CN105352979A - Soil humidity estimation method based on Beidou GEO satellite signals - Google Patents

Abstract

The invention relates to a soil humidity estimation method based on Beidou GEO satellite signals. The method is used for soil humidity inversion through signal-to-noise ratio data of Beidou GEO satellite direct signals and reflected signals. The soil humidity value is estimated mainly adopting a Beidou receiver for receiving the variance of reflection coefficients of the GEO satellite signals; a comparison diagram for the actually-measured soil humidity variation trend and the variance change trend is drawn, the relevance between the actually-measured soil humidity variation trend and the variance change trend is compared, the correlation coefficient can reach 0.71 through calculation, the relation between the variance and actually-measured soil humidity is fit finally, and the soil humidity of the same day is estimated through combination of a fit logarithm relation model and Beidou signal signal-to-noise ratio data of the day. The application field of the Beidou signals is expanded, and the method can be applied to research on agricultural irrigation and weather.

Description

Based on the soil moisture method of estimation of Big Dipper GEO satellite-signal

Technical field

The present invention relates to electronics, areas of information technology, is a kind of soil moisture method of estimation based on Big Dipper GEO satellite-signal, is specifically related to a kind of method utilizing the variance of Big Dipper GEO satellite direct signal and reflected signal smnr data to carry out soil moisture estimation.

Technical background

Soil moisture plays an important role in meteorology, the hydrology, agricultural environment research.The measurement of soil moisture data, to potential flood, the forecast of the weathers such as arid can provide information.Soil moisture data, to the Rational Irrigation of crop, reduces water resource waste, reduces production cost also extremely important with raising crop yield.

In the inversion method of current soil moisture, the comparative maturity of development have following in site measurement method, as weight measurement method, tensiometer method, electric-resistivity method, Neutron probe method etc.

In the last few years, it is found that satellite-borne microwave remote sensing can be used for large area monitoring soil moisture (Zhang Xiaojuan, Zhang Wenji. Dual-Frequency Synthetic Aperture Radar for Deep Soil Moisture Estimation. CAS Electronics Research Institute Beijing .2007), star-loaded optical remote sensing is also a kind of means.But utilize space remote sensing means, what the such as method of SAR radar inverting humidity was limited to satellite returns to the cycle, because satellite becomes periodic rotary around Earth's orbit, only in the specific time period through same place, so it cannot obtain a certain place round-the-clock data.

In addition, GPS or GNSS-R satellite-signal remote sensing humidity is adopted also to be a kind of exploration.One method adopts GPS interference signal, such as, adopt the flex point of search interference signal to realize soil moisture retrieval (patent CN201010207399.2).Another kind method is that the ratio research utilizing antenna and receiver to carry out reflected signal and direct signal carrys out Soil Moisture (tight song Hua Zhangxun tool, the soil moisture retrieval based on GNSS-R signal is studied, electric wave science journal, the 1st phase in 2010).But these researchs are all for gps satellite, due to the global motion of gps satellite, not in the work year in year out of which fixed location, even if so have employed reflection coefficient to study, also the angle, elevation bearing due to satellite is indefinite, and a kind of approximate method in high elevation angle can only be adopted to calculate, lack accuracy.

Dipper system formally puts into operation, according to the open service signal 2.0 editions of dipper system spacing wave interface control document that China will publish the end of the year 2013, and the open service performance specification of dipper system, the current operation on orbit satellite of system has 5 geostationary orbit satellite (GEO) satellites, 5 inclination geo-synchronous orbit satellite (IGSO) satellites and 4 middle altitude circle orbiter (MEO) satellites, formally serve Asia-Pacific region, horizontal and vertical positioning precision is provided to be better than the service range of 10m (degree of confidence 95%), the i.e. open service area of dipper system.

Geostationary orbit satellite GEO (being numbered C01C02C03C04C05) in special concern big-dipper satellite constellation of the present invention, it has fixed elevation, trapped orbit height, according to the feature of big-dipper satellite, this satellite is that whole day 24 hours is continual provides navigation signal accurately, again due to its relatively ball position fix, therefore, when receiver location is fixing, the smnr data in same place any moment can be obtained; In addition, immobilize just because of its overlay area, therefore the variance characteristic of its reflected signal reflects the trend of soil moisture, may be used for estimating soil moisture, also be beneficial to the present invention's utilization simultaneously and carry out actual humidity measurement in this overlay area, to set up the funtcional relationship with variance.

Summary of the invention

For background technology Problems existing, the present invention proposes to utilize the variance characteristic of the reflection coefficient of Big Dipper GEO satellite to estimate the method for soil moisture.Returned by long-term observation data and set up reflection coefficient variance and the funtcional relationship of actual measurement humidity, finally utilize this relation to estimate soil moisture.

The present invention adopt direct signal and the signal to noise ratio (S/N ratio) of reflected signal in Big Dipper GEO satellite ratio---the variance characteristic of reflection coefficient is to estimate soil moisture.Because the variance change of reflection coefficient presents certain associating with soil moisture change, the corresponding logarithmic relationship of variance and the soil moisture counted can be utilized, set up and utilize variance to estimate the mathematical model of soil moisture.In estimation afterwards, just can utilize this funtcional relationship, by the smnr data of known direct signal and reflected signal, try to achieve reflection coefficient, and then soil moisture at that time can be estimated.

Technical scheme of the present invention arranges a right-handed polarized antenna upward and a left-hand polarized antenna down (being used for respectively receiving direct signal and reflected signal), two Beidou receivers, and the GPRS transmission card of the band SIM certification of signal transmission, transfer data to PC, original position humidity sensor is on the spot laid, to data analysis in early stage.Original position hygrometer can be removed afterwards.

A kind of soil moisture method of estimation based on Big Dipper GEO satellite-signal, first obtain the direct signal of soil moisture change comparatively significantly nearly 2 months (from mid-September to nearly 2 months at the beginning of 12 months) and the smnr data of reflected signal, the ratio obtaining reflected signal and direct signal again obtains reflection coefficient, variance is asked for it, the relatively correlativity of variance and true humidity, finally variance and humidity are carried out curve fitting, set up contacting of variance and soil moisture, last according to this funtcional relationship, the humidity value on the same day is estimated by certain day Big Dipper GEO satellite-signal smnr data.

Specifically comprise the following steps;

Step 1, overlay area is determined and raw data acquisition:

According to the angle, elevation bearing of Big Dipper GEO satellite and the position of receiving antenna with highly determine overlay area.

Utilize right-handed polarized antenna to receive GEO satellite direct signal, left-hand polarized antenna receives GEO reflected signal.Receive by CPU (central processing unit) DTU the signal that two antennas transmit again, data are finally passed on the server in laboratory by output signal-to-noise ratio data.

Step 2, data preliminary election:

Select in Big Dipper GEO satellite direct signal and reflected signal, whole day has the data of signal to noise ratio (S/N ratio) for 24 hours as pending data source.

Step 3, Big Dipper Signal Pretreatment:

Signal to noise ratio (S/N ratio) in the data of the UTC time included by the GEO satellite-signal received, the elevation angle, position angle, signal to noise ratio (S/N ratio) and UTC temporal information extract, and respectively by the time unifying of direct signal and reflected signal, ask for reflectance value again, the reflection coefficient now obtained per secondly has data.

Step 4, ask for variance:

Because data within half an hour are changes, the size variance of disturbance is measured.Ask for the variance of per period half an hour 1800 reflection coefficients respectively to reflect the fluctuation situation of reflection coefficient.

Step 5, compares the Long-term change trend relation of variance and soil moisture and the empirical model of matching:

The information such as signal to noise ratio (S/N ratio), the elevation angle, position angle, UTC time of the continuous process Big Dipper GEO satellite-signal of nearly about 2 months, the actual measurement soil humidity value of itself and 2 every days in the middle of the month is contrasted, this variance of 2 months is arranged in chronological order, and this soil moisture value of 2 months is arranged in chronological order, finally both are plotted in a figure, are set up the logarithmic function relation of variance change and soil moisture change by nonlinear regression analysis.

Step 6, utilizes logarithmic function relation to estimate soil moisture:

After obtaining the big-dipper satellite smnr data of certain day certain period half an hour, obtain the variance yields of this period half an hour through data processing, substitute into the soil moisture can obtaining this period in logarithmic function relation.

Accompanying drawing explanation

Fig. 1 is Big Dipper GEO signal receiving antenna schematic diagram of the invention process;

Fig. 2 is the coverage diagrams of the Big Dipper 5 GEO satellites when high 2 meters of receiving antenna;

Fig. 3 is Big Dipper direct signal of the invention process and the preliminary election of reflected signal smnr data;

Fig. 4 is Big Dipper signal reflex coefficient figure of the invention process;

Fig. 5 is Big Dipper signal-data processing process flow diagram of the invention process;

Fig. 6 is variance of the invention process and actual measurement soil moisture variation tendency comparison diagram;

Fig. 7 is Big Dipper satellite signal variance of the invention process and the logarithmic function graph of a relation of surveying soil moisture.

Concrete scheme is implemented

In current research, the method that soil moisture retrieval has proposed has many, such as interference signal method, reflectometry etc.The present invention adopts a kind of new approaches, utilizing the fluctuation situation of the reflection coefficient of Big Dipper geo-stationary orbit GEO satellite-signal---the change of variance is to estimate soil moisture, by the smnr data that Beidou receiver obtains, calculate the variance of reflection coefficient, set up the mathematical model of variance and soil moisture.Finally just can calculate the Big Dipper Signal-to-Noise data variance of certain period as required to estimate the soil moisture value of this period.

Feature of the present invention is first according to the orientation of GEO satellite, determines its overlay area; The smnr data of the Big Dipper GEO signal adopted, extracts the variance of reflection coefficient; Set up the funtcional relationship of actual humidity value variance in region; Soil moisture is estimated finally by variance.

Below with specific embodiment also by reference to the accompanying drawings, the invention will be further described.

Step 1: overlay area is determined and raw data acquisition

Fig. 1 device is used to gather original Big Dipper signal, and wherein 1 is the satellite of GEO; 2 is right-handed polarized antennas, is used for receiving direct signal; 3 is left-hand polarized antennas, receives reflected signal; 4 is CPU (central processing unit) DTU, is used for receiving the signal from antenna, output signal-to-noise ratio data, and is sent on the server in laboratory by data; The height on antenna distance ground is 2m.Due to the present invention's employing is No. 1 satellite-signal, so its fixed elevation is 43 °.

Fig. 2 is the different overlay areas of 5 GEO satellites (C01, C02C03C04C05) when high 2 meters of reflection receivable antenna.Wherein 5-9 is the area coverage of 5,2,3,1, No. 4 GEO satellites respectively, and its area coverage is 11m respectively ², 3.3m ², 1.8m ², 2.6m ², 5.7m ².

Raw data comprises: Big Dipper direct signal signal to noise ratio snr _d, reflected signal signal to noise ratio snr _r, direct signal UTC time T _d, reflected signal UTC time T _r.

The collection of measured data: Big Dipper GEO satellite and receiving antenna overlay area place (employing be in Fig. 2.Soil moisture research station is set, hygrometer is inserted soil 0-5cm place, record the soil moisture m of about 2 months continuously _vj(i) data, wherein, segment labeling when j represents one day 48 and a half hours, such as first and a half hours time period of this day from 2014.11.140000:00-00:29:59, now the value of j is 1, the span of j is 1-48, the value of i represents i-th point of jth time period, the span of i is 0-1800, therefore soil moisture data be p.s. once, in experiment, actual measurement humidity data be reception per second once, this just means that the data volume of process of the present invention can be very large, but in conjunction with actual analysis, humidity data had almost no change in one second on the one hand, on the other hand, the factors such as unstable may be there is by local power supply, these factors cause the precision of data not high, therefore invention defines a kind of special humidity sensor---medial humidity sensor.This sensor transmission primaries data s per half an hour _mn, s _mnsoil moisture value m per second _vievery halfhour mean value, computing formula is as follows:

$s_{mn}=\underset{i=1}{\overset{1800}{\Σ}}\frac{m_{vj}\left(i\right)}{1800}$

Data are stored as actual measurement humidity sequence S and contrast object as variance.The expression formula of S is as follows:

Wherein, m is capable represents one day m data, and in this experiment, owing to being receive a secondary data half an hour, the value of m is total number of days that measurement is shown in 48, n list, and this experiment measures the data of 2 months, and the value of n is 60.

Step 2: data preliminary election

The Big Dipper signal collected comprises UTC time T, the elevation angle, position angle, signal to noise ratio snr information, extracts UTC time T and the signal to noise ratio snr of a wherein satellite _dwith SNR _r, be direct signal signal to noise ratio (S/N ratio) and the reflected signal signal to noise ratio (S/N ratio) on November 14th, 2014 in figure 3, wherein 10 is direct signal signal to noise ratio (S/N ratio), and 11 is reflected signal signal to noise ratio (S/N ratio), and direct signal signal to noise ratio (S/N ratio) is greater than reflected signal signal to noise ratio (S/N ratio).

Because signal to noise ratio (S/N ratio) has data each second, so one day nearly 86000 point, the smnr data of selection is as far as possible complete, less appearance breakpoint or null value.

Step 3: Big Dipper Signal Pretreatment

First by the UTC time T of direct signal signal to noise ratio (S/N ratio) _dwith the UTC time T of reflected signal signal to noise ratio (S/N ratio) _ralignment, then computational reflect coefficient value, reflection coefficient Γ _kexpression formula is as follows:

Γ _k＝SNR _r(k)/SNR _d(k)

$SNR=10\lg \left(\frac{Ps}{Pn}\right)=20\lg \left(\frac{Vs}{Vn}\right)$

Wherein SNR _rreflected signal signal to noise ratio (S/N ratio), SNR _dbe direct signal signal to noise ratio (S/N ratio), Ps is the useful power of signal, and Pn is the useful power of noise, and Vs is the effective voltage of signal, and Vn is root-mean-square noise voltage.K represents the data of the second of kth in a day.

Step 4: step 4 is divided into two steps, namely first asks for expectation value, then asks variance.

(1) reflection coefficient expectation value is asked for

Once one day 48 reflectance data is obtained by average for reflection coefficient per second per half an hour of trying to achieve, as shown in Figure 3, reflection coefficient expectation value Γ _aveformula is as follows:

${\mathrm{\Γ}}_{ave}=\frac{\underset{k=1}{\overset{1800}{\Σ}}{\mathrm{\Γ}}_k}{1800}$

Wherein, Γ _kfor reflectance value once per second, because per half an hour has 1800 seconds, therefore have about 1800 data, the Γ asked for per half an hour _avebe the variance yields of per period half an hour, within one day, have 48 values.No. 12 lines in Fig. 4 are reflection coefficient expectation values of certain day, and as can be seen from the figure, average reflection coefficient value changes between 0.6-1, and in one day, the amplitude of fluctuation is little.

(2) variance is asked for

According to the average reflection coefficient expectation value Γ calculated _ave, ask for the variance yields D of reflection coefficient _ave, expression formula is as follows:

$D_{ave}\left(k\right)=\underset{k=1}{\overset{n}{\Σ}}{p}_k\·{({\mathrm{\Γ}}_k-{\mathrm{\Γ}}_{ave})}^2$

Wherein, p _kfor a kth reflection coefficient Γ _ithe probability occurred, Γ _avefor the expectation value of reflection coefficient Γ.

Finally obtain a variance sequence D, one day 48 value, altogether the data of 2 months.

Step 5: draw the Long-term change trend relation of variance and soil moisture and the empirical relationship of matching

The smnr data of continuous process about 2 months, obtains variance sequence D by step 3,4 _mnand by the actual measurement soil moisture sequence S of itself and this 2 every days in the middle of the month _mncontrast.Smnr data file is arranged in chronological order, actual measurement soil moisture data file is arranged in chronological order simultaneously, finally both variation tendencies are plotted in a figure, set up the funtcional relationship of variance variation tendency and soil moisture change trend.

Fig. 6 is variance and actual measurement humidity changing trend diagram, and in figure, 13 represent soil moisture change curve, and 14 represent variance change curve, variance reaches 0.71 with the correlativity of actual measurement humidity, and trend is substantially identical, when humidity value is less, variance is also less, illustrates that the fluctuation of reflection coefficient is less.After raining on November 24 and November 27, variance yields becomes large, illustrates that the fluctuation of reflection coefficient becomes large, and the relative fluctuation further illustrating Big Dipper direct signal and reflected signal becomes large.

Fig. 6 is the empirical relationship model of variance and soil moisture, and its expression formula is as follows:

s＝1.97*ln(d)+15.48

Wherein, s is actual measurement soil humidity value, and d is variance yields.

In the figure 7,15 represent that horizontal ordinates represent variance, and ordinate represents the point of soil moisture, and the expression formula of this point is (D, S), and 16 is logarithmic function empirical models of matching, and these are put near the logarithmic relationship curve of basic matching as can be drawn from Figure 7.

Step 6: utilize logarithmic function relation to estimate soil moisture

Finally can utilize this model, utilize the big-dipper satellite smnr data on the same day to estimate soil moisture.According to this relation, calculate certain day Big Dipper signal reflex coefficient variance after can estimate the soil moisture on this ground same day.

Claims (4)

1., based on a soil moisture method of estimation for Big Dipper GEO satellite-signal, it is characterized in that:

First obtain the smnr data of the soil moisture change direct signal of comparatively obvious 2 months and reflected signal, the ratio obtaining reflected signal and direct signal again obtains reflection coefficient, variance is asked for it, the relatively correlativity of variance and true humidity, finally variance and humidity are carried out curve fitting, set up contacting of variance and soil moisture, finally according to this funtcional relationship, estimated the humidity value on the same day by certain day Big Dipper GEO satellite-signal smnr data.

2. the soil moisture method of estimation based on Big Dipper GEO satellite-signal according to claim 1, is characterized in that: specifically comprise the following steps;

Step 1: overlay area is determined and raw data acquisition

According to the angle, elevation bearing of Big Dipper GEO satellite and the position of receiving antenna with highly determine overlay area; Right-handed polarized antenna is utilized to receive direct signal, left-hand polarized antenna receives reflected signal, receive by CPU (central processing unit) DTU the signal that two antennas transmit again, export the signal to noise ratio (S/N ratio) of Big Dipper GEO satellite-signal, the elevation angle, position angle, UTC temporal information, finally data are passed on server;

Step 2: data preliminary election

Select in direct signal and reflected signal, whole day has the data of signal to noise ratio (S/N ratio) for 24 hours as pending data source;

Step 3: Big Dipper Signal Pretreatment

Signal to noise ratio (S/N ratio) in the data of the UTC time included by the GEO satellite-signal received, the elevation angle, position angle, signal to noise ratio (S/N ratio) and UTC temporal information extract, and respectively by the time unifying of direct signal and reflected signal, then ask for reflectance value;

Step 4: ask for variance

Ask for the variance of per period half an hour 1800 reflection coefficients respectively to reflect the fluctuation situation of reflection coefficient;

Step 5: compare the Long-term change trend relation of variance and soil moisture and the empirical model of matching;

Step 6: rule of thumb soil moisture estimated by model.

3. the soil moisture method of estimation of basic Big Dipper GEO satellite-signal according to claim 2, is characterized in that: the specific implementation process of described step 5 is;

The continuous process smnr data of 2 months, utilize reflection coefficient and signal to noise ratio (S/N ratio) formula, known signal to noise ratio (S/N ratio) obtains reflectance value per second, the variance yields of last computational reflect coefficient, the actual measurement soil humidity value of itself and 2 every days in the middle of the month is contrasted, this variance of 2 months is arranged in chronological order, and this soil moisture value of 2 months is arranged in chronological order, finally both are plotted in a figure, are set up the logarithmic function relation of variance change and soil moisture change by nonlinear regression analysis.

4. the soil moisture method of estimation of basic Big Dipper GEO satellite-signal according to claim 3, is characterized in that: described step 6 utilizes logarithmic function relation to estimate soil moisture;

After obtaining the big-dipper satellite smnr data of certain day certain period half an hour, obtain the variance yields of this period half an hour through data processing, substitute into the soil moisture can obtaining this period in logarithmic function relation.