JP3733330B2 - Atmospheric measurement system and method - Google Patents

Description

【００２４】
すなわち、２つの信号の積をとり、時間Ｔで平均したものとして与えられる。（１）式と（２）式を（５）式に代入し、平均時間Ｔが受信周波数の逆数１／ｆに比べて十分に長いとすると、次式（６）が成り立つ。
【００２５】
【数２】

【００２６】
となる。ここで、ΔΦ（ｔ）は相互相関位相であり、ΔΦ（ｔ）＝Φ_２（ｔ）−Φ_１（ｔ）＝２πｆ（τ_１−τ_２）である。衛星の動きによる到着時間差の変化分を補正すると、τ_１−τ_２は「衛星６０からアンテナ１０を結ぶ伝播路上にある水蒸気などの揺らぎによる伝播時間の揺らぎ」と「衛星６０からアンテナ２０を結ぶ伝播路上にある水蒸気などの揺らぎによる伝播時間の揺らぎ」の差を表しており、位相差ΔΦ（ｔ）もそれに比例した量になっている。なお、（５）式のｃ（ｔ）から直接ΔΦ（ｔ）をもとめることはできないので、アンテナ２０の受信信号を９０度位相をずらした信号である、
ｓ_２´（ｔ）＝Ａ_２・sin（２πｆｔ＋Φ_２（ｔ）＋π／２）＝Ａ_２・cos（２πｆｔ＋Φ_２（ｔ））
を取り出し、これと（１）式との相互相関を計算する。これにより、次式（７）が成り立つ。
【００２７】
【数３】

【００２８】
つぎに、（６）式と（７）式から、次式（８）として求める。
ΔΦ（ｔ）＝tan^−１（ｃ´（ｔ）／ｃ（ｔ）） （８）
【００２９】
図６は、大気計測システム１００における相関処理装置４０での処理を主に示すフローチャートである。なお、ここでは、上述のアンテナ１０とアンテナ２０との位相差ΔΦ（ｔ）を算出する際に用いた各数式と対応させて説明する。
まず、相関処理装置４０は、上述のｃ（ｔ）とｃ´（ｔ）との初期化を行う（Ｓ２０１）。すなわち、ｃ（ｔ）＝０、ｃ´（ｔ）＝０とする。つぎに、第１受信装置１５は、アンテナ１０で衛星６０からのビーコン電波ｓ_１（ｔ）を第１データファイル７１から読出す（Ｓ２０３）。また、第２受信装置２５は、アンテナ２０で衛星６０からのビーコン電波ｓ_２（ｔ）を第１データファイル７１から読出す（Ｓ２０７）。
【００３０】
つぎに、相関処理装置４０は、ステップＳ２０５、Ｓ２０９で読出したデータを、次式に基づいて、それぞれｃ（ｔ）、ｃ´（ｔ）を算出する（Ｓ２１１）。
ｃ（ｔ）＝ｃ（ｔ）＋ｓ_１（ｔ）・ｓ_２（ｔ）
ｃ´（ｔ）＝ｃ´（ｔ）＋ｓ_１（ｔ）・ｓ´_２（ｔ）
【００３１】
ここで、相関処理装置４０は、算出したデータ数が所要数を満たすか否かを判定する（Ｓ２１３）。ここで、所要数を満たさない場合、相関処理装置４０は、再びステップＳ２０３、２０７へ戻り、データ読込み、算出処理を繰返す。一方、ステップＳ２１３で所要数を満たす場合、相関処理装置４０は、ステップＳ２１１で算出したｃ（ｔ）、ｃ´（ｔ）を、データ数で割ることにより、ｃ（ｔ）、ｃ´（ｔ）のそれぞれの平均を求める（Ｓ２１５）。つぎに、ステップＳ２１５で算出したｃ（ｔ）、ｃ´（ｔ）のそれぞれの平均に基づいて、（８）式に従い位相差
ΔΦ（ｔ）を求める（Ｓ２１７）。
【００３２】
図７に、第２データファイル７２の説明図を示す。この例では、衛星識別子、時間、衛星の方位角、衛星の仰角、位相差Φ（到着時間差）、ゆらぎσ_Φを含む。ここでは、相関処理装置４０は、ゆらぎσ_Φ以外のデータを第２データファイルに書込む。
【００３３】
（データ解析装置５０における位相揺らぎ（水蒸気分布の揺らぎ）の算出：Ｓ１１９について）
データ解析装置５０は、第２データファイル７２を参照し、小領域ごとに代表点に対応して、読み出した位相差Φに基づき、さらに到着時間差の変化（例えば、偏差σ_Φ（ｔ））を算出する。
ここで、到着時間差の変化を示す偏差σ_Φ（ｔ）について説明する。
【００３４】
ステップＳ１１９の処理では、大気中の水蒸気の局所的な不均一さを検出することを目指しているので、測定量（到達時間差）から到着時間差の系統的な変化（たとえば、時間の経過に対する一様な増加あるいは減少）を引き去った後、平均からのゆらぎ（すなわち、標準偏差）を求める。ここで、系統的な変化は、例えば、水蒸気、空気の層により生じて、衛星６０が出現してから没入するまでの間に測定される大きな変動のことである。この変動は、ハイパスフィルタ等により補正された信号を所定周波数以上パスさせることで除いたり、所定の１次、２次、３次式等の近似式を用いて除いたりすることができる。標準偏差を、衛星６０の軌道６０２の小区間６０３ごとに求めるようにすると、この量は天球上の局所的な部分における水蒸気量等の空間的なゆらぎに対応している（参考文献：G.Brussaard and P.A. Watson, "Atmospheric modelling and millimetre wave propagation, Chapman & Hall, 1995のp.54の記述など）。
【００３５】
以上のような操作を衛星６０の軌道６０１、６０２に沿って、また、さまざまな衛星の軌道に沿っておこなうと、天球上（二次元空間）のさまざまな場所での水蒸気量等の空間的なゆらぎが得られる。
到着時間差のゆらぎσ_Φ（ｔ）は、相互相関位相ΔΦ（ｔ）の揺らぎと等価なので、相互相関位相ΔΦ（ｔ）のゆらぎは、次式（９）より算出される。
【００３６】
【数４】

【００３７】
ここで、Ｔはデータを平均する区間であり、観測点から見た衛星６０の天球上での角移動速度をｕ［radian/sec］、二次元画像の所要解像度をΔθとすると、Ｔ＝Δθ／ｕ
によって与えられる。なお、所要解像度をあまり小さく取るとデータの信頼度が下がるので、最適な値、範囲が存在する（例えば、Δθ＝１[deg]程度）。この値又は範囲は、アンテナの位置、気象条件、地域、気候等により予め適宜定めることができる。データ解析装置５０は、第２データファイル７２の該当エリアに、ゆらぎσ_Φを書込む。
【００３８】
図８は、相互相関位相ΔΦ（ｔ）と、相関位相のゆらぎσ_Φ（ｔ）との対応関係を示す図である。
相互相関位相ΔΦ（ｔ）は、例えば、上述した（６）式、（７）式を用いて算出されるものであり、横軸を時間ｔとし、さらに、横軸は、データを平均するための区間であるＴ時間毎に区切られている。なお、衛星６０は、軌道６０２に含まれる複数の小区間６０３をＴ時間で移動することになる。また、相関位相のゆらぎσ_Φ（ｔ）は、例えば、上述した（９）式を用いて算出されるものであり、横軸を時間ｔとし、さらに、縦軸には、小区間６０３に含まれる偏差の代表点６０４に対応した位置での値（図中、○印）が示されている。
【００３９】
（データ解析装置５０における水蒸気の二次元分布の算出：Ｓ１２１について）
図９は、水蒸気の二次元分布図を作成する際の天球面を示す図である。
天球面は、例えば、地平線６００、測定の代表点（図中、○印）６１０、衛星の軌道（図中、○印を含む実線）６３０、格子の交点６２０を含む。格子の交点６２０は、例えば、上述の補間処理を用いて、二次元分布を求める点である。
【００４０】
天球上での水蒸気量等の空間的なゆらぎの測定点の分布は一様ではなく、衛星６０の軌道に沿った部分に局在している。二次元分布図を作るためには、まず、天球面を格子状に区切り、データ解析装置５０は、第２データファイル７２に記憶されたデータを読み出し、位置データを格子状の２次元座標に変換して第３データファイルを作成し記憶する。さらに、データ解析装置５０は、第２データファイルを読み出し、記憶された測定の代表点６１０のゆらぎの値等のデータから格子の交点６２０でのゆらぎの値を推定する。この処理は、二次元補間アルゴリズムにより行う。補間法としては、例えば、二次元空間でのスプライン補間法、キュービックコンボリューション法などの汎用のアルゴリズムを使うことができる。
【００４１】
図１０は、第３データファイルの説明図を示す。この例では、Ｘ、Ｙ座標に対するゆらぎが記憶される。
なお、上述の大気計測システム１００では、２つのアンテナ（第１衛星追跡アンテナ１０と第２衛星追跡アンテナ２０）を用いて衛星６０を追跡しているが、アンテナの数は、これに限られず、更に多くのアンテナを用いることもできる。これにより、測定精度、測定効率を上げることができる。また、本発明の応用として、まだ雲の動きとして捉えることができない気象前線最先端部の大気の乱れなどを詳細に検出し、気象災害のより早い予測に利用できることも期待できる。
【００４２】
【発明の効果】
本発明によると、以上説明した通り、地上から高度数ｋｍの高度における大気の流れを広範囲、高精度かつ簡便に検出することができる。また、本発明は、水滴へと成長する前の水蒸気の分布を高感度で捉えることができる。また、本発明は、従来の高層大気状態の測定法に比べて、簡便かつ安価な方法で上層の大気の様子を知ることができる。
【図面の簡単な説明】
【図１】本発明に関する大気計測システム１００の概略構成図。
【図２】本発明に関する大気計測システム１００のフローチャート。
【図３】第１データファイル７１の説明図。
【図４】観測点から見上げたときの空（天球面）を示す図。
【図５】大気計測システム１００における相関処理装置４０での処理を示す説明図。
【図６】大気計測システム１００における相関処理装置４０での処理を主に示すフローチャート。
【図７】第２データファイル７２の説明図。
【図８】相互相関位相ΔΦ（ｔ）と、相関位相のゆらぎσ_Φ（ｔ）との対応関係を示す図。
【図９】水蒸気の二次元分布図を作成する際の天球面を示す図。
【図１０】第３データファイルの説明図。
【符号の説明】
１０ 第１衛星追跡アンテナ
１５ 第１受信装置
２０ 第１衛星追跡アンテナ
２５ 第２受信装置
３０ 軌道予測計算機
４０ 相関処理装置
５０ データ解析装置
６０ 衛星
７０ 記憶装置
７１ 第１データファイル
１００ 大気計測システム[0001]
BACKGROUND OF THE INVENTION
The present invention relates to an atmospheric measurement system and method, and more particularly, to determine the distribution of water vapor and raindrops in the atmosphere at a low altitude orbit (altitude several kilometers to several thousand km) or a medium altitude orbit (altitude, about several thousand to 10,000 km). The present invention relates to an atmospheric measurement system and method for measuring in a simple and short time using radio waves radiated from a satellite orbiting the earth.
[0002]
[Prior art]
In general, as a method for examining the distribution of water vapor and raindrops at low or medium altitudes of several kilometers from the ground surface, for example, a method using a visible light image or infrared image taken by a weather satellite, a reflection of radio waves by a weather radar, etc. There are a method of measuring waves, a method of directly measuring by blowing a balloon or an airplane equipped with weather observation equipment, a method of measuring the amount of radio waves emitted from the atmosphere with a water vapor radiometer, and the like. In addition, there are a method of monitoring changes in reception intensity using radio waves from a geostationary satellite, a method of measuring arrival time differences (arrival time differences) among a plurality of antennas, and the like.
[0003]
[Problems to be solved by the invention]
However, in each of the above-described methods, it is assumed that it is difficult to detect how an invisible cloud, that is, a mass of water vapor moves due to wind in the upper atmosphere. For example, among the conventional measurement techniques, methods using weather satellite images and methods using weather radar are mainly suitable for detecting raindrop components, but it may be difficult to detect water vapor components before they become raindrops. The In direct measurement using a balloon or an airplane, both water vapor and raindrops can be detected. However, the measurement point is only around the detector, and it takes a long time to perform a wide range measurement. Further, in the method using a water vapor radiometer, both absorbed water vapor and raindrops due to raindrops can be detected, but it is difficult to separate them.
[0004]
Here, a differential radiometer has been proposed in which the contribution of the water vapor component and the raindrop component can be separated. However, even when this differential radiometer is used, it is assumed that it is very difficult to detect the water vapor component when there are many raindrop components. The method of measuring the arrival time difference by receiving radio waves from geostationary satellites with multiple antennas has high sensitivity to fluctuations in the water vapor component, but the position of the radio wave source is fixed on the celestial sphere. It is difficult to make a wide range of measurements.
[0005]
In view of the above, one object of the present invention is to provide an atmospheric measurement system and method that can easily and accurately detect the flow of air from the ground at low to medium altitudes over the ground. Another object of the present invention is to provide an atmospheric measurement system and method capable of capturing with high sensitivity the distribution of water vapor before growing into water droplets.
[0006]
[Means for Solving the Problems]
In the present invention, the difference in arrival time of satellite radio waves having high sensitivity to fluctuations in the water vapor component has been extended to a method of measuring using a non-stationary satellite signal. In the present invention, instead of beacon radio waves from geostationary satellites, unmodulated waves such as beacon waves output by non-geostationary satellites, downlink user link signals (customer signals), downlink feeder link signals (control signals), and the like Use modulation waves. This makes it possible to measure a wide range of water vapor distributions that could not be performed because the position of the satellite is constant on the celestial sphere in the conventional method. Moreover, as a non-geostationary satellite, a satellite group used in a low orbit earth orbit satellite system or a medium orbit earth orbit satellite system for satellite communication, which has been rapidly developed in recent years, is used. In this satellite group, one or more satellites can always be seen on the celestial sphere, and since they move at high speed on the celestial sphere, measurement of a wide range of water vapor distribution can be realized in a short time.
[0007]
According to the first solution of the present invention,
In an atmospheric measurement system that measures atmospheric water vapor distribution based on radio waves received from non-geostationary satellites by multiple antennas,
An orbit prediction calculator that calculates the satellite's orbit, instructs each antenna to point to the satellite, and calculates the arrival time difference of the received radio waves due to the direction and position of the antenna and the satellite's orbit;
First and second antennas for capturing a satellite based on instructions from the orbit prediction computer and then tracking the satellite;
First and second receiving devices for outputting first and second received data based on received signals from the first and second antennas, respectively;
By measuring at a plurality of satellite positions, the received data from the first and second receiving devices are corrected with the arrival time difference calculated by the orbit prediction computer to calculate first and second corrected received data; A correlation processing device for calculating a phase difference between the first and second corrected received data at each position on the sky;
By measuring at a plurality of satellite positions, the phase fluctuation at each position on the celestial sphere is calculated based on the time variation of the phase difference calculated by the correlation processing device, and the phase fluctuation obtained at each measurement is spatially A data analysis device for obtaining a two-dimensional water vapor distribution by interpolating automatically,
An atmospheric measurement system comprising:
[0008]
According to the second solution of the present invention,
In an atmospheric measurement method for measuring an atmospheric water vapor distribution based on radio waves received from a non-geostationary satellite by first and second antennas,
An orbit prediction calculator calculates a satellite orbit and directs the first and second antennas to point at the satellite;
The first and second antennas capture satellites based on instructions from the orbit prediction computer, and then track the satellites,
The first and second receiving devices output first and second received data based on the received signals from the first and second antennas, respectively.
The orbit prediction calculator calculates the arrival time difference of the received radio waves due to the direction and position of the antenna and the orbit of the satellite,
The correlation processing device corrects the reception data from the first and second receiving devices by the arrival time difference calculated by the orbit prediction computer by measuring at a plurality of satellite positions, and receives the first and second corrected receptions. Calculating the data, and further calculating the phase difference between the first and second corrected received data at each position on the sky,
The data analysis device calculates the phase fluctuation at each position on the celestial sphere based on the time variation of the phase difference calculated by the correlation processing device by measuring at a plurality of satellite positions, and further obtained by each measurement. The two-dimensional water vapor distribution by spatially interpolating the phase fluctuations
An atmospheric measurement method is provided.
[0009]
DETAILED DESCRIPTION OF THE INVENTION
Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings.
FIG. 1 is a schematic configuration diagram of an atmospheric measurement system 100 according to the present invention.
The atmospheric measurement system 100 includes, for example, a first satellite tracking antenna 10, a first receiving device 15, a second satellite tracking antenna 20, a second receiving device 25, an orbit prediction computer 30, a reference signal source 35, a correlation processing device 40, data An analysis device 50, a satellite 60, a storage device 70, and an output device 80 are included. The storage device 70 includes, for example, a first data file 71, a second data file 72, and a third data file 73. The satellite 60 is, for example, a non-stationary satellite that orbits the earth at low altitudes (altitudes from several kilometers to several thousand kilometers) to medium altitudes (altitudes, from several thousand kilometers to 10,000 kilometers). Radiating.
[0010]
The first satellite tracking antenna 10 and the second satellite tracking antenna 20 are antennas for receiving beacon radio waves from the non-stationary satellite 60. The antennas 10 and 20 are installed, for example, separated by a distance d. This distance d will vary depending on the size of the atmospheric structure to be detected. The distance d can be set to about 100 m as an example, but this distance can be set as appropriate. In this example, the antennas 10 and 20 are of the same standard and track the movement of the satellite 60. The first and second receiving devices 15 and 25 are connected to the antennas 10 and 20, and are further connected to the correlation processing device 40 by wire or wirelessly. The first receiving device 15 and the second receiving device 25 are receivers of satellite radio waves (beacon waves), for example, amplifying and frequency converting received signals, converting them into signals that can be taken into a computer, and outputting them.
[0011]
The reference signal source 35 generates a synchronization signal for operating the first receiving device 15 and the second receiving device 25 in synchronization. The reference signal source 35 is connected to the first and second receiving devices 15 and 25 by, for example, wired or wireless, and operates the first receiving device 15 and the second receiving device 25 in synchronization. Here, in order to obtain the arrival time difference (arrival time difference, delay) between the signals received by the antennas 10 and 20, for example, the local part used in the frequency conversion included in the first receiving device 15 and the second receiving device 25. The oscillation signal needs to be synchronized with the reference signal.
[0012]
The orbit prediction computer 30 stores, for example, data on the position and movement of the satellite in advance, and based on the data, changes in reception frequency (Doppler shift) and arrival time difference due to the directions of the antennas 10 and 20 and the movement of the satellite 60. Calculate data for correction of changes. The orbit prediction computer 30 also calculates the orbit of the satellite 60 and indicates the direction in which the antennas 10 and 20 are directed. In addition, the orbit prediction computer 30 obtains a correction amount for the change in frequency due to the movement of the satellite 60 and the change in radio wave arrival time difference. The correlation processing device 40 obtains the arrival time difference of satellite radio waves based on the signals received by the first and second receiving devices 15 and 25 and the data from the orbit prediction computer 30, for example. For example, the data analysis apparatus 50 estimates the water vapor distribution in the atmosphere from the measured arrival time difference and performs visualization. For example, the data analysis device 50 calculates a two-dimensional water vapor distribution. The storage device 70 can read / write data of each file from each device such as the second receiving devices 15 and 25, the correlation processing device 40, and the trajectory prediction computer 30. The output device 80 outputs, for example, the two-dimensional water vapor distribution calculated by the data analysis device 50 to an appropriate display device, recording medium, or other device.
[0013]
FIG. 2 is a flowchart of the atmospheric measurement system 100 according to the present invention.
For example, the trajectory prediction computer 30 calculates the trajectory of the satellite 60 (from the appearance from the horizon to the immersion to the horizon) (S101). At this time, the orbit prediction computer 30 instructs the antennas 10 and 20 to point the antennas 10 and 20 in the direction of the calculated appearance position of the satellite 60 from the horizon. As indicated by the orbit prediction computer 30 in step S101, each antenna 10, 20 directs the antenna to the appearance position of the satellite 60 and waits for the satellite 60 (S103). Next, the antennas 10 and 20 determine whether or not the satellite 60 has appeared (S105). After the satellite 60 has appeared, the antennas 10 and 20 track the satellite 60, and the first and The second receiving devices 15 and 25 transmit signals from the satellite 60 (for example, beacon waves, unmodulated waves such as downlink user link signals (customer signals), downlink feeder link signals (control signals), etc.) Reception of a wave or both of them is continuously received (S107).
[0014]
The orbit prediction computer 30 calculates Doppler correction data for correcting the change due to the Doppler shift of the frequency due to the movement of the satellite 60 tracked by each of the antennas 10 and 20 in step S107, and uses the data for the first and second receivers. 15 and 25. The first and second receiving devices 15 and 25 correct the Doppler shift change of the beacon signal based on the Doppler correction data (S109). Here, the first and second receiving devices 15 and 25 can perform Doppler correction by adjusting the tuning of the reception frequency by the Doppler shift frequency. Further, the orbit prediction computer 30 calculates the arrival time difference between the signals received from both antennas 10 and 20 in consideration of the position and angle between the satellite 60 and the antennas 10 and 20 (S111). Note that the processing of these steps S109 and S111 can also be performed in the correlation processing device 40. In addition, when the distance between the antennas 10 and 20 is relatively short, the difference in Doppler shift may be negligible. In this case, the Doppler shift correction process (S109) may be omitted.
[0015]
The first and second receiving devices 15 and 25 respectively receive the first and second received signals that have been subjected to Doppler correction processing in step S109 (if the processing is omitted, the first and second received signals remain as they are). Is transmitted to the correlation processing device 40 in a wired or wireless manner. Further, the orbit prediction computer 30 transmits the arrival time difference caused by the movement of the satellite itself calculated in step S111 to the data correlation processing device 40. The correlation processing device 40 corrects the first and second received signals from the first and second receiving devices 15 and 25 with arrival time difference data from the trajectory prediction computer 30. The correlation processing device 40 uses the corrected first and second received data as data (satellite identifier, azimuth of the satellite 60) on the position of the satellite 60 on the celestial sphere previously calculated by the orbit prediction computer 30. Angle, elevation angle) and measurement time data (time) and the like, a first data file 71 is created and stored in the first data file 71 of the storage device 70 (S113). As a first cause, the arrival time difference changes due to a change in the distance difference between the satellite 60 and the antennas 10 and 20 due to the movement of the satellite 60. In addition, the arrival time difference is a second cause. The propagation path of the radio wave between the satellite 60 and the antennas 10 and 20 is changed due to the movement of the satellite 60, and the fluctuation of the atmospheric water vapor amount in the propagation path for each place. Reflect and change. The change in arrival time difference due to the first cause can be estimated by estimating the position of the satellite for each measurement time using an orbital element or the like. In this way, only the change in arrival time difference due to the second cause remains.
[0016]
FIG. 3 is an explanatory diagram of the first data file 71. The first data file 71 includes, for example, a satellite identifier, time, satellite azimuth, satellite elevation, first reception data, and second reception data. Here, versatile position data for indicating the position of each satellite 60 at each measurement time is represented by “satellite azimuth” and “satellite elevation angle”. In this example, as the format of the first data file 71, time, satellite azimuth, and elevation are added to each received data (for each sample), but the data is, for example, tens of thousands of samples / second. Therefore, if additional data (time, azimuth angle of satellite, elevation angle) is attached to each sample, the processing and the amount of data become enormous. Therefore, data may be blocked (for example, a block every second), and time, satellite azimuth, and elevation may be added to the head of each block. Then, after processing the data (for example, after correlation processing), when time, satellite azimuth, and elevation are required, they can be obtained by interpolation calculation using a function such as a linear function based on the information at the head of the block.
[0017]
Next, the antennas 10 and 20 determine whether or not the satellite 60 is immersed in the horizon (S115). Here, if the satellite 60 is not immersed, the process returns to step S109 again, and thereafter, steps S111 and S113 are repeated to add data to the first data file 71. On the other hand, if the satellite 60 is immersive in step S115, it is determined whether the measured number of satellites 60 satisfies the required number (S117). If the required number is not satisfied, the process returns to step S101 again, and the above processing is repeated for each satellite that appears.
[0018]
Next, when the number of satellites 60 measured in step S117 satisfies the required number, the correlation processing device 40 reads the first data file 71 created in step S113, and further, the first and second receiving devices 15 and 25. The arrival time difference between signals per unit time (for example, every 0.1 second) is calculated for the received data subjected to the correction processing from (S118: details will be described later). When the received signal is a non-modulated wave (for example, a signal that vibrates sinusoidally), the received signals of the first satellite tracking antenna 10 and the second satellite tracking antenna 20 are multiplied and integrated by unit time. The arrival time difference can be obtained as an amount called a phase difference of sinusoidal vibration. On the other hand, even if the received signal is a modulated wave or both a non-modulated wave and a modulated wave, the received signal is a signal in which a sine wave is superimposed. The amount of phase difference can be obtained as
[0019]
The data analysis device 50 calculates the water vapor distribution / phase fluctuation (fluctuation of water vapor distribution) at each position on the celestial sphere based on the stored arrival time difference data and satellite position data on the celestial sphere (S119: details) Later). For example, the water vapor distribution is obtained by integrating the time variation of the arrival time difference. Since the data distribution device 50 obtains water vapor distributions corresponding to different orbits on the celestial sphere by a plurality of measurements at a plurality of satellite positions as described above, the data analysis device 50 spatially interpolates the results obtained in each measurement. Thus, a two-dimensional water vapor distribution is obtained (S121: details will be described later).
[0020]
Hereinafter, the processes of steps S119 and S121 described above will be specifically described.
(Calculation of arrival time difference in correlation processing device 40: S118)
FIG. 4 is a diagram showing the sky (celestial sphere) when looking up from the observation point.
The celestial sphere includes, for example, a horizon 600 indicated by a large circle in the drawing, and orbits 601 and 602 of the satellite 60 indicated by thick solid lines within the celestial sphere surrounded by the horizon 600. Further, the trajectory 602 is divided into, for example, a plurality of small sections (areas indicated by ellipses in the drawing) 603. A representative point 604 of deviation is shown at the (substantially) center or center of gravity of the small section 603. The correlation processing device 40 measures the time difference (phase difference) at which the radio waves radiated from the satellite 60 arrive at the two antennas 10 and 20 for each small section 603.
[0021]
FIG. 5 is an explanatory diagram showing processing in the correlation processing device 40 in the atmospheric measurement system 100.
First, the beacon radio wave s of the satellite 60 received by the first satellite tracking antenna 10 and the second satellite tracking antenna 20. ₁ (T), s ₂ (T) is the signal strength A ₁ And A ₂ , Phase Φ ₁ (T) and Φ ₂ (T), where f is the frequency
s ₁ (T) = A ₁ ・ Sin (2πft + Φ ₁ (T)) (1)
s ₂ (T) = A ₂ ・ Sin (2πft + Φ ₂ (T)) (2)
Thus, it can be expressed as a sine wave signal. Here, t is time. Strictly speaking, the amount of Doppler shift due to the movement of the satellite 60 differs between the antennas 10 and 20, but when the distance between the antenna 10 and the antenna 20 is within a predetermined range (for example, about 100 m), the two antennas 10 are provided. , 20, the Doppler shift due to the movement of the satellite 60 is almost the same, so even if the reception frequency is the same for each of the two antennas 10, 20, the influence can be ignored.
[0022]
Where phase Φ ₁ (T) and Φ ₂ (T) represents the distance from the satellite 60 to the antenna 10 and the antenna 20, respectively, r ₁ , R ₂ , V ₁ , V ₂ (V ₁ ≒ v ₂ ≒ Light speed)
Φ ₁ (T) = 2πf · r ₁ / V ₁ = 2πfτ ₁ (3)
Φ ₂ (T) = 2πf · r ₂ / V ₂ = 2πfτ ₂ (4)
It is expressed as follows. Τ ₁ , Τ ₂ Is a time (propagation time) required for radio waves radiated from the satellite 60 to reach the antenna 10 and the antenna 20.
When the cross-correlation result of these signals is c (t), the following equation (5) is established.
[0023]
[Expression 1]

[0024]
That is, the product of two signals is taken and averaged over time T. When the expressions (1) and (2) are substituted into the expression (5) and the average time T is sufficiently longer than the reciprocal 1 / f of the reception frequency, the following expression (6) is established.
[0025]
[Expression 2]

[0026]
It becomes. Where ΔΦ (t) is the cross-correlation phase, and ΔΦ (t) = Φ ₂ (T) -Φ ₁ (T) = 2πf (τ ₁ −τ ₂ ). When the change in arrival time difference due to satellite movement is corrected, τ ₁ −τ ₂ Represents the difference between “fluctuation of propagation time due to fluctuation of water vapor on the propagation path connecting the satellite 60 to the antenna 10” and “fluctuation of propagation time due to fluctuation of water vapor etc. on the propagation path connecting the satellite 60 to the antenna 20”. The phase difference ΔΦ (t) is also proportional to it. In addition, since ΔΦ (t) cannot be obtained directly from c (t) in equation (5), the received signal of the antenna 20 is a signal whose phase is shifted by 90 degrees.
s ₂ '(T) = A ₂ ・ Sin (2πft + Φ ₂ (T) + π / 2) = A ₂ ・ Cos (2πft + Φ ₂ (T))
And the cross-correlation between this and the equation (1) is calculated. Thereby, the following expression (7) is established.
[0027]
[Equation 3]

[0028]
Next, it calculates | requires as following Formula (8) from (6) Formula and (7) Formula.
ΔΦ (t) = tan ^-1 (C '(t) / c (t)) (8)
[0029]
FIG. 6 is a flowchart mainly showing processing in the correlation processing device 40 in the atmospheric measurement system 100. Here, the description will be made in correspondence with each mathematical formula used when calculating the phase difference ΔΦ (t) between the antenna 10 and the antenna 20 described above.
First, the correlation processing device 40 initializes c (t) and c ′ (t) described above (S201). That is, c (t) = 0 and c ′ (t) = 0. Next, the first receiver 15 receives the beacon radio wave s from the satellite 60 with the antenna 10. ₁ (T) is read from the first data file 71 (S203). Further, the second receiving device 25 receives the beacon radio wave s from the satellite 60 with the antenna 20. ₂ (T) is read from the first data file 71 (S207).
[0030]
Next, the correlation processing device 40 calculates c (t) and c ′ (t) from the data read in steps S205 and S209 based on the following equations (S211).
c (t) = c (t) + s ₁ (T) ・ s ₂ (T)
c ′ (t) = c ′ (t) + s ₁ (T) ・ s' ₂ (T)
[0031]
Here, the correlation processing device 40 determines whether or not the calculated number of data satisfies the required number (S213). If the required number is not satisfied, the correlation processing device 40 returns to steps S203 and 207 again, and repeats the data reading and calculation processing. On the other hand, when the required number is satisfied in step S213, the correlation processing device 40 divides c (t) and c ′ (t) calculated in step S211 by the number of data to obtain c (t) and c ′ (t ) Is obtained (S215). Next, based on the respective averages of c (t) and c ′ (t) calculated in step S215, the phase difference according to the equation (8)
ΔΦ (t) is obtained (S217).
[0032]
FIG. 7 shows an explanatory diagram of the second data file 72. In this example, satellite identifier, time, satellite azimuth, satellite elevation, phase difference Φ (arrival time difference), fluctuation σ _Φ including. Here, the correlation processing device 40 performs fluctuation σ _Φ Other data is written to the second data file.
[0033]
(Calculation of phase fluctuation (fluctuation of water vapor distribution) in the data analysis device 50: S119)
The data analysis device 50 refers to the second data file 72 and further changes the arrival time difference (for example, deviation σ) based on the read phase difference Φ corresponding to the representative point for each small area. _Φ (T)) is calculated.
Here, the deviation σ indicating the change in arrival time difference _Φ (T) will be described.
[0034]
Since the process of step S119 aims to detect local non-uniformity of water vapor in the atmosphere, a systematic change in the arrival time difference from the measured amount (arrival time difference) (for example, uniform over time) Fluctuations from the average (ie, standard deviation). Here, the systematic change is, for example, a large fluctuation caused by a layer of water vapor and air and measured between the appearance of the satellite 60 and the immersion. This variation can be removed by passing a signal corrected by a high-pass filter or the like by a predetermined frequency or more, or by using an approximate expression such as a predetermined first-order, second-order or third-order expression. When the standard deviation is obtained for each small section 603 of the orbit 602 of the satellite 60, this amount corresponds to a spatial fluctuation such as a water vapor amount in a local portion on the celestial sphere (reference document: G. Brussaard and PA Watson, "Atmospheric modeling and millimetre wave propagation, Chapman & Hall, 1995, p.54, etc.).
[0035]
When the above operation is performed along the orbits 601 and 602 of the satellite 60 and along the orbits of various satellites, the spatial amount of water vapor in various places on the celestial sphere (two-dimensional space) is determined. Fluctuation is obtained.
Fluctuation of arrival time difference σ _Φ Since (t) is equivalent to the fluctuation of the cross-correlation phase ΔΦ (t), the fluctuation of the cross-correlation phase ΔΦ (t) is calculated from the following equation (9).
[0036]
[Expression 4]

[0037]
Here, T is an interval in which the data is averaged. When the angular movement speed of the satellite 60 on the celestial sphere viewed from the observation point is u [radian / sec] and the required resolution of the two-dimensional image is Δθ, T = Δθ / U
Given by. Note that if the required resolution is too small, the reliability of the data is lowered, so there is an optimum value and range (for example, about Δθ = 1 [deg]). This value or range can be appropriately determined in advance according to the antenna position, weather conditions, region, climate, and the like. The data analysis device 50 applies fluctuation σ to the corresponding area of the second data file 72. _Φ Write.
[0038]
FIG. 8 shows the cross-correlation phase ΔΦ (t) and the correlation phase fluctuation σ. _Φ It is a figure which shows a corresponding relationship with (t).
The cross-correlation phase ΔΦ (t) is calculated using, for example, the above-described equations (6) and (7). The horizontal axis is time t, and the horizontal axis is for averaging data. It is divided every T time which is a section of. Note that the satellite 60 moves in a plurality of small sections 603 included in the orbit 602 in T time. Also, correlation phase fluctuation σ _Φ (T) is calculated by using, for example, the above-described equation (9). The horizontal axis represents time t, and the vertical axis corresponds to the representative point 604 of the deviation included in the small section 603. The value at the position (circle mark in the figure) is shown.
[0039]
(Calculation of two-dimensional water vapor distribution in the data analysis device 50: S121)
FIG. 9 is a diagram showing a celestial sphere when creating a two-dimensional distribution map of water vapor.
The celestial sphere includes, for example, a horizon 600, a measurement representative point (marked with a circle in the figure) 610, a satellite orbit (solid line including the mark in the figure) 630, and a grid intersection 620. The grid intersection 620 is a point for obtaining a two-dimensional distribution by using, for example, the above-described interpolation processing.
[0040]
The distribution of spatial fluctuation measurement points such as the amount of water vapor on the celestial sphere is not uniform, but is localized in a portion along the orbit of the satellite 60. In order to create a two-dimensional distribution chart, first, the celestial sphere is partitioned into a lattice shape, and the data analysis device 50 reads the data stored in the second data file 72 and converts the position data into a lattice-like two-dimensional coordinate. Then, a third data file is created and stored. Further, the data analysis device 50 reads the second data file, and estimates the fluctuation value at the grid intersection 620 from the stored data such as the fluctuation value of the representative point 610 of the measurement. This process is performed by a two-dimensional interpolation algorithm. As the interpolation method, for example, a general-purpose algorithm such as a spline interpolation method in a two-dimensional space or a cubic convolution method can be used.
[0041]
FIG. 10 is an explanatory diagram of the third data file. In this example, fluctuations with respect to the X and Y coordinates are stored.
In the atmospheric measurement system 100 described above, the satellite 60 is tracked using two antennas (the first satellite tracking antenna 10 and the second satellite tracking antenna 20), but the number of antennas is not limited to this. Many more antennas can be used. Thereby, measurement accuracy and measurement efficiency can be increased. In addition, as an application of the present invention, it can be expected that the turbulence of the atmosphere in the most advanced part of the weather front that cannot be captured as cloud movements will be detected in detail and used for earlier prediction of weather disasters.
[0042]
【The invention's effect】
According to the present invention, as described above, atmospheric flow at an altitude of several kilometers from the ground can be detected in a wide range, with high accuracy and simply. In addition, the present invention can capture the distribution of water vapor before growing into water droplets with high sensitivity. Further, the present invention can know the state of the upper atmosphere by a simple and inexpensive method compared to the conventional measurement method of the upper atmosphere condition.
[Brief description of the drawings]
FIG. 1 is a schematic configuration diagram of an atmospheric measurement system 100 according to the present invention.
FIG. 2 is a flowchart of the atmospheric measurement system 100 according to the present invention.
3 is an explanatory diagram of a first data file 71. FIG.
FIG. 4 is a diagram showing the sky (celestial sphere) when looking up from an observation point.
FIG. 5 is an explanatory diagram showing processing in the correlation processing device 40 in the atmospheric measurement system 100.
6 is a flowchart mainly showing processing in the correlation processing device 40 in the atmospheric measurement system 100. FIG.
7 is an explanatory diagram of a second data file 72. FIG.
FIG. 8 shows cross-correlation phase ΔΦ (t) and correlation phase fluctuation σ. _Φ The figure which shows the correspondence with (t).
FIG. 9 is a view showing a spherical surface when creating a two-dimensional distribution map of water vapor.
FIG. 10 is an explanatory diagram of a third data file.
[Explanation of symbols]
10 First satellite tracking antenna
15 First receiver
20 First satellite tracking antenna
25 Second receiver
30 Orbit prediction computer
40 correlation processor
50 Data analyzer
60 satellites
70 storage device
71 First data file
100 Atmospheric measurement system

Claims (10)

In an atmospheric measurement system that measures atmospheric water vapor distribution based on radio waves received from non-geostationary satellites by multiple antennas,
An orbit prediction calculator that calculates the satellite's orbit, instructs each antenna to point to the satellite, and calculates the arrival time difference of the received radio waves due to the direction and position of the antenna and the satellite's orbit;
First and second antennas for capturing a satellite based on instructions from the orbit prediction computer and then tracking the satellite;
First and second receiving devices for outputting first and second received data based on received signals from the first and second antennas, respectively;
By measuring at a plurality of satellite positions, the received data from the first and second receiving devices are corrected with the arrival time difference calculated by the orbit prediction computer to calculate first and second corrected received data; A correlation processing device for calculating a phase difference between the first and second corrected received data at each position on the sky;
By measuring at a plurality of satellite positions, the phase fluctuation at each position on the celestial sphere is calculated based on the time variation of the phase difference calculated by the correlation processing device, and the phase fluctuation obtained at each measurement is spatially A data analysis device for obtaining a two-dimensional water vapor distribution by interpolating automatically,
Atmospheric measurement system with The orbit prediction computer further calculates Doppler correction data for correcting a frequency Doppler shift due to satellite movement,
The said 1st and 2 receiving apparatus further correct | amends the Doppler shift change part with respect to receiving data based on the data for Doppler correction calculated by the said orbit prediction computer, The output is Claim 1 characterized by the above-mentioned. Atmospheric measurement system. 3. The correlation processing device calculates an arrival time difference as a phase difference of sinusoidal vibration by multiplying the received data from the first and second receiving devices and integrating in unit time. The atmospheric measurement system described in 1. 4. The data analysis device according to claim 1, wherein the data analysis device calculates a fluctuation from an average based on the phase difference calculated by the correlation processing device, thereby obtaining a variation in arrival time difference for each orbit of the satellite. The atmospheric measurement system according to any one of the above. 5. The atmospheric measurement system according to claim 1, wherein the data analysis device further excludes a temporally uniform change or systematic change in arrival time difference from the calculated fluctuation. 6. The atmospheric measurement system according to claim 1, further comprising a display device that visually displays a two-dimensional distribution of water vapor calculated by the data analysis device. In an atmospheric measurement method for measuring an atmospheric water vapor distribution based on radio waves received from a non-geostationary satellite by first and second antennas,
An orbit prediction calculator calculates a satellite orbit and directs the first and second antennas to point at the satellite;
The first and second antennas capture satellites based on instructions from the orbit prediction computer, and then track the satellites,
The first and second receiving devices output first and second received data based on the received signals from the first and second antennas, respectively.
The orbit prediction calculator calculates the arrival time difference of the received radio waves due to the direction and position of the antenna and the orbit of the satellite,
The correlation processing device corrects the reception data from the first and second receiving devices by the arrival time difference calculated by the orbit prediction computer by measuring at a plurality of satellite positions, and receives the first and second corrected receptions. Calculating the data, and further calculating the phase difference between the first and second corrected received data at each position on the sky,
The data analysis device calculates the phase fluctuation at each position on the celestial sphere based on the time variation of the phase difference calculated by the correlation processing device by measuring at a plurality of satellite positions, and further obtained by each measurement. An atmospheric measurement method that obtains a two-dimensional water vapor distribution by spatially interpolating phase fluctuations. The orbit prediction computer further calculates Doppler correction data for correcting a frequency Doppler shift due to satellite movement,
The said 1st and 2 receiving apparatus further correct | amends the Doppler shift change part with respect to receiving data based on the data for Doppler correction calculated by the said orbit prediction computer, The output is Claim 7 characterized by the above-mentioned. Atmospheric measurement method. The orbit of the satellite in the celestial sphere is divided into a plurality of small regions, and the phase difference at each representative point with respect to the plurality of orbits is measured with the center or center of gravity of the small region as a representative point. The atmospheric measurement method described in 1. 10. The atmospheric measurement method according to claim 7, wherein any one of a non-modulated wave, a modulated wave, or both of these radio waves is used as a received signal from a non-geostationary satellite.

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