired by the scattering signal acquiring unit (<NUM>) according to an elevation angle of each of the beams emitted to the space to enable monitoring of observation points of same range bins, the range bins being at the same altitude even for the plurality of beams at different elevation angles, and calculate a Doppler frequency of a range bin corresponding to a two-dimensional plane including an observation region from the each of the scattering signals;
a first wind speed distribution estimating unit (<NUM>) to estimate a wind speed distribution in the two-dimensional plane from the plurality of Doppler frequencies calculated by the Doppler frequency calculating unit (<NUM>); and
a wind speed prediction unit (<NUM>, <NUM>) to predict a wind speed in the observation region from the wind speed distribution in the two-dimensional plane estimated by the first wind speed distribution estimating unit (<NUM>);
characterised in that;
the first wind speed distribution estimating unit (<NUM>) is configured to estimate the wind speed distribution in the two-dimensional plane using a volume velocity processing (VVP) method; and
the wind speed predication unit (<NUM>, <NUM>) is configured to predict the wind speed in the observation region using a two-dimensional Navier-Stokes equation.