JPH06249970A - Visibility measuring method, rainfall/snowfall deciding method, method and system for measuring intensity of rainfall/snowfall - Google Patents

Abstract

PURPOSE:To realize concurrence in the observation by utilizing the correlational characteristics of histogram of the number of A/D converted data of optical signal projected into the air, reflected and scattered in the air, and then received for each strength of received light. CONSTITUTION:A light projector 1 constantly projects an optical signal, subjected to luminance modulation by a modulator 3, into the air and the optical signal reflected or scattered by floating substances or raindrops impinges on a light receiver 2. Output signals from the light receiver 2 are demodulated by a demodulator 4 in synchronism with a modulation signal delivered from the modulator 3 and then delivered through an A/D converter 5 to a CPU 6. The CPU 6 reads in a conversion data one by one from the converter and stores the data in a memory 7 while classifying according to the intensity of received light. The CPU 6 then totalize the A/D converted data, detects the intensity of received light based on a histogram data thus obtained, operates a rain/snow discrimination coefficient defined by the ratio between the maximum intensity of received light and the number of A/D converted data, and then decides rainfall or snowfall.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a method of receiving reflected and scattered light in the air of an optical signal emitted in the air, and performing visibility measurement, rainfall / snow discrimination, and rainfall / intensity measurement by the received light signal, and a method thereof. It relates to a device to be implemented.

[0002]

2. Description of the Related Art Conventionally, as a visibility measuring method, an optical signal is radiated in the air, and reflected and scattered light in the air of the optical signal is received.
A method of calculating a visibility value by a DC level of the received light signal obtained by averaging received light intensities of received light signals (received light signals) is known.

In addition, as a method of determining rainfall during rainfall,
Conventionally, a pair of comb-shaped electrodes are combined so that the comb teeth are alternately arranged, and it is raining or snowing by monitoring the formation of a bridge between the pair of electrodes due to the snow grains depending on the energization state between the pair of electrodes. A method for discriminating is known.

Further, as a method of measuring rainfall and snowfall intensity, conventionally, there is known a method of calculating rainfall or snowfall intensity per unit time by using a rain gauge or a power meter to calculate the rainfall or snowfall intensity. is there.

[0005]

According to the above conventional method, visibility measurement, rainfall / snow discrimination, and rainfall / snow intensity measurement are performed.
It is necessary to use separate means, and if the above three types of observations are performed simultaneously, not only will the equipment become bulky, but each measurement will be performed on the basis of separate data. When changes are rapid,
There is a problem that it is difficult to synchronize observations (measurements at the same time).

Therefore, the present invention provides a method capable of performing visibility measurement, rainfall snowfall determination, and rainfall snowfall intensity measurement, and an apparatus for carrying out the method, based on one type of measurement data. It is an issue.

Further, regarding each measurement, in the conventional technique, in the conventional visibility measuring method, since the average processing of the received light intensity is usually performed by integrating the received light signal under a constant time constant, Visibility changes faster than the time determined by the time constant cannot be detected, and if the time constant is set to a short time in order to measure the fast-changing visibility, the noise component of the measuring device added to the change in the integrated value of the received light signal will be detected. (The noise is an irregular signal, so if it goes through a circuit with a long time constant, its components will decrease due to the canceling effect and the S / N ratio will improve, but if the time constant is short, the canceling effect will decrease. S / N ratio decreases, and S of the received light signal
Since the / N ratio decreases, the measurement accuracy deteriorates particularly in the visibility measurement when the visibility is good with a gradual change in visibility. Further, in the conventional method, the intensity of the received light signal due to rainfall or snow, which has little relation to the visibility value, is included in the average value of the received light intensity, so that the measurement error increases.

Therefore, in the present invention, in the visibility measurement, even when the visibility change is fast, it is possible to measure the visibility by following the change, and also when the visibility change is gradual, highly accurate measurement is possible. An object of the present invention is to obtain a visibility measuring method and a device for implementing this method.

Further, in the conventional rain / snow discrimination method using a pair of electrodes, the accuracy of rainfall / snow discrimination is affected by the distance between the pair of electrodes. That is, if the interval between the electrodes is widened, a bridge between the electrodes is less likely to be formed due to snowfall when the snow grains are fine, and it becomes difficult to determine the snowfall especially in the early stage of snowfall. Then, the inter-electrode bridge is formed even if it is raining or in thick fog, so that it is impossible to discriminate between rainfall and snowfall. As described above, the conventional rain / snow determination method has a problem that the rain / snow determination cannot be determined at the initial stage of precipitation regardless of the state of rainfall or snowfall.

Therefore, the present invention determines the rainfall and snowfall in the initial stage (beginning of snowfall) regardless of the state of rainfall and snowfall.
An object of the present invention is to obtain a rainfall / snowfall determination method capable of reliably determining rainfall / snowfall and a device for implementing this method.

Further, according to the conventional method of measuring rainfall and snow intensity using a rain gauge or a snow cover, not only it is necessary to measure with a separate measuring device during rainfall and during snowfall, but also during a certain period of rainfall or snowfall. Since it is necessary to measure the amount of time and convert this amount to intensity, the measurement time becomes longer, and it is impossible to measure the rainfall snowfall intensity that follows the change, especially when the change in rainfall or snowfall is severe. Become.

Therefore, according to the present invention, it is possible to measure both the rainfall intensity and the snowfall intensity by the same measuring means, and even if the rainfall or the snowfall changes drastically, the change can be reliably followed. A possible method of measuring the amount of rainfall and snowfall,
It is an object to obtain a device for carrying out this method.

A further object of the present invention is to obtain a system that can perform visibility measurement, determination of rainfall and snowfall, and intensity measurement thereof by implementing the method described above.

[0014]

In order to solve each of the problems described above, the present invention A / D-converts the received light signal of the reflected scattered light in the air of the optical signal projected in the air and obtains it by this. The histogram showing the number of A / D converted data classified by received light intensity created by distributing and aggregated the A / D converted data according to the received light intensity is utilized by utilizing the characteristics that correlate with the visibility value, the difference in rainfall and snowfall, and the rainfall and snowfall intensity. Visibility measurement, rainfall / snow discrimination, and rainfall / snow intensity measurement are performed.

[0015]

The inventor projects an optical signal in the air, receives the reflected and scattered light of the optical signal in the air, A / D-converts the received light signal, and receives the A / D-converted data thus obtained. The following findings were obtained by analyzing the histogram created by sorting by strength.

FIG. 4A shows the received light intensity (L) of the received light signal versus the received light time (T), which directly represents an analog signal output from the light receiving means and proportional to the received light intensity. . The portion P exhibiting a particularly strong level in this light receiving characteristic is due to the light receiving signal reflected by raindrops or snow grains and incident on the light receiving means during rainfall or snowfall, and the level fluctuation of other portions is generally This is due to the noise of the measuring device and the noise caused by the back light received by the light receiving means (light incident other than the reflection and scattering of the projection light signal).

Further, the above-mentioned strong level portion P appears as a stronger level during snowfall than during rainfall. This can be easily understood because the reflection by snow grains is stronger than the reflection by raindrops.

Further, the fog that influences the visibility is generated by extremely small water droplets floating in the air. Considering a relatively narrow space which is the visual field of the light receiving means and a relatively short measurement time, the fog density Is substantially constant, the received light intensity due to the incidence of reflected and scattered light due to fog on the light receiving means has a level L1 (a DC level of a received light signal obtained by a conventional visibility measuring method) that is substantially averaged in other portions except the strong level portion P. It corresponds to the level).

The above received light signals are A / D converted, and the A / D change data obtained by this is aggregated for each received light intensity, and the relationship between the received light intensity (L) and the total number (N) of the A / D converted data is shown. When represented, a histogram as shown in FIG. 4B is obtained (this data is referred to as histogram data). In FIG. 4B, the axis scale on the light receiving intensity (L) side is averaged to facilitate understanding. The axis scale is drawn slightly wider than the axis scale of FIG.

As shown in FIG. 4 (B), the maximum number Np of A / D converted data (N) is summed up in the average level L1 and the received light intensity (L) is increased or decreased with the average level L1 as the center. The number (N) is distributed in a decreasing direction, and when there is rainfall or snow, it is wide in the direction of high light reception level and narrow in the direction of low light reception (solid line), and when there is no rainfall or snow, it is the above. They are evenly distributed in the increasing / decreasing direction of the received light intensity (L) around the average level L1 (the broken line on the high level side, the low level side is the same as during rain or snow).

When there is rainfall or snowfall,
As rainfall or snowfall increases, A / on the higher level side
The slope of the distribution curve of the number of D-converted data (N) becomes gentle, and the level of the maximum received light intensity Lp in which the A / D-converted data is distributed becomes higher when snowing than when it rains.

The following facts have been found from the above characteristics appearing in the histogram data.

(1) The fog density has a correlation with the received light intensity L1 in which the maximum number A / D converted data Np is tabulated, and the visibility value is determined by the fog density. Therefore, the visibility value is the above received light intensity. It can be calculated from L1.

(2) If there is rainfall or snowfall, the symmetry of the histogram data with the received light intensity L1 as the target axis is broken. Therefore, by judging the symmetry of the histogram data, it is determined whether there is rain or snowfall. It becomes possible to judge whether.

(3) The maximum received light intensity Lp appearing in the histogram data is at a higher level during snowfall than during rainfall. It is possible to distinguish rainfall and snowfall by utilizing this characteristic.
The maximum received light intensity Lp varies depending on the intensity of rainfall or snowfall, but the inventors have found that the maximum received light intensity Lp and the distribution width of the asymmetric portion S of the histogram data (for this distribution width, It will be clarified in the description of the embodiments)) and the ratio of
It has been confirmed that it is possible to distinguish between rainfall and snow regardless of the severity of rainfall or snowfall.

(4) When the intensity of rainfall or snowfall increases,
As described above, the distribution curve on the higher level side of the received light intensity L1 of the histogram data becomes gentle, which means that the asymmetrical portion S appearing in the histogram data has some correlation with the intensity of rainfall or snowfall. is doing. As a result of examining various correlations with respect to the asymmetrical portion S, the inventor found that the number of D / A converted data for each level (Lk) of the received light intensity appearing in the asymmetrical portion S (symmetrical portion (portion below the broken line ) Number excluding the number of
It was found that the sum (ΣLk · ΔNk) of the product (Lk · ΔNk) of k) and each level (Lk) has the strongest correlation with the intensity of rainfall or snowfall. Therefore, the rainfall and snowfall intensity can be measured from this correlation.

As described above, according to the present invention, the visibility value, the rainfall snowfall determination, and the rainfall snowfall intensity can be simultaneously obtained from one histogram data.

[0028]

1 is a block diagram showing an embodiment of the present invention, in which 1 is a projector, 2 is a light receiver, 3 is a modulator, 4 is a demodulator, 5 is an A / D converter, 6 is a CPU, Reference numeral 7 is a memory, 8 is a recording / display device, and 9 is a temperature sensor.

The light projector 1 is a light projecting means for radiating a measurement optical signal toward the air, and comprises a light emitting element, a drive source for the light emitting element, and an optical system such as a light projecting lens.

The light receiver 2 is a light receiving means for receiving the reflected and scattered light in the air of the optical signal emitted from the light projector 1, and is composed of an optical system such as a light receiving element and a light receiving lens.

In the light receiving operation of the light receiver 2, the modulator 3 constitutes a modulator for, for example, brightness-modulating an optical signal emitted from the light projector 1 in order to distinguish between the back light and a normal signal.

The demodulator 4 is a demodulation means for demodulating the signal received by the light receiver 2 in synchronization with the modulation frequency by the modulator 3, and the received light signal is reflected and scattered light of the optical signal emitted from the projector 1. Only the received light signal by is selected.

The A / D converter 5 is an A / D conversion means for A / D converting the received light signal (analog signal) obtained through the demodulator 4 and outputting the A / D converted data of the received light signal. Then, it operates in a high-speed sampling cycle and outputs A / D conversion data for each received light intensity corresponding to the cycle.

The CPU 6 collectively has the control and processing means of the apparatus of the embodiment, and these means are realized by program control, and the main means is to control the light reception signal sent from the A / D converter 5. A / D conversion data totalization processing means 601 (first processing means), visibility value calculation processing means 602 (second processing means) for processing data (histogram data) obtained by the totalization processing means 601. Rainfall / snow determination processing means 603 (third processing means), rainfall / snow intensity calculation processing means 604 (fourth processing means), and record display for recording and / or displaying data obtained by each of these processing means. There are processing means 605 and the like.

The memory 7 stores the data necessary for the processing by the CPU 6 and the data obtained by the processing. The first memory stores the histogram data obtained by the processing of the A / D conversion data totaling by the CPU 6. 701
(First storage means), second memory 702 (second storage means) in which correlation data for visibility value calculation processing is stored in advance, correlation data for rainfall and snowfall intensity calculation processing is stored in advance. There is a certain third memory 703 (third storage means), a fourth memory 704 in which data for determining the number of A / D converted data to be totaled is stored in advance, and other data to be recorded and displayed is stored. Although omitted in the fifth memory 705 and the drawing, there are a memory for temporarily storing data in the middle of processing, a program storage memory for the CPU 6, and the like.

The recording / display unit 8 is a recording / display unit for displaying and / or recording data indicating the visibility value, the rainfall / snow discrimination, and the rainfall / snow intensity calculated by the CPU 6, and is a liquid crystal display panel, a printer, or the like. Composed of.

The temperature sensor 9 is a sensor for detecting the outside air temperature. The outside air temperature detected by the temperature sensor 9 is auxiliary data for the determination when the determination coefficient (described later) indicates the boundary value of the rainfall snowfall in the rainfall snowfall determination process. Used as.

In the histogram data described in FIG. 4B, the maximum received light intensity (hereinafter referred to as the maximum data number level) in which the maximum A / D converted data number Np is tabulated.
The characteristic of the correlation existing between L1 and the visibility value is shown in FIG.
As shown in, when the maximum data number level L1 is taken on the ordinate and the visibility value is taken on the abscissa on the logarithmic coordinate, the characteristic becomes a linear right-downward change. The data showing this correlation is
It is previously stored and stored in the second memory 702.

Further, the total sum ΔV (= ΣLk · ΔNk) of the product of the received light intensity for each received light intensity and the number of A / D converted data in the S portion shown in FIG. 4B and the intensity of rain or snow. As shown in FIG. 6, when the vertical axis is the above summation ΔV and the horizontal axis is the rainfall or snowfall intensity, the correlation characteristic between the two changes to the upper right on the straight line.
The slope of the rainfall intensity characteristic shown in (a) is steeper than that of the snow intensity characteristic shown in (b). The data indicating this correlation is stored and stored in the third memory 703 in advance. The summation ΔV will be referred to as an intensity correlation value.

2A and 2B are flowcharts showing the operation of the apparatus of the embodiment of the present invention, showing the processing in the CPU 6. The operation will be described below according to this flowchart.

From the projector 1, an optical signal whose brightness is modulated by the modulator 3 is constantly radiated toward the air, and this optical signal is a suspended matter (fog, smog, etc.) in the air, raindrops, snow particles, etc. The light is reflected and scattered by and is incident on the light receiver 2, and the light is received by the light receiver 2. The light receiver 2 outputs a light reception signal proportional to the light reception intensity.

The received light signal output from the light receiver 2 is demodulated by the demodulator 4 in synchronization with the modulation signal from the modulator 3,
The digital signal is converted by the A / D converter 5 and sent to the CPU 6.

The CPU 6 reads the A / D converted data of the received light signal sent from the A / D converter 5 one by one (step S1), and reads the read A / D converted data into the first memory according to the received light intensity. It is stored in 701 (step S2).

Next, the CPU 6 determines whether or not the set number of A / D converted data is stored in the first memory 701 (step S3), and if not, the stored number of A / D converted data is set. The above operation is repeated until the number is reached. In this way, the histogram data indicating the number of A / D converted data for each received light intensity is completed. Steps S1 to S1
The processing of S3 is performed by the totalization processing unit 601 included in the CPU 6.

An example of histogram data is shown in FIG.
It shows in (C).

FIG. 7A shows an example of data when there is no rainfall or snowfall, and when the visibility is good (when there is no fog), the data is the received light intensity when the total number (N) of A / D conversion data is (L) has a Gaussian distribution that becomes the largest at the zero level, and when the visibility is poor (when fog occurs), the aggregated number (N) has the largest Gaussian distribution at the received light intensity L1 that correlates with the visibility value. Become. The Gaussian distribution in this case is bilaterally symmetric with respect to the received light intensity (zero or L1) in which the maximum number A / D converted data Np is totaled. This characteristic is that the distribution of A / D converted data appearing in the histogram data is caused by irregular noise (device noise, back light noise, etc.), and when fog occurs, the optical signal is This is a characteristic obtained by the fact that the light-receiving component due to fog appears as a DC component in the signal, because it is continuously reflected by the extremely small water droplets that remain in the air and is suspended, averaged, and received.

7 (B) and 7 (C) are data examples at the time of rainfall and at the time of snowfall, respectively, and the Gaussian distribution in which the total number (N) of the A / D converted data is the largest at the received light intensity L1 which correlates with the visibility value. This is the same as the case of FIG. 7 (A) above, but a characteristic that more A / D converted data is distributed on the level side higher than the received light intensity L1, and when snowing, the level is higher than when raining. The A / D conversion data is distributed up to the range. That is, when it is raining or snowing, the left-right symmetry of the distribution in the case of FIG. 7A is broken. This characteristic is that the raindrops or snowflakes do not stay in the air and pass through the monitoring area of the photodetector 2, so that the light reflected by the raindrops or snowflakes is not averaged and the signal has a level higher than the received light intensity L1. Is detected, and in general, the reflection due to snow grains is stronger than the reflection due to raindrops.

When the histogram data is completed and stored in the first memory 701, the CPU 6 then detects the received light intensity (maximum data number level) L1 in which the maximum A / D conversion data Np is aggregated in the histogram data. Then, the visibility value is calculated from the maximum data number level L1 with reference to the correlation data shown in FIG. 5 stored in the second memory 702 (step S4) (step S4).
5). The visibility value data calculated in this way is displayed on the recording / display device 8 or displayed on the fifth memory 705 for recording.
It is stored in (display memory) (step S6). The above steps S4 to S6 are performed by the visibility value calculation processing means 602 included in the CPU 6.

Next, the CPU 6 detects the minimum received light intensity Ls and the maximum received light intensity Lp from the histogram data (step S7), and a point away from the maximum data number level L1 by a level difference (L1-Ls) in the high level direction. Received light intensity L
4, the calculation of (2L1-Ls) is performed (step S8), and then the number ΔN of A / D converted data tabulated in the received light intensity L4 is detected (step S9).

Next, the CPU 6 determines whether or not the A / D converted data number ΔN is substantially zero (substantially zero means that ΔN indicates a numerical value which can be regarded as a noise component. Means zero.)
Is determined (step S10), and if “ΔN = 0”, it is determined that there is no rainfall or snowfall (step S11),
Data obtained so far (visibility value and zero rainfall and snowfall)
Is displayed on the recording / display unit 8 and / or recorded to end a series of processing (step S18).

When "ΔN ≠ 0", it means that there is rainfall or snowfall, and the CPU 6 causes the maximum received light intensity Lp.
And the rain / snow discrimination coefficient K defined by the ratio of the above-mentioned A / D converted data number ΔN is calculated (step S12), and the rain / snow discrimination coefficient K and the boundary value KS of rainfall and snowfall (see FIG. 8) are calculated. By comparison (step S13), it is determined whether it is raining or snowing (step S14). The processes of steps S7 to S14 described above are performed by the rainfall and snowfall determination processing means 603 included in the CPU 6.

Here, the rain / snow discrimination coefficient K will be described.
FIG. 8 shows the sum of products of each received light intensity Lk in the asymmetric portion S of the histogram data and the number ΔNk of the A / D converted data at the received light intensity Lk (ΣLk · ΔNk). It is clarified by the calculation process) and the rain / snow discrimination coefficient K.

As shown in FIG. 8, the rain / snow discrimination coefficient K becomes a value smaller than a certain value KS at the time of rain and becomes larger than the value KS at the time of snowfall. Therefore, the value KS is set as a boundary value between rainfall and snowfall, and by comparing the boundary value KS with the rain / snow distinction coefficient K obtained from the histogram data, it is possible to determine the rainfall and snowfall.

Further, as is clear from FIG. 8, the rain / snow discrimination coefficient K approaches the boundary value KS and becomes similar in the heavy rain and the light snow.
If (≈KS), it becomes impossible to determine the rainfall and snowfall. Therefore, although not shown in the flow chart of FIG. 2, in such a case, the CPU 6 reads the outside air temperature from the temperature sensor 9, and when the outside air temperature is lower than a constant temperature (for example, 4 ° C.), it is determined that it is snowing. If it is high, it is judged that it is raining.

Further, the determination of rainfall and snowfall can be carried out based on the received light intensity obtained by counting the number 1 / 2Np, which is a half of the maximum number Np of A / D converted data, in the histogram data.

That is, from the histogram data, 1/2
Received light intensity L2 in which Np A / D converted data are aggregated
L3 (provided that L3> L2) is obtained, the difference (L3-L1) and (L1-L2) between the maximum data number level L1 and the above-mentioned two received light intensities L2 and L3 are obtained, and further 2 Difference in received light intensity difference ΔL (= L2 + L3-2L
1) is obtained, it is determined that there is no rainfall or snowfall when the value of the difference ΔL is substantially zero, and it is determined that there is rain or snowfall when the value of the difference ΔL is not substantially zero,
The rain / snow discrimination coefficient K is defined as “K = Lp / ΔL”, and rain / snow is compared with the boundary value KS of rain and snow (however, the value of KS itself is different from the above method) as described above. Is determined.

When it is determined that there is rainfall or snowfall by the above processing, the CPU next receives each received light intensity Lk and the received light intensity Lk for the asymmetric portion S of the histogram data.
A process of calculating a product of the A / D converted data number ΔNk (the number obtained by subtracting the data number of the symmetric portion (the portion below the broken line)) that has been totalized for each of the received light intensities Lk, and totalizing this. That is, the intensity correlation value ΔV (= ΣLk ·
A calculation for obtaining ΔNk) is performed (step S15).

This calculation is performed as follows, for example. That is, in the histogram data shown in FIG. 7 (B) or (C), first, for each received light intensity Lk for which A / D conversion data is aggregated, the difference between each received light intensity Lk and the maximum data number level L1. ΔLk is calculated, and A / D conversion data tabulated into the above respective received light intensities Lk for each of the range from the maximum data number level L1 to the maximum received light intensity Lp and the range from the maximum data number level L1 to the minimum received light intensity Ls The product of the number Nk and the value ΔLk of the difference corresponding to each received light intensity Lk is calculated for each received light intensity Lk and summed, and the total sum V thus obtained is obtained.
When “Vp−Vs” is calculated from p and Vs, this value becomes the intensity correlation value ΔV (= ΣLk · ΔNk).

Next, the CPU 6 refers to the correlation data shown in FIG. 6 stored in the third memory 703 and calculates the intensity of rainfall or snow from the intensity correlation value ΔV (step S16). The rainfall and snowfall intensity data calculated in this manner is stored in the fifth memory 705 together with the rainfall and snowfall determination data obtained in the rainfall and snowfall determination processing (step S17). The above-described processing of steps S15 to S17 is performed by the rainfall and snow intensity calculation processing means 604 included in the CPU 6.
Done by.

Next, the CPU 6 records the data stored in the fifth memory 705 (the visibility value data, the rainfall / snow discrimination data, and the rainfall / snow intensity data) and / or displays the display process on the display unit 8 and / or the recording process. This is performed by the display processing means 605 (step S18), and a series of control is completed.

By the way, in the process of collecting the A / D converted data for each received light intensity and creating the histogram data, in order to improve the measurement accuracy of the visibility value and the measurement accuracy of the rainfall and snowfall intensity in particular, the A / D Although the number of converted data must be increased, the processing time becomes longer and the measurement speed becomes slower when the number of collected data increases. For example, when the weather condition changes drastically, it is impossible to perform the measurement following the weather condition change.

By the way, when the meteorological condition changes rapidly, the visibility signal is generally high (dense fog), the received light signal has a higher level than noise, and the S / N ratio is extremely high.
Even if the number of A / D converted data is small, it is possible to maintain a certain measurement accuracy, but on the contrary, when the weather conditions are calm,
Since the intensity of the received light signal decreases (the noise level does not change) and the S / N ratio decreases, the total number of A / D converted data must be increased in order to maintain constant measurement accuracy. However, when the weather is calm, generally, a high measurement speed is not required. Therefore, when creating the histogram data, A
Performing the process of changing the total number of the / D conversion data is extremely effective in obtaining the data corresponding to the gradual change of the weather condition while maintaining the constant measurement accuracy.

FIG. 3 is a flow chart for explaining the histogram data creating process by the above process, FIG. 9A is a diagram showing an example of the histogram data for explaining the above process, and FIG. 9B is the correlation necessary for the above process. Data,
The data stored in the fourth memory 704 is shown.

When performing the processing, A shown in FIG.
Steps S1 to S3 of the / D conversion data totaling process are replaced by the flow shown in FIG. The histogram data creation process by the process will be described below.

The CPU 6 reads the A / D converted data of the received light signal sent from the A / D converter 5 one by one (step S101), and reads the read A / D converted data into the first memory for each received light intensity. It is stored in 701 (step S102).

Next, the CPU 6 sets the number Na set in the first memory 701 for creating preliminary data of histogram data (data for grasping the outline of weather conditions).
It is determined whether (a relatively small number) of A / D converted data has been stored (step S103).
The above operation is repeated until the number of stored D / D converted data reaches the number Na.

When the number of A / D converted data stored in the first memory 701 reaches the number Na and the preliminary data is completed, the CPU 6 next detects the maximum data number level L0 in the preliminary data (step S104). ), The fourth
Referring to the data shown in FIG. 9B stored in the memory 704, the number of A / D converted data (total number of data) Nt necessary for the histogram data to be finally created
Is determined (step S104).

The preliminary data in the above-described processing is data that indicates the general condition of the weather condition because the number of A / D converted data Na to be totaled is small, so that the processing is completed in a very short processing time. That is, whether the change in weather conditions is slow or rapid can be determined by the preliminary data.

The data stored in the fourth memory 704 shows the relationship between the received light intensity of the maximum data number Npo (the maximum data number level in the preliminary data) and the total data number Nt, and the logarithmic coordinate. In the case of the above, it was confirmed that accurate measurement is possible by setting the linear relationship as shown in the figure (accuracy in the relationship between the maximum data number level L1 in the final histogram data and the visibility value). Is almost proportional to the square root of the total number of A / D converted data (total data number Nt).)

When the maximum data number L0 is detected, C
The PU 6 refers to the data stored in the fourth memory 704 to determine the total number of data Nt (step S105), and then reads the A / D conversion data sent from the A / D converter 5 again. (Step S106),
The read A / D converted data is again stored in the first memory 701 according to the received light intensity thereof (step S107), and the judgment is made in step S108 until the number of data stored in the first memory 701 reaches the total data number Nt. The processing of steps S106 and S107 is repeated. After the processing of step S107, the processing of step S4 and subsequent steps in FIG. 2 is performed.

As described above, when a weather change is rapid, a small number of A / D conversion data are aggregated to quickly obtain various data, and when the weather change is mild, a large number of A / D conversion data are obtained. It becomes possible to obtain various data while maintaining a predetermined accuracy by totaling.

Further, when the histogram data is created by the process shown in FIG. 3, the number of A / D converted data to be aggregated differs depending on the weather condition, so the process of calculating the rainfall and snowfall intensity (steps S15 to S17 in FIG. 2). In the process), the intensity correlation value ΔV calculated in step S15 does not become a value based on the same standard, and therefore the intensity of rainfall or snow cannot be calculated. Therefore, it is necessary to normalize the intensity correlation value ΔV so that the intensity correlation value has the same standard. In this normalization processing, the intensity correlation value ΔV is divided by a value proportional to the total number of data Nt. This is easily possible by performing

In the embodiment described above, the visibility value, the measurement process, the rainfall / snow discrimination process, and the rainfall / snow intensity measurement process are performed at the same time, but any one or two processes may be performed. Needless to say.

[0074]

As is apparent from the above description,
The present invention has the following effects.

(1) Since the visibility measurement, the presence / absence of rainfall / snowfall, the rainfall / snowfall determination, and the rainfall / snowfall intensity measurement can be performed based on the same data (histogram data), simultaneous observation can be obtained.

(2) Even if the observation items are different, separate observation equipment is not required, and the observation system can be downsized and simplified, and a comprehensive system for multi-item observation can be easily realized.

(3) Since the data averaging process which requires the time constant circuit is not included, stable observation is possible even when there is a drastic weather change.

(4) Even if the weather changes drastically, it is possible to carry out observations that can follow the changes, and it is also possible to perform observations that maintain a certain degree of accuracy even during calm times when the observation accuracy generally decreases.

(5) In the visibility measurement, since the received light component due to raindrops or snowflakes, which has little relation to the visibility value, is not included in the visibility value calculation data, the measurement can be performed with high accuracy.

(6) In the rainfall / snowfall determination, regardless of the situation of rainfall / snowfall, it is possible to make a reliable determination in the initial stage (beginning of rainfall).

(7) Rainfall In measuring the snowfall intensity, both the rainfall intensity and the snowfall intensity can be measured by the same measuring means.

[Brief description of drawings]

FIG. 1 is a block diagram of an embodiment of the present invention.

2A and 2B are overall flowcharts of an embodiment of the present invention.

FIG. 3 is a flowchart of another embodiment regarding the totalization processing of the embodiment of the present invention.

4A and 4B are views for explaining the principle of the present invention.

FIG. 5 is a diagram showing a correlation between a maximum data number level and a visibility value.

FIG. 6 is a diagram showing the correlation between the intensity correlation value and the intensity of rainfall and snowfall.

FIG. 7 is a diagram showing histogram data, (A) shows data when there is no rainfall and no snow, (B) shows data when it rains, and (C) shows data when it snows.

FIG. 8 is a diagram showing a relationship between an intensity correlation value and a rain / snow discrimination coefficient.

9A is a diagram illustrating a case where histogram data is created according to FIG. 3, and FIG. 9B is a diagram showing a relationship between a maximum data number level of preliminary data and a total data number.

[Explanation of symbols]

DESCRIPTION OF SYMBOLS 1 ... Emitter 2 ... Light receiver 3 ... Modulator 4 ... Demodulator 5 ... A / D converter 6 ... CPU 7 ... Memory 8 ... Recording / display 9 ... Temperature sensor 601 ... A / D conversion data total processing means 602 ... Visibility value calculation processing means 603 ... Rainfall and snowfall determination processing means 604 ... Rainfall and snowfall intensity calculation means 605 ... Record display processing means

Claims (13)

[Claims] 1. An A / D conversion data obtained by projecting an optical signal in the air, receiving reflected / scattered light of the optical signal in the air, and A / D converting the received light signal is aggregated for each received light intensity. By doing so, histogram data indicating the number (A) of A / D converted data for each received light intensity (L) is created, and the maximum number of A / D converted data (N) is generated in the histogram data.
A visibility measuring method for obtaining a visibility value based on the fact that the received light intensity (L1) for which p) is tabulated has a correlation with the visibility value. 2. The histogram data created by the visibility measuring method according to claim 1 is used, and the received light intensity (L1) in which the maximum number of A / D converted data (Np) is tabulated in the histogram data is used as an axis of symmetry. The symmetry of the histogram data is determined, and when it is found to be symmetric, it is determined that there is no rainfall or snowfall, and when it is found to be asymmetric, it is determined that there is rain or snowfall, and it appears in the histogram data. The ratio of the maximum received light intensity (Lp) and the distribution width (ΔN) of the number of A / D converted data of the asymmetrical portion (S) or the distribution width (ΔL) of the received light intensity is different between when it is raining and when it is snowing. A method for discriminating rainfall or snowfall in which it is determined whether it is raining or snowing based on showing different values. 3. The method for determining rainfall / snowfall according to claim 2, wherein the received light intensity (L1) and the minimum received light intensity (Ls) in which the maximum number of A / D converted data (Np) is tabulated are obtained from the histogram data. , The number of A / D converted data summed to the received light intensity (L4) at a point distant from the received light intensity (L1) in the high level direction by the difference (L1-Ls) between the two received light intensities, If is substantially zero, then the histogram data is assumed to be symmetric, and
When the number of data is not substantially zero, the histogram data is assumed to be asymmetric, and the number of data is defined as the distribution width (ΔN) of the A / D conversion data number of the asymmetric portion (S) of the histogram data. How to determine. 4. The method for determining rainfall and snowfall according to claim 2, wherein the maximum received light intensity (L1) and the maximum A / D converted data number (Np) are collected.
The number of A / D converted data which is half of p) (1/2 Np)
The light reception intensities (L2) and (L3) (where L2 <L3) are calculated from the histogram data, and the light reception intensity difference (L3-L1) and the light reception intensity difference (L1-) are obtained.
When the difference value (L2 + L3-2L1) from L2) is substantially zero, the histogram data is assumed to be symmetrical, and when the difference value (L2 + L3-2L1) is not substantially zero, the histogram data is A method for discriminating rainfall and snowfall in which the value of the difference (L2 + L3-2L1) is regarded as asymmetrical and the distribution width (ΔL) of the received light intensity of the asymmetrical portion (S) of the histogram data is used. 5. The rain / snow discrimination method according to claim 2, wherein the maximum received light intensity (Lp) appearing in the histogram data and the distribution width (ΔN or Δ) of the asymmetric portion (S).
A method for determining rainfall and snowfall in which the outside air temperature is added to the determination data when the value of the ratio to L) indicates the boundary value for rainfall and snowfall determination. 6. Using the histogram data created by the visibility measuring method according to claim 1, for each received light intensity for which A / D conversion data is aggregated, each received light intensity and maximum A / D
Received light intensity (L
1) The difference between the received light intensity (L1) and the maximum received light intensity (Lp) is calculated as the sum of the products of each of the difference values and the number of A / D converted data collected for each received light intensity. And the range from the above received light intensity (L1) to the minimum received light intensity (Ls), and the value of the difference (ΔV) between the two sums has a correlation with the intensity of rainfall or snowfall. A method for measuring rainfall and snow intensity, in which the rainfall intensity or snow intensity is calculated. 7. A light projecting means (1) for emitting a modulated optical signal into the air, and a light receiving means (2) for receiving reflected and scattered light in the air of the optical signal emitted from the light projecting means (1). A demodulating means (4) for demodulating the output signal of the light receiving means (2) in synchronization with the modulation of the optical signal, and an A / D converting the light receiving signal output from the demodulating means (4) for A / D conversion. D conversion means (5)
A first processing means (601) for distributing the A / D conversion data of the received light signal output from the A / D conversion means (5) according to the received light intensity (L), and the first processing means. A sorted by received light intensity (L) by (601)
By storing the A / D converted data for each received light intensity (L), the number of A / D converted data (N) for each received light intensity (L)
And a first storage unit (701) for storing histogram data indicating
Received light intensity (L
1) and the second storage means (702) in which the correlation data between the visibility value and the first storage means (701) are stored in advance.
Second processing means (602) for obtaining a visibility value by collating the histogram data stored in the second storage means with the correlation data stored in the second storage means (702), and the second processing means (602) A visibility measuring device comprising a storage display means (8) for recording and / or displaying the visibility value obtained by. 8. A second storage means (702) and a second processing means (60) included in the visibility measuring device according to claim 7.
Instead of 2) or together with these means (702, 602), with respect to the histogram data stored in the first storage means (701), the maximum received light intensity (Np) is collected (Np). L1) is a determination process for determining the symmetry of the histogram data, and the determination process yields the result that the histogram data is asymmetrical, the maximum received light intensity appearing in the histogram data. (Lp) and an A / D conversion data number distribution width (ΔN) of the asymmetrical portion (S) or a calculation processing for calculating a rain / snow discrimination coefficient defined by a ratio of the received light intensity distribution width (ΔL), and the calculation. A rainfall and snowfall determination device including third processing means (603) having each processing function of determination processing for determining whether it is rainy or snowy from the rain / snowiness determination coefficient obtained in the processing. 9. The rain / snow determination device according to claim 8, wherein when the rain / snow determination coefficient indicates a boundary value of the rainfall / snow determination, the temperature detecting means for using the outside air temperature as the data of the rainfall / snow determination ( A rainfall and snowfall determination device further having 9). 10. The rainfall / snow determination device according to claim 8, wherein the received light intensities in the asymmetric portion (S) of the histogram data stored in the first storage means (701) and the received light intensities are summarized. With respect to the histogram data, the third storage means (703) in which the correlation data between the rainfall intensity and the snowfall intensity and the value obtained by calculating and summing the product of the number of A / D converted data for each received light intensity are stored in advance, A /
A first calculation process for calculating the difference between the received light intensity and the received light intensity (L1) for which the maximum number of A / D converted data (Np) is calculated for each received light intensity for which the D-converted data is collected, In the second arithmetic processing, the product of the difference value obtained in the arithmetic processing of No. 1 and the number of A / D converted data tabulated for each of the above received optical intensities is calculated for each of the above received optical intensities. The obtained product value for each received light intensity is respectively calculated for the range from the received light intensity (L1) to the maximum received light intensity (Lp) and the range from the received light intensity (L1) to the minimum received light intensity (Ls). The summation is performed separately and the sum (Vp,
Vs), and the difference between the two sums (ΔV = Vp−
Vs) is calculated by a third calculation process, and the difference value (ΔV) obtained by the third calculation process is compared with the correlation data stored in the third storage means to determine the intensity of rainfall or snowfall. A rainfall and snowfall intensity measuring device further comprising a fourth processing means having each processing function of a fourth arithmetic processing for calculating. 11. A visibility measuring method according to claim 1, a rain / snow determining method according to claim 2-5, a visibility measuring device according to claim 7, and a rain / snow determining according to claim 8 or 9. A method of creating histogram data used in an apparatus, wherein first, A / D conversion data of a small number (Na) of received light signals is aggregated for each received light intensity, and number of A / D converted data for each received light intensity (L) (N) The preliminary data of the histogram data indicating is created, and the total number (Nt) of the A / D converted data is determined based on the received light intensity (L0) in which the maximum number of the A / D converted data (Npo) is calculated in the preliminary data. Then, the A / D conversion data of the difference number (Nt-Na) between the total number (Nt) and the number (Na) already counted in the preliminary data is overlaid on the preliminary data and received light intensity (L) is classified. I tried to count How to create stogram data. 12. The method for measuring rainfall and snowfall intensity according to claim 6, wherein when the histogram data is created by the method according to claim 11, the total number (Nt) of A
2 according to the histogram data created from the / D conversion data
Rainfall in which the intensity of rainfall or snowfall is calculated based on the normalized value by calculating the difference (ΔV) between the two totals and dividing the value of this difference (ΔV) by a value proportional to the total number of counts (Nt). How to measure snowfall intensity. 13. The rainfall / snow intensity measuring device according to claim 10, wherein the first processing means (601) is the measuring device.
In the case of a method of creating histogram data by the method described in (3), the difference value (Δ
A rainfall and snowfall intensity measuring device having a normalization processing means for the difference value (ΔV) by dividing V) by a value proportional to the total number (Nt) of the A / D converted data.