CN107991646A - Very low frequency navigation electric wave propagation prediction refined method based on cloud framework - Google Patents
Very low frequency navigation electric wave propagation prediction refined method based on cloud framework Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
- G01S5/02—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using radio waves
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Abstract
The present invention provides a kind of very low frequency navigation electric wave propagation prediction refined method based on cloud framework, using the big data and cloud computing technology of networking, by means of machine learning come the radio waves propagation model that builds and refine, realize high-precision radio waves propagation model amendment, in addition to high-precision Modifying model can be provided, the updated model data that cloud framework radio wave propagation is corrected data processing centre and broadcasted can also be received by very low frequency navigation user terminal, the newest radio wave propagation that radio wave propagation correction model is updated in time corrects prediction model, the modified accuracy of lift scheme.
Description
Technical field
The present invention relates to a kind of radionavigation location model modification method, more particularly to it is a kind of excavated based on big data and
The very low frequency navigation electric wave propagation prediction refined method of machine learning.
Background technology
Radionavigation is to launch radio navigation signal by the transmitting station of known location, and user terminal is multiple by receiving
The radionavigation navigation signal of transmitting station, by positioning calculation, obtains customer location.
The frequency of very low frequency radio is 3kHz~30kHz, and the radio of this wave band passes through ground and ionosphere waveguide
The distance of propagation is remote, and propagation attenuation is small, has certain underwater penetration, and very low frequency is wirelessly normally used for remote wide area radio
Navigation and communication.
Typical very low frequency navigation system is the omega navigation system in the U.S. and Alpha's navigation system of Russia.It is beautiful
State once established 8 omega transmitting stations in the whole world, and signal frequency is in the range of the very low frequency of 10k~15kHz, realizes
The Global coverage of very low frequency navigation signal.Omega uses the hyperbolic fix system than phase time of measuring difference, provides to the user
Passive two-dimensional positioning (plane positioning of earth surface) service, design accuracy are 2~4 nautical miles, position error and user locations, sight
Moment, the selected station to be surveyed, propagates to correct etc. and there are much relations, place is identical and reproducibility that the time is different is 2~4 nautical miles,
Time is identical and relative accuracy that place is different is 0.25~0.5 nautical mile, and positioning accuracy 1 can be brought up to using differential technique
In the sea (in the range of 500 nautical miles).
Alpha's navigation system is the super-long-range navigation system similar to omega of former Soviet Union's construction, establishes 3 hairs
Penetrate platform.Emission signal frequency is in the range of the very low frequency of 11k~16kHz, and Alpha's navigation system workspace is covering the whole world
70% area.The usual positioning accuracy of Alpha's navigation is at 2~4 nautical miles, to solve the problems, such as electric wave " forecast value revision ", Russia
31 alpha signals have successively been built up in system work area and have propagated monitoring station.The common Europe rice of the ratio of precision of difference Alpha
The positioning accuracy of gal improves 3~5 times, and the positioning accuracy on daytime is up to 200~1000m.
The positioning accuracy of very low frequency navigation system is influenced very greatly, in order to carry by the environmental characteristics in ionosphere and propagation path
The positioning accuracy of very low frequency navigation system is risen, it is necessary to lift final positioning accuracy using radio wave propagation correction technique.
Traditional electric wave tradition corrects general take and establishes correction model, king build write " very low frequency propagation phase is pre-
In survey and the research of C effect layers " (in October, 2004) electronics science research institute master thesis, using semi-empirical approach to very low
Frequently " the C effect layers " of (VLF) propagation phase has carried out analysis and modeling, improves VLF propagation phase anticipation functions.With the U.S.
10 percentage weeks of precision of prediction of six generation Phase Prediction models are compared, and precision of prediction was higher by for about 3.35 percentage week.
Traditional model phase forecast value revision is mostly based on empirical parameter, and parameter change affected by various factors is big, corrects
Precision it is not high, it is difficult to meet the requirement of high-precision navigator fix.
The content of the invention
For overcome the deficiencies in the prior art, the present invention provides a kind of propagation correcting process method based on cloud framework, adopts
With the big data and cloud computing technology of networking, by means of machine learning come the radio waves propagation model that builds and refine, realize high-precision
The radio waves propagation model amendment of degree, in addition to it can provide high-precision Modifying model, can also be used by very low frequency navigation
Family terminal receives the updated model data that cloud framework radio wave propagation corrects data processing centre's broadcast, in time corrects radio wave propagation
The newest radio wave propagation that model modification arrives corrects prediction model, the modified accuracy of lift scheme.
The technical solution adopted by the present invention to solve the technical problems comprises the following steps：
Step 1, the very low frequency navigation electric wave that several positions accurately measure is disposed in very low frequency navigation working region to pass
Broadcast monitoring station, and the cloud framework radio wave propagation of unicom very low frequency navigation radio wave propagation monitoring station and very low frequency navigation user terminal
Correct data processing centre；Data processing centre, which is corrected, in cloud framework radio wave propagation establishes radio wave propagation error correction anticipation function
PPC (t)=ω 0+ ∑ N (t)+∑ B (t)+∑ σ (t)+∑ ε (t), wherein, ω 0 is to be calculated according to transmitting station to customer location
Very low frequency signal notional phase value；∑ N (t) is ionosphere on transmitting station to customer location path, to very low frequency signal phase
The segmentation aggregate-value of influence；∑ B (t) is earth magnetic field on transmitting station to customer location path, to very low frequency signal phase shadow
Loud segmentation accumulated value；∑ σ (t) is the electrical conductivity on transmitting station to customer location path, to very low frequency signal phase effect
It is segmented accumulated value；∑ ε (t) is the dielectric constant on transmitting station to customer location path, and very low frequency signal phase effect is divided
Section accumulated value；
Step 2, the real-time measurement values Δ ε of real-time reception very low frequency navigation radio wave propagation monitoring station, and radio wave propagation is missed
Wave Propagation Prediction value caused by difference amendment anticipation function PPC on the position of monitoring station is missed compared with measured value
Difference sigma=Δ ε-PPC；
Step 3, according to error amount σ, using single order contiguous segmentation curve fitting algorithm, to PPC Wave Propagation Prediction amendments
The segment phase of ionosphere N (t), magnetic field B (t), conductivityσ (t), permittivity ε (t) in function influence coefficient and weighting is
Number is adjusted, so that the error of curve matching is minimum, obtains the radio wave propagation error correction prediction letter after parameter precision
Number PPC ' (ω, Pt,Pr,,Tymdt)；
Step 4, data are observed according to the modified history of radio wave propagation, with reference to the meteorological and hydrogeological data conversion of history
Electrical conductivity and dielectric constant values, in PPC ' (ω, Pt,Pr,,Tymdt) on the basis of with history observation data be iterated processing, adopt
With single order contiguous segmentation curve fitting algorithm, ionosphere N (t), the magnetic in PPC Wave Propagation Prediction correction functions are further adjusted
Field B (t), conductivityσ (t), the segment phase of permittivity ε (t) influence coefficient and weighting coefficient so that the actual measurement of radio wave propagation
The statistical error of value and radio waves propagation model predicted value is minimum, the radio wave propagation correction model after being refined.
The value range of the PPC (t) is [- 350cec ,+350cec], and cec is the percentage week of very low frequency signal phase.
The value range of the ∑ N (t) is [- 150cec ,+150cec]；The value range of the ∑ B (t) be [-
50cec ,+50cec]；The value range of the ∑ σ (t) is [- 110cec ,+110cec]；The value range of the ∑ ε (t) is
[- 40cec ,+40cec].
The beneficial effects of the invention are as follows：Due to combining real-time measuring data and historical measurement data, pass through sectional curve
Process of fitting treatment, it is minimum by the statistical error of mass data, by the precision of very low frequency navigation radio waves propagation model forecast value revision from
1 percentage week is brought up to 5~10 traditional percentage weeks, so as to the final positioning accuracy of very low frequency navigation user terminal be had original
Several nautical miles of levels bring up to hundreds of meters of magnitudes.
Brief description of the drawings
Fig. 1 is the very low frequency navigation electric wave propagation prediction configuration diagram based on cloud framework；
Fig. 2 is radio wave propagation monitoring station deployed position figure；
Fig. 3 is very low frequency navigation radio wave propagation monitoring station equipment composition frame chart；
Fig. 4 is that cloud framework radio wave propagation corrects data processing centre's data processing shelf schematic diagram；
Fig. 5 is radio wave propagation correction model refined processing flow chart；
Fig. 6 is very low frequency navigation user terminal radio waves propagation model correcting process process schematic.
Embodiment
The present invention is further described with reference to the accompanying drawings and examples, and the present invention includes but are not limited to following implementations
Example.
The present invention uses following technical scheme：
Radio wave propagation monitoring and cloud framework electric wave correcting process system of the present invention based on networking, include and are distributed in very
Very low frequency navigation radio wave propagation monitoring station, electric wave monitoring station and cloud framework radio wave propagation in low frequency navigation working region correct number
Data processing centre is corrected according to the communication network of processing center, cloud framework radio wave propagation, cloud framework radio wave propagation is corrected at data
Radio communication channel between reason center and very low frequency navigation user terminal, and very low frequency navigation user terminal.
The very low frequency navigation radio wave propagation monitoring station is on the fixing point of known location, and very low frequency navigation monitoring connects
The radio signal that receipts machine is launched by receiving very low frequency navigation platform, measures the letter between very low frequency navigation transmitting station and monitoring station
Number propagation values, and compared with the high stable time and frequency standards and accurately known position reference, obtain radio wave propagation
Error amount.The real-time meteorological data in monitoring station is obtained by meteorological sensor.Radio wave propagation monitors and corrects integrated treatment and calculates
Machine carries out data processing and storage, and the radio wave propagation error amount and real time meteorological data that will be obtained, by wirelessly or non-wirelessly
Transmission of network corrects data processing centre to cloud framework radio wave propagation.
The cloud framework radio wave propagation corrects data processing centre, on the basis of based on existing radio waves propagation model,
Real-time reception and the data for handling the radio wave propagation monitoring station that multiple wide areas are distributed, and combine the modified historical data of radio wave propagation
And the data such as real-time weather and geology are handled, by cloud computing and machine learning, radio waves propagation model is carried out fine
Change and correct.
Cloud framework radio wave propagation is preset in very low frequency navigation user terminal and corrects the electricity that data processing centre produces in advance
Ripple propagates correction model, after very low frequency navigation user terminal obtains pseudorange value by measuring the signal of very low frequency navigation platform, then
Pseudorange value is modified using radio wave propagation correction model, resolves to obtain positioning result using revised pseudorange value.When very
Low frequency navigation user terminal can be received cloud framework radio wave propagation by radio communication unit and correct data processing centre
During wireless broadcast communication information, then unidirectional dumb radio waves propagation model parameter, so that by very low frequency navigation user terminal
Radio wave propagation correction model be changed to newest radio waves propagation model, repair the radio wave propagation in very low frequency navigation user terminal
Positive model is in optimal, ensures the revised user's positioning accuracy of radio wave propagation.
Corrected in cloud framework radio wave propagation in the minds of Data processing, based on historical data and measured data, structure electric wave passes
The step of broadcasting correction model and refined processing is as follows：
Step 1：The heart establishes preliminary radio wave propagation error correction anticipation function PPC (ω, P in data handlingt,Pr,,
Tymdt), this anticipation function is frequencies omega, time Tymdt, very low frequency navigation transmitting station position Pt, very low frequency navigation user terminal
The function of the position Pr of receiving point, includes global lower ionosphere electron concentration four-dimensional spacetime changing pattern in the function againGlobal lower ionosphere collision frequency spatial variations pattern v (h), Global Geomagnetic Field three dimensions changing patternUniversal Terrestrial conductivity two-dimensional space distribution patternUniversal Terrestrial dielectric constant two-dimensional space distributed mode
FormulaEtc. subfunction.
In formula
ω --- the angular frequency of-signal；
Tymdt----time value, including year (y), the moon (m), day (d), Hour Minute Second (t)；
λ ----Pt and the longitude on the whole great circle path of Pr point-to-point transmissions；
----Pt and the latitude on the whole great circle path of Pr point-to-point transmissions；
The longitude and latitude value of ----transmitting station；
The longitude and latitude value of ----receiving point；
When ----global lower ionosphere electron concentration is four-dimensional, empty changing pattern；
V (h) ----whole world lower ionosphere collision frequency spatial variations pattern；
----Global Geomagnetic Field three dimensions changing pattern；
----Universal Terrestrial conductivity two-dimensional space distribution pattern；
----Universal Terrestrial dielectric constant two-dimensional space distribution pattern.
According to (1) formula, the influence factor of very low frequency phase propagation is simplified and linearized, for known transmitting station position
Put, on given customer location and working frequency, obtain following prediction
PPC (t)=ω 0+ ∑ N (t)+∑ B (t)+∑ σ (t)+∑ ε (t) (2)
(2) in formula,
ω 0 is the very low frequency signal notional phase value calculated according to transmitting station to customer location in the ideal situation.It is assumed that
The very low frequency signal initial phase of transmitting station is zero, according to propagation distance and ripple of the very low frequency signal from transmitting station to customer location
Long relational expression is calculated.
∑ N (t) is ionosphere on transmitting station to customer location path, the segmentation to very low frequency signal phase effect adds up
Value.The basic data in ionosphere can be obtained by Global Ionospheric observation system.Ionosphere effect is to change over time, according to
Situation is shined upon on propagation path, 24 time zones will be divided daily, in each time zone, respectively according to propagation path
Segmentation carries out accumulation calculating, sets different phase effect coefficients in segmented paths, the value range of coefficient [- 20cec ,+
20cec], ∑ N (t) value ranges [- 150cec ,+150cec] finally accumulated, cec is the percentage week of very low frequency signal phase.
∑ B (t) is earth magnetic field on transmitting station to customer location path, the segmentation to very low frequency signal phase effect is tired out
Product value.The basic data in earth magnetic field can be calculated by general earth magnetic field model.It is to change over time that magnetic field, which influences,
, 24 time zones will be divided daily, in each time zone, carrying out segmentation accumulation according to changes of magnetic field respectively and calculating, dividing
Section sets different phase effect coefficients, the value range [- 2cec ,+2cec] of coefficient on path, and the ∑ B (t) finally accumulated takes
It is worth scope [- 50cec ,+50cec].
∑ σ (t) is the electrical conductivity on transmitting station to customer location path, the segmentation accumulation to very low frequency signal phase effect
Value.Electrical conductivity basic data is from geological exploration measurement bulletin.Electrical conductivity changes over time, and with Changes in weather and
Change, the time in 1 year is divided according to season, the moon, day, daily among, weather is influenced in units of hour into
Row weighting, weather take different weighting coefficients, weights scope [0.5,2] according to rain, snow, the moon, fine.In transmitting station to user position
On the path put, according to geology and the electrical conductivity value range [0.002,5] of hydrographic data, linear segmented sets different phases
Influence coefficient, the value range [- 5cec ,+5cec] of coefficient, it is final accumulate ∑ σ (t) value range [- 110cec ,+
110cec]。
∑ ε (t) is the dielectric constant on transmitting station to customer location path, and the segmentation to very low frequency signal phase effect is tired out
Product value.Dielectric constant basic data is from geological exploration measurement bulletin.Dielectric constant changes over time, and and weather
Change and change, the time in 1 year is divided according to season, the moon, day, among daily, to weather in units of hour
Influence is weighted, and weather takes different weighting coefficients, weights scope [0.9,1.1] according to rain, snow, the moon, fine.In transmitting station
Onto the path of customer location, according to geology and the dielectric constant value range [20,90] of hydrographic data, linear segmented is set not
With phase effect coefficient, the value range [- 2cec ,+2cec] of coefficient, it is final accumulate ∑ σ (t) value range [- 40cec,
+40cec]。
To the value range of finally cumulative PPC (t) at [- 350cec ,+350cec]
In very low frequency navigation system, the frequency of the position of transmitting station and launched signal is known, passes through the above
Method can obtain the radio waves propagation model parameter on different frequency and different user position.
Step 2：The real-time measurement values Δ ε of real-time reception very low frequency navigation radio wave propagation monitoring station, and radio wave propagation is missed
Wave Propagation Prediction value caused by difference amendment anticipation function PPC on the position of monitoring station is missed compared with measured value
Difference sigma=Δ ε-PPC.
Step 3：The error amount σ obtained according to step 2, using single order contiguous segmentation curve fitting algorithm, passes PPC electric waves
Broadcast ionosphere N (t) in forecast value revision function, magnetic field B (t), conductivityσ (t), the segment phase of permittivity ε (t) influence system
Number and weighting coefficient are adjusted, so that the error of curve matching is minimum, obtain the radio wave propagation error after parameter precision
Correct anticipation function PPC ' (ω, Pt,Pr,,Tymdt)。
Step 4：According to the modified history observation data of radio wave propagation, with reference to the meteorological and hydrogeological data conversion of history
Electrical conductivity and dielectric constant values, in radio wave propagation error correction anticipation function PPC ' (ω, the P that step 3 producest,Pr,,Tymdt) base
On plinth, processing is iterated with history observation data, using single order contiguous segmentation curve fitting algorithm, further adjusts PPC
Ionosphere N (t), magnetic field B (t), conductivityσ (t), the segment phase of permittivity ε (t) in Wave Propagation Prediction correction function
Influence coefficient and weighting coefficient so that the measured value of radio wave propagation is minimum with the statistical error of radio waves propagation model predicted value, obtains
Radio wave propagation correction model to after refining.
As shown in Figure 1, in the embodiment of the present invention, the very low frequency navigation electric wave propagation prediction framework based on cloud framework
Passed included in workspace according to several very low frequency navigation radio wave propagation monitoring stations 44 of certain regular distribution, cloud framework electric wave
Broadcast and correct data processing centre 33, very low frequency navigation user terminal 55, radio wave propagation monitoring station and cloud framework radio wave propagation amendment
Wired or wireless communication network, very low frequency navigation user terminal and cloud framework radio wave propagation between data processing centre correct number
According to the wireless channel in processing.Cloud framework radio wave propagation correct data processing centre 33 according to real-time received monitoring station data with
And the data such as meteorological and geology, prediction model is corrected with reference to historical data and existing radio wave propagation, passes through fitting and engineering
The methods of habit, adjustment radio wave propagation correct the parameter in prediction model so that radio wave propagation correct prediction model and measured value it
Between statistical error it is minimum.Cloud framework radio wave propagation corrects data processing centre 33 can be by One-to-All Broadcast communication channel, will
It is newest to obtain radio wave propagation and correct prediction model being sent to very low frequency navigation user terminal 55, very low frequency navigation user terminal 55
The error correction and positioning calculation of pseudorange value are measured using new radio wave propagation amendment prediction model, improves positioning accuracy.
When in very low frequency navigation working region, very low frequency navigation radio wave propagation monitoring station is set, in the way of shown in Fig. 2
Disposed.Multiple very low frequency navigation radio wave propagation monitoring stations and very low frequency navigation transmitting station be on straight line (or closely
Seemingly it is in a straight line), the distance R1 of the nearest very low frequency navigation radio wave propagation monitoring station of very low frequency navigation transmitting station, and
Spacing R2, Rn value between very low frequency navigation radio wave propagation monitoring station, takes propagate wavelength more than 10 times, for wavelength 10kHz
Very low frequency signal, spacing is more than 300km.
The equipment composition of very low frequency navigation radio wave propagation monitoring station is as shown in Figure 3.Very low frequency navigation monitoring receiver 11 is logical
Cross vlf receiving antenna and receive very low frequency navigation signal, ginseng is used as using the high stable Time and frequency standard that atomic frequency standard 16 exports
Signal is examined, measurement obtains real-time signal phase value, is sent to radio wave propagation monitoring and corrects integrated treatment computer 12.Electric wave
Propagate monitoring and correct integrated treatment computer 12 and receive the data such as the humiture from meteorological sensor 13 and atomic frequency standard
16 time data, by initial data such as signal phase value, meteorological data and the times of measurement, there are data record storage to set
In standby 15, by data filtering and fusion treatment, the monitoring station data of generation are sent to cloud framework electricity by communication network 14
Ripple, which is propagated, corrects data processing centre.Atomic frequency standard 16 uses rubidium atomic clock, and frequency stability is better than 10E-11.Meteorological sensor
13 include the sensors such as temperature sensor, humidity sensor and wind speed.
Cloud framework radio wave propagation corrects the data processing of data processing centre and storage uses cloud computing and cloud storage frame
Structure.Data processing centre is corrected in cloud framework radio wave propagation, it is as follows to carry out the method that radio wave propagation amendment prediction model is refined：
Step 1：The heart establishes preliminary radio wave propagation error correction anticipation function in data handlingThis anticipation function is frequencies omega, time Tymdt, very low frequency navigation transmitting station position Pt, very low frequency
The function of the position Pr for user terminal receiving point of navigating, includes global lower ionosphere electron concentration four-dimensional spacetime in the function again
Changing patternGlobal lower ionosphere collision frequency spatial variations pattern v (h), Global Geomagnetic Field three dimensions
Changing patternUniversal Terrestrial conductivity two-dimensional space distribution patternUniversal Terrestrial dielectric constant two dimension is empty
Between distribution patternEtc. subfunction.
ω --- the angular frequency of-signal；
Tymdt----time value, including year (y), the moon (m), day (d), Hour Minute Second (t)；
λ ----Pt and the longitude on the whole great circle path of Pr point-to-point transmissions；
----Pt and the latitude on the whole great circle path of Pr point-to-point transmissions；
The longitude and latitude value of ----transmitting station；
The longitude and latitude value of ----receiving point；
When ----global lower ionosphere electron concentration is four-dimensional, empty changing pattern；
V (h) ----whole world lower ionosphere collision frequency spatial variations pattern；
----Global Geomagnetic Field three dimensions changing pattern；
----Universal Terrestrial conductivity two-dimensional space distribution pattern；
----Universal Terrestrial dielectric constant two-dimensional space distribution pattern.
Simplified and linearized for the influence factor of very low frequency phase propagation, for known transmitting station position, to
Determine on customer location and working frequency, obtain following prediction
PPC (t)=ω 0+ ∑ N (t)+∑ B (t)+∑ σ (t)+∑ ε (t)
In PPC (t) formulas,
ω 0 is the very low frequency signal notional phase value calculated according to transmitting station to customer location in the ideal situation.It is assumed that
The very low frequency signal initial phase of transmitting station is zero, according to propagation distance and ripple of the very low frequency signal from transmitting station to customer location
Long relational expression is calculated.
∑ N (t) is ionosphere on transmitting station to customer location path, the segmentation to very low frequency signal phase effect adds up
Value.The basic data in ionosphere can be obtained by Global Ionospheric observation system.Ionosphere effect is to change over time, according to
Situation is shined upon on propagation path, 24 time zones will be divided daily, in each time zone, respectively according to propagation path
Segmentation carries out accumulation calculating, sets different phase effect coefficients in segmented paths, the value range of coefficient [- 20cec ,+
20cec], ∑ N (t) value ranges [- 150cec ,+150cec] finally accumulated, cec is the percentage week of very low frequency signal phase.
∑ B (t) is earth magnetic field on transmitting station to customer location path, the segmentation to very low frequency signal phase effect is tired out
Product value.The basic data in earth magnetic field can be calculated by earth magnetic field model.Magnetic field influences to change over time, will
24 time zones of division daily, in each time zone, carrying out segmentation accumulation according to changes of magnetic field respectively and calculating, in segmented paths
It is upper that different phase effect coefficients, the value range [- 2cec ,+2cec] of coefficient, ∑ B (t) value ranges finally accumulated are set
[- 50cec ,+50cec].
∑ σ (t) is the electrical conductivity on transmitting station to customer location path, the segmentation accumulation to very low frequency signal phase effect
Value.Electrical conductivity basic data is from geological exploration measurement bulletin.Electrical conductivity changes over time, and with Changes in weather and
Change, the time in 1 year is divided according to season, the moon, day, daily among, weather is influenced in units of hour into
Row weighting, weather take different weighting coefficients, weights scope [0.5,2] according to rain, snow, the moon, fine.In transmitting station to user position
On the path put, according to geology and electrical conductivity value range [0.002,5] Siemens of hydrographic data, linear segmented sets different
Phase effect coefficient, the value range [- 5cec ,+5cec] of coefficient, it is final accumulate ∑ σ (t) value range [- 110cec ,+
110cec]。
∑ ε (t) is the dielectric constant on transmitting station to customer location path, and the segmentation to very low frequency signal phase effect is tired out
Product value.Dielectric constant basic data is from geological exploration measurement bulletin.Dielectric constant changes over time, and and weather
Change and change, the time in 1 year is divided according to season, the moon, day, among daily, to weather in units of hour
Influence is weighted, and weather takes different weighting coefficients, weights scope [0.9,1.1] according to rain, snow, the moon, fine.In transmitting station
Onto the path of customer location, according to geology and the dielectric constant value range [20,90] of hydrographic data, linear segmented is set not
With phase effect coefficient, the value range [- 2cec ,+2cec] of coefficient, it is final accumulate ∑ σ (t) value range [- 40cec,
+40cec]。
To the value range of finally cumulative PPC (t) between [- 350cec ,+350cec].
Step 2：The real-time measurement values Δ ε of real-time reception very low frequency navigation radio wave propagation monitoring station, and radio wave propagation is missed
Wave Propagation Prediction value caused by difference amendment anticipation function PPC on the position of monitoring station is missed compared with measured value
Difference sigma=Δ ε-PPC.
Step 3：The error amount σ obtained according to step 2, using single order contiguous segmentation curve fitting algorithm, passes PPC electric waves
Broadcast the segmentation in forecast value revision function, the cumulative ionosphere of timesharing, magnetic field, electrical conductivity, dielectric constant phase effect coefficient and add
Weight coefficient is adjusted, so that the error of curve matching is minimum, the radio wave propagation error correction obtained after parameter precision is pre-
Survey function PPC ' (ω, Pt,Pr,,Tymdt)。
During using single order contiguous segmentation curve matching, based on data weighting and cubic Hamiltonian symmetrical systems, to segments
According to being fitted paragraph by paragraph, the single order continuity of matched curve is realized, reduce error of fitting.
Step 4：According to the modified history observation data of radio wave propagation, with reference to data conversions such as history meteorology, hydrogeologys
Electrical conductivity and dielectric constant values, step 3 produce radio wave propagation error correction anticipation function PPC ' (ω, Pt,Pr,,Tymdt)
On the basis of, the big data observed with history is iterated processing, further adjusts the correlation of radio wave propagation error correction model
Parameter so that the measured value of radio wave propagation is minimum with the statistical error of radio waves propagation model predicted value, the electric wave after being refined
Propagate correction model.
Cloud framework radio wave propagation corrects data processing centre on the basis of existing radio wave propagation Phase Prediction model, carries out
The frame of data processing is as shown in Figure 4.Cloud framework radio wave propagation corrects data processing centre and supervises very low frequency navigation radio wave propagation
Survey station real time data 17, very low frequency navigation radio wave propagation monitoring station historical data 18, existing radio wave propagation correct prediction model
19, and the exterior big data 21 such as meteorological data, hydrographic data, ionospheric data, geologic data, it is input to use processing
Unit 20, by data filtering and fusion, radio wave propagation correction model refined processing, the radio wave propagation after finally output is refined is repaiied
Positive prediction model 22.
When cloud framework radio wave propagation corrects data processing centre's data processing, handled using big data and machine learning is calculated
Method, carries out the elite of radio wave propagation correction model.The flow of radio wave propagation correction model refined processing is as shown in Figure 5.Will input
Monitoring station electric wave correct monitoring data 23, data processing is carried out to monitoring data, is transformed into the model training of signal characteristic
Sequence 24, is input to existing radio wave propagation and corrects in prediction model 25, using training sequence be sequentially completed unsupervised training and
The fine setting for having feedback optimizes, and then according to the parameter and model whether steady 26 in real time and after historical data training of judgement, is
No smoothly basis for estimation is exactly whether error restrains, if parameter and model are unstable, carries out model parameter adjustment 27, back and forth
Circulation is steady until model, so that exporting new radio wave propagation corrects prediction model 28.Cloud framework radio wave propagation is corrected at data
Prediction model is corrected in reason center using new radio wave propagation, further adjusts the relevant parameter of radio wave propagation error correction model,
So that the measured value of radio wave propagation monitoring station and the statistical error of radio waves propagation model predicted value are minimum, so that after being refined
Radio wave propagation corrects prediction model.
In very low frequency navigation user terminal, positioning process such as Fig. 6 institutes are modified using electric wave propagation prediction
Show.Very low frequency navigation user terminal is received by radio communicating channel and corrects Data processing from cloud framework radio wave propagation
After the model parameter data 36 of the heart, the electric wave newest model parameter data 36 being input in very low frequency navigation user terminal passes
Broadcast and correct in prediction model 37, radio wave propagation is corrected the parameter in prediction model is updated to last look.Very low frequency navigation user
The navigation signal that terminal is launched by reception and measurement very low frequency navigation platform, obtains very low frequency navigation signal measurement pseudorange value 34,
When positioning first, directly by very low frequency navigation signal measurement pseudorange value 34, it can be carried out without radio wave propagation correcting process
Navigator fix resolves 38 processing, so as to obtain latitude, longitude data 39.During follow-up positioning, then resolve 38 according to navigator fix and obtain
Latitude, longitude data 39, be input to radio wave propagation and correct in prediction model 37, obtain radio wave propagation correction value, carry out electric wave biography
Broadcast correcting process 35, correcting process then subtracts (or plus) correction value using measurement pseudorange value, utilizes revised pseudorange
Value, carries out navigator fix and resolves 38 processing, so as to obtain more accurate latitude, longitude data 39.
Claims (3)
1. a kind of very low frequency navigation electric wave propagation prediction refined method based on cloud framework, it is characterised in that including following steps
Suddenly：
Step 1, the very low frequency navigation radio wave propagation prison that several positions accurately measure is disposed in very low frequency navigation working region
Survey station, and the cloud framework radio wave propagation amendment of unicom very low frequency navigation radio wave propagation monitoring station and very low frequency navigation user terminal
Data processing centre；Data processing centre, which is corrected, in cloud framework radio wave propagation establishes radio wave propagation error correction anticipation function PPC
(t)=ω 0+ ∑ N (t)+∑ B (t)+∑ σ (t)+∑ ε (t), wherein, ω 0 be calculated according to transmitting station to customer location it is very low
Frequency signal theory phase value；∑ N (t) is ionosphere on transmitting station to customer location path, to very low frequency signal phase effect
Segmentation aggregate-value；∑ B (t) is earth magnetic field on transmitting station to customer location path, to very low frequency signal phase effect
It is segmented accumulated value；∑ σ (t) is the electrical conductivity on transmitting station to customer location path, the segmentation to very low frequency signal phase effect
Accumulated value；∑ ε (t) is the dielectric constant on transmitting station to customer location path, and the segmentation to very low frequency signal phase effect is tired out
Product value；
Step 2, the real-time measurement values Δ ε of real-time reception very low frequency navigation radio wave propagation monitoring station, and radio wave propagation error is repaiied
Wave Propagation Prediction value caused by positive anticipation function PPC on the position of monitoring station obtains error amount σ compared with measured value
=Δ ε-PPC；
Step 3, according to error amount σ, using single order contiguous segmentation curve fitting algorithm, to PPC Wave Propagation Prediction correction functions
In ionosphere N (t), magnetic field B (t), conductivityσ (t), the segment phase of permittivity ε (t) influence coefficient and weighting coefficient into
Row adjustment, so that the error of curve matching is minimum, obtains the radio wave propagation error correction anticipation function after parameter precision
PPC′(ω,Pt,Pr,,Tymdt)；
Step 4, data are observed according to the modified history of radio wave propagation, with reference to the conductance of the meteorological and hydrogeological data conversion of history
Rate and dielectric constant values, in PPC ' (ω, Pt,Pr,,Tymdt) on the basis of with history observation data be iterated processing, using one
Rank contiguous segmentation curve fitting algorithm, further adjusts ionosphere N (t), magnetic field B in PPC Wave Propagation Prediction correction functions
(t), conductivityσ (t), the segment phase of permittivity ε (t) influence coefficient and weighting coefficient so that the measured value of radio wave propagation
Minimum, the radio wave propagation correction model after being refined with the statistical error of radio waves propagation model predicted value.
2. the very low frequency navigation electric wave propagation prediction refined method according to claim 1 based on cloud framework, it is special
Sign is：The value range of the PPC (t) is [- 350cec ,+350cec], and cec is the percentage week of very low frequency signal phase.
3. the very low frequency navigation electric wave propagation prediction refined method according to claim 1 based on cloud framework, it is special
Sign is：The value range of the ∑ N (t) is [- 150cec ,+150cec]；The value range of the ∑ B (t) be [- 50cec,
+50cec]；The value range of the ∑ σ (t) is [- 110cec ,+110cec]；The value range of the ∑ ε (t) be [-
40cec ,+40cec].
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