CN105549007A - Vertical measurement ionogram reversion method based on overlapping polynomial model - Google Patents
Vertical measurement ionogram reversion method based on overlapping polynomial model 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
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
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Abstract
The invention discloses a vertical measurement ionogram reversion method based on an overlapping polynomial model. The method comprises the following steps: step A, preprocessing actually measured data; step B, based on a result of the preprocessing of the actually measured data, calculating an E-layer profile by use of the overlapping polynomial model; step C, based on the actually measured data preprocessing result and the E-layer profile, estimating a parameter valley width Wv and a valley depth Fv, and constructing corresponding valley layer parameter profiles; and step D, based on the actually measured data preprocessing result and the valley layer profiles, calculating an F-layer profile by use of the overlapping polynomial model. According to the vertical measurement ionogram reversion method based on the overlapping polynomial model, disclosed by the invention, a vertical measurement ionogram reversion method which is based on an overlapping polynomial model idea and is integrated with data preprocessing and valley layer profile searching optimization is brought forward, and the ionosphere inversion precision and stability can be effectively improved.
Description
Technical field
The present invention relates to PROGRESS OF IONOSPHERIC RESEARCH IN and application, particularly relate to a kind of vertical survey ionogram inversion method based on overlapping multinomial model.
Background technology
Ionospheric vertical sounding (be called for short hang down survey) technology is the detection method adopted the earliest in PROGRESS OF IONOSPHERIC RESEARCH IN history, although there are numerous Detection Techniques at present, the ionosphere survey technology that hangs down is still topmost ionospheric probing method.The vertical survey ionogram of reflection Ionospheric virtual height and frequency relation can be obtained by ionospheric vertical sounding.The virtual height surveying acquisition of hanging down not is the true reflection height of electromagnetic wave in ionosphere, true reflection height obtains to be needed to carry out inverting to vertical survey ionogram, and namely utilizing hangs down surveys ionogram frequency-virtual height trace inverting Ionospheric Profile (corresponding relation of layer height and plasma frequency or electron concentration).Hang down survey ionogram inverting to research ionospheric structure and ionosphere wave propagation problem significant, be subject to paying attention to very widely, certainly, inverting also has sizable difficulty all the time.
At present, applying comparatively general vertical survey ionogram inversion method is the Ionospheric Parameters inversion method developed based on direct computing method or type method thought, wherein, based on direct computing method thought, Titheridge etc. disclose a kind of method of overlapping polynomial expression inverting Ionospheric Profile, in the method, its true reflection height is calculated by the measurement virtual height on look-in frequency, in each frequency, consider to determine 5 multinomial coefficients above and below institute's two-part observed case of calculated rate, thus determine Ionospheric Profile.The weak point of the method is, directly based on actual detection data, thus the quality of data is larger to its Accuracy, a small amount of virtual height shortage of data can directly cause reference section to occur vibration, a large amount of shortage of datas will bring significantly distortion and the displacement of section, and due to detecting devices and ionospheric fading, the disappearance of actual detection virtual height data is inevitable; Have again, some are to the direct interpolation method of detection virtual height data, in conjunction with ionospheric propagation characteristic, good interpolation can be played to the low volume data disappearance that non-each layer faces frequently, but full of prunes interpolation result may be obtained to the shortage of data that more or mass data lack and each layer faces frequently, more increase the error of calculation of section.In addition, for " paddy layer " in Ionospheric Profile, be not specifically related in the method, but this does not meet actual conditions from physical significance yet.
Summary of the invention
Technical matters to be solved by this invention is just to provide a kind of vertical survey ionogram inversion method based on overlapping multinomial model.
The present invention adopts following technical scheme:
Based on a vertical survey ionogram inversion method for overlapping multinomial model, its improvements are, said method comprising the steps of:
Steps A, measured data pre-service;
Step B, based on the pretreated result of measured data, overlapping multinomial model is used to calculate E layer section;
Step C, based on measured data pre-processed results and E layer section, estimated parameter paddy is wide
dark with paddy
, and build corresponding paddy layer parameter section;
Step D, based on measured data pre-processed results and paddy layer section, overlapping multinomial model is used to calculate F layer section.
Further, described steps A is specially:
Steps A 1, the E layer building parabolic model and paddy layer section, multinomial model
layer and
layer section;
Steps A 2, based on set up ionospheric model, in conjunction with actual measurement virtual height data, under the constraint condition of section continuous and derivable, calculate virtual height according to ionospheric model and survey virtual height error and minimum criteria, obtaining by the method for search, iteration the parameter building ionospheric model;
Steps A 3, employing determine that the ionospheric model of parameter carries out extrapolation to disappearance measured data and compensates pre-service, form complete continuous print virtual height data.
Further, described step B specifically comprises:
Step B1, calculate E layer average group refractive index based on E layer virtual height data prediction result:
Symbol
for representing at wave frequency
and plasma frequency
the group refractive index at place
, group refractive index
there is following form
(1)
Wherein,
(2)
(3)
(4)
(5)
(6)
(7)
(8)
In formula,
for 300km place, vertical survey station overhead gyro-frequency,
for 300km place, vertical survey station overhead magnetic dip,
for wave frequency,
for plasma frequency;
At wave frequency
place,
with
between group refractive index corresponding to plasma frequency
average use
represent, for
,
in
, can accuracy be obtained by following formula higher
value:
(9)
And
(10)
at wave frequency
and plasma frequency
the group refractive index value at place;
Step B2, calculate E layer overlapping multinomial coefficient based on E layer virtual height data prediction result:
Frequency
with
between the high curve of reality be expressed as
(11)
This curve must can provide plasma frequency
on just really high, therefore have
(12)
(13)
Wherein
,
,
Formula (11) is differentiated
(14)
Thus in frequency
the reduction virtual height at place is (from height
measure) be:
(15)
Or
(16)
Wherein
(17)
Similar have
(18)
(19)
Wherein
(20)
(21)
Formula (12), formula (13), formula (16), formula (18) and formula (19) determine
with
five values, according to formula (11), frequency
reality high
for:
(22)
If meet formula (12), formula (13), formula (16), formula (18), formula (19) and formula (22)
value can be obtained, and so system of equations must be linear correlation, draws constant thus
with
there is following relation:
(23)
(24)
Frequency is determined by solving Simultaneous Equations (24)
5 multinomial coefficients
(
);
Can be obtained by above derivation
(25)
Wherein
time,
equal respectively
,
with
,
equal respectively
,
,
,
(26)
(27)
Integration in formula (25) is estimated by the Gaussian dependence formula of 5 points, wherein
and weights
for:
(28)
(29)
Corresponding each
value, first can calculate corresponding
with
value, for given magnetic field intensity and direction,
value only depend on
with
, from 5
value is corresponding calculates 5
value, and 5
value, then for
4
value is calculated by following formula (30):
(30)
Coefficient
with
after calculating, just can separate Simultaneous Equations (24) and obtain coefficient
, when
, repeat above computation process completely and can provide each frequency
5 multinomial coefficients, here because Simultaneous Equations (24) is an ill-conditioned linear systems to a certain extent, before solving equations, can significantly improve its accuracy in computation, so use following Simultaneous Equations during evaluator coefficient by difference between equation
(31)
Step B3, overlapping multinomial model is used to calculate E layer section based on E layer data pre-processed results:
Frequency
the reality at place is high
be expressed as:
(32)
In formula
with
it is wave frequency
,
with
the virtual height at place
,
with
reference
the value determined, it is by virtual height data
,
with
calculate and obtain:
(33)
(34)
(35)。
Further, described step C specifically comprises:
Step C1, Gu Kuan
dark with paddy
estimate:
After using overlapping multinomial model inverting complete E layer section based on E layer data after pre-service, according to E layer section maximal value, namely to face frequently corresponding reality high for E layer, estimates that paddy layer parameter paddy is wide
dark with paddy
, expression is:
，
(36)
Wherein
the reality of facing correspondence frequently for E layer is high,
According to the paddy layer parameter estimated, build " three-segment type " paddy layer, be specially:
(37)
Wherein
for E layer faces frequently, coefficient
with
by
with
determine for 2, coefficient
with
by
with
determine for 2;
Or increase " two segment types " paddy layer, be specially
(38)
Wherein coefficient
with
by
with
determine for 2, coefficient
with
by
with
determine for 2;
Step C2, F layer profile inversion:
(1) F layer maximum frequency is less than
corresponding real high of plasma frequency calculate:
When paddy layer parameter paddy is wide
dark with paddy
after tentatively estimating, based on data after structure three-segment type or two segment type paddy layer models and the pre-service of F layer, use the overlapping multinomial model of same step B to calculate F layer and be less than maximum frequency
reality corresponding to plasma frequency high;
(2) F layer maximum frequency
corresponding real high calculating:
Calculate maximum frequency
corresponding reality is high
need to determine
value, the ionosphere for stock size has:
(39)
In formula
represent frequency interval
(equal
),
the threshold frequency of presentation layer;
(3) F range upon range of mountains height calculates:
Use threshold frequency
calculate ionosphere peak height
, pass through frequency by parabola of fit
with
corresponding reality is high
with
realize, be specifically expressed as:
(40)
Step C3, Gu Kuan
dark with paddy
finally determine:
Vertical incidence radio wave attenuation real pass that is high and detection record virtual height in ionosphere is:
(41)
Wherein
for in electric wave ripple frequency
and plasma frequency
the group refractive index that place is corresponding, according to the section of above-mentioned steps inverting, calculates corresponding virtual height data based on the relation between real high and virtual height, then calculates actual measurement virtual height
error with calculating virtual height, is specially:
(42)
By the mode of optimizing in the wide and dark certain limit of paddy of paddy, will make
reach the wide and dark parameter of paddy of minimum paddy and be defined as paddy layer sectional parameter.
Further, described step D is specially:
Based on making actual measurement virtual height in step C and calculating virtual height error
reach minimum that group inverting F layer cross-sectional data, be defined as final F layer section.
Beneficial effect of the present invention is:
Vertical survey ionogram inversion method based on overlapping multinomial model disclosed in this invention, propose the vertical survey ionogram inversion algorithm of fused data pre-service based on overlapping multinomial model thought and the optimizing of paddy layer section, first it build polynomial expression ionospheric model; Then combine actual measurement virtual height data, under the constraint condition of section continuous and derivable, obtained the coefficient of polynomial expression ionospheric model by the method for search, iteration, thus the effective extrapolation realizing disappearance measured data compensates pre-service; Based on pretreated E layer virtual height data, by the overlapping multinomial model in ionosphere, solve the multinomial coefficient that each frequency is corresponding, directly calculate the Ionospheric Profile determining E layer; And mode of paddy dark optimizing wide by paddy increases standard scores segmentation paddy layer; Last based on paddy layer and pretreated F layer virtual height data, adopt the overlapping multinomial model in ionosphere, solve the multinomial coefficient that each frequency is corresponding, directly calculate and determine final Ionospheric Profile, can effectively improve ionospheric inversion precision and stability.
Accompanying drawing explanation
Fig. 1 is the process flow diagram of vertical survey ionogram inversion method disclosed in this invention;
Fig. 2 carries out the example of inverting for using the method disclosed in the present to three layers of ionosphere containing " two segment types " paddy layer;
Fig. 3 carries out the example of inverting for using the method disclosed in the present to three layers of ionosphere containing " three-segment type " paddy layer.
Embodiment
In order to make object of the present invention, technical scheme and advantage clearly understand, below in conjunction with embodiment, the present invention is further elaborated.Should be appreciated that specific embodiment described herein only in order to explain the present invention, be not intended to limit the present invention.
Embodiment 1, as shown in Figure 1, present embodiment discloses a kind of vertical survey ionogram inversion method based on overlapping multinomial model, said method comprising the steps of:
(1) Ionospheric Profile mathematical model is built:
The present invention by ionosphere modeling for comprise E layer, paddy layer,
layer,
four layer models of layer, E layer and paddy layer section are parabolic type,
layer and
layer section is polynomial type.Continuous and derivable characteristic is met in order to make the Electron density profile of foundation, at the tie point place of layer and layer, based on more than tie point and plasma frequency (square) value that calculates respectively of following ionospheric model and section gradient should be equal, according to this condition, limit the internal relation between correlation parameter.
(2) structure ionosphere model parameters is obtained:
The error of the virtual height calculated based on model and actual measurement virtual height and minimum criteria, obtain the sectional parameter that each layer is final:
1) E layer sectional parameter is obtained:
Determine three parameters of E layer section mainly
,
(or
),
, wherein
automatically can be provided by vertical survey ionogram interpretation software, error is less than 0.2MHz, adopt a kind of method of range searching to realize the determination choosing and build model parameter of E layer calculating virtual height in this method, be specially: suppose that the E layer actual measurement trace that the interpretation of vertical survey ionogram obtains has
individual, frequency of operation and the virtual height of its correspondence are respectively
with
, the E layer of reading faces frequently and minimum virtual height is designated as respectively
with
, then to parameter
,
,
?
,
,
(wherein
,
with
hunting zone controlled quentity controlled variable) obtain different group parameter with certain stepping value, each group parameter obtains according to the computing method of model E layer virtual height
individual point
, then calculate the error sum of squares of actual measurement virtual height and model calculating virtual height, make error sum of squares reach that minimum group parameter and be defined as E layer sectional parameter.
2) paddy layer sectional parameter is obtained:
?
in layer actual measurement trace, be greater than E layer face frequently and
the minimum virtual height of layer trace
data between corresponding frequency are more responsive to paddy layer parameter, therefore, in the refutation process of paddy layer parameter, select this part tracing point as the corresponding actual measurement virtual height of paddy layer, for choosing the corresponding calculating virtual height of paddy layer and determining paddy layer building model parameter, suppose total
individual, frequency of operation and the virtual height of its correspondence are respectively
with
.Calculated by least square method in this method
layer section coefficient, and by checking whether the coefficient calculated meets
layer section monotonically increasing characteristic, final search, iteration realize the acquisition of paddy layer sectional parameter.
3)
layer sectional parameter
Choose
in layer actual measurement trace,
frequency corresponding to layer trace minimum virtual height arrives
between data be used for determining
layer parameter, supposes total
individual data point, frequency of operation and the virtual height of its correspondence are respectively
with
.Have read
when,
layer section is by multinomial coefficient
determine completely, the method used during similar inverting paddy layer parameter can be adopted to calculate these coefficients.
4)
layer sectional parameter:
data in layer actual measurement trace are used for determining
layer parameter, supposes total
individual data point, frequency of operation and the virtual height of its correspondence are respectively
with
.Have read
when,
layer section is by coefficient
determine completely,
after layer parameter is determined,
layer with
the section gradient of layer point of intersection is also determined, therefore
the determination of layer building model parameter is a constrained optimization problem equally, can adopt similarly to determine
the method used during layer parameter is to calculate these coefficients.
5) finally determine paddy layer,
layer,
layer building model parameter:
For not reaching full growth
layer, the survey ionogram interpretation software that hangs down provides automatically
relative to
deviation when layer reaches full growth
a unknown quantity, in theory,
value between
, therefore, determine paddy layer,
layer,
during layer parameter, will
?
interior traversal, chooses and makes all data point calculation virtual heights and actual measurement virtual height error and minimum
corresponding paddy layer,
layer,
layer parameter as final paddy layer,
layer,
layer parameter.
(3) disappearance actual measurement virtual height Data Extrapolation compensates pre-service:
Based on the ionospheric model of above-mentioned structure, and in conjunction with the parameter of each layer building model that measured data obtains, calculate by model the extrapolation realizing disappearance measured data to compensate, continuous print preprocessed data in formation trend, for the calculating that follow-up reality is high provides high-quality data supporting.
(4) E layer frequency
real high to calculate:
Based on the pretreated result of measured data, suppose that E layer has
individual data point, frequency of operation and the virtual height of its correspondence are respectively
with
, based on the overlapping multinomial model of 5 coefficients, calculated rate
(
) corresponding reality is high
.Be specially:
1) evaluator coefficient and average group refractive index
(frequency of operation and virtual height are respectively to compensate pretreated result based on measured data extrapolation
with
(
)), use formula (31) to calculate each frequency
(
) corresponding 5 multinomial coefficients; Use formula (1)-formula (8) calculates wave frequency
and plasma frequency
the group refractive index at place is
; Use formula (9) and (10) calculate wave frequency
place,
with
between the average of group refractive index corresponding to plasma frequency be
value.
2) reality calculating first three frequency is high:
Setpoint frequency
,
corresponding reality is high
,
be equal to virtual height
, calculate by formula (43)
value, then the overlapping polynomial computation of 5 coefficients representing of through type (44) obtains frequency
reality high
.
(43)
(44)
3) reality calculating other frequency of E layer is high:
The overlapping polynomial expression of 5 coefficients that use formula (32) represents is determined real high in turn
(
), in formula
use formula (33)-formula (35) calculates and obtains.
(5) preset paddy layer parameter to calculate F layer real high:
Based on the pretreated result of measured data, suppose that F layer has
individual data point, frequency of operation and the virtual height of its correspondence are respectively
with
.Estimate that paddy is wide according to above-mentioned paddy layer parameter evaluation method
dark with paddy
, and build corresponding paddy layer parameter section, adopt the overlapping multinomial model calculated rate of 5 coefficients
(
) corresponding reality is high
.Be specially:
1) paddy layer parameter is set
Wide according to formula (36) preset paddy
dark with paddy
value, and use formula (37) or formula (38) model construction paddy layer section.
2) evaluator coefficient and average group refractive index
Method calculates with above-mentioned E layer, wherein uses
value is set to E layer and faces frequently
.
3) reality calculating first three frequency is high
Setpoint frequency
,
corresponding reality is high
,
equal respectively to build paddy layer section model in frequency
,
the value of extrapolation
,
; Calculate in order to following formula (45)
value, then the overlapping polynomial computation of 5 coefficients representing of through type (44) obtains frequency
reality high
.
(45)
(46)
(47)
(48)
4) calculate F layer and be less than maximum frequency
reality corresponding to plasma frequency high
The overlapping polynomial expression of 5 coefficients that use formula (32) represents is determined real high in turn
(
), in formula
use formula (33) and (34) calculate and obtain, and are calculated by (49)
value.
(49)
5) maximum frequency is calculated
corresponding real high
Use formula (31) calculates
5 corresponding multinomial coefficients; In conjunction with actual measurement threshold frequency
, use formula (39) to calculate
value; The overlapping polynomial computation maximum frequency of 5 coefficients then using formula (32) to represent
corresponding real high
value.
6) ionosphere peak height is calculated
In conjunction with actual measurement threshold frequency
, use formula (40) to calculate ionosphere peak height
value.
(6) error of calculation and actual measurement virtual height data
According to the section of above-mentioned steps inverting, use formula (41) to calculate corresponding virtual height data, then calculate actual measurement virtual height according to formula (42)
virtual height is calculated with model
between error.
(7) final section is determined
It is wide that paddy is set
dark with paddy
?
,
various combination parameter is obtained with certain stepping value in scope, each group parameter repeats the error that above step (5) and (6) obtain surveying virtual height and calculating virtual height, makes error reach minimum that and organizes paddy layer parameter and section is defined as final paddy layer parameter and section.
Fig. 2 and Fig. 3 gives two the inverting examples adopting the inventive method, and Fig. 2 inverting section is containing " two segment types " paddy layer, and Fig. 3 inverting section is containing " three-segment type " paddy layer.Wherein measured data hangs down to surveying the sentence read result of ionogram interpretation software, this be one typical three layers (E layer,
layer and
layer),
the underdeveloped Ionospheric Echo trace of layer.In the present invention, based on structure ionospheric model, compensation (black is punctuated) of effectively extrapolating is achieved to disappearance measured data; Use the present invention is based on overlapping polynomial vertical survey ionogram inversion method and obtains more level and smooth and accurate Ionospheric Profile (black dash line), is significantly better than only adopting the profile inversion result (solid black lines) of measured data and the profile inversion result (black dotted line) of the direct interpolation of measured data.Overcome more in polynomial expression inversion method or mass data disappearance, each layer faces the shortage of data frequently and significantly increase in conjunction with the section error of calculation that the direct interpolation of a large amount of missing data of ionospheric propagation characteristic causes, the even defect of mistake; And reasonably consider in inverting section in esse " paddy layer ", make ionospheric inversion precision and stability higher.
Claims (5)
1., based on a vertical survey ionogram inversion method for overlapping multinomial model, it is characterized in that, said method comprising the steps of:
Steps A, measured data pre-service;
Step B, based on the pretreated result of measured data, overlapping multinomial model is used to calculate E layer section;
Step C, based on measured data pre-processed results and E layer section, estimated parameter paddy is wide
dark with paddy
, and build corresponding paddy layer parameter section;
Step D, based on measured data pre-processed results and paddy layer section, overlapping multinomial model is used to calculate F layer section.
2. a kind of vertical survey ionogram inversion method based on overlapping multinomial model according to claim 1, it is characterized in that, described steps A is specially:
Steps A 1, the E layer building parabolic model and paddy layer section, multinomial model
layer and
layer section;
Steps A 2, based on set up ionospheric model, in conjunction with actual measurement virtual height data, under the constraint condition of section continuous and derivable, calculate virtual height according to ionospheric model and survey virtual height error and minimum criteria, obtaining by the method for search, iteration the parameter building ionospheric model;
Steps A 3, employing determine that the ionospheric model of parameter carries out extrapolation to disappearance measured data and compensates pre-service, form complete continuous print virtual height data.
3. a kind of vertical survey ionogram inversion method based on overlapping multinomial model according to claim 1, it is characterized in that, described step B specifically comprises:
Step B1, calculate E layer average group refractive index based on E layer virtual height data prediction result:
Symbol
for representing at wave frequency
and plasma frequency
the group refractive index at place
, group refractive index
there is following form
(1)
Wherein,
(2)
(3)
(4)
(5)
(6)
(7)
(8)
In formula,
for 300km place, vertical survey station overhead gyro-frequency,
for 300km place, vertical survey station overhead magnetic dip,
for wave frequency,
for plasma frequency;
At wave frequency
place,
with
between group refractive index corresponding to plasma frequency
average use
represent, for
,
in
, can accuracy be obtained by following formula higher
value:
(9)
And
(10)
at wave frequency
and plasma frequency
the group refractive index value at place;
Step B2, calculate E layer overlapping multinomial coefficient based on E layer virtual height data prediction result:
Frequency
with
between the high curve of reality be expressed as
(11)
This curve must can provide plasma frequency
on just really high, therefore have
(12)
(13)
Wherein
,
,
Formula (11) is differentiated
(14)
Thus in frequency
the reduction virtual height at place is (from height
measure) be:
(15)
Or
(16)
Wherein
(17)
Similar have
(18)
(19)
Wherein
(20)
(21)
Formula (12), formula (13), formula (16) formula (18) and formula (19) determine
with
five values, according to formula (11), frequency
reality high
for:
(22)
If meet formula (12), formula (13), formula (16), formula (18), formula (19) and formula (22)
value can be obtained, and so system of equations must be linear correlation, draws constant thus
with
there is following relation:
(23)
(24)
Frequency is determined by solving Simultaneous Equations (24)
5 multinomial coefficients
(
);
Can be obtained by above derivation
(25)
Wherein
time,
equal respectively
,
with
,
equal respectively
,
,
,
(26)
(27)
Integration in formula (25) is estimated by the Gaussian dependence formula of 5 points, wherein
and weights
for:
(28)
(29)
Corresponding each
value, first can calculate corresponding
with
value, for given magnetic field intensity and direction,
value only depend on
with
, from 5
value is corresponding calculates 5
value, and 5
value, then for
4
value is calculated by following formula (30):
(30)
Coefficient
with
after calculating, just can separate Simultaneous Equations (24) and obtain coefficient
, when
, repeat above computation process completely and can provide each frequency
5 multinomial coefficients, here because Simultaneous Equations (24) is an ill-conditioned linear systems to a certain extent, before solving equations, can significantly improve its accuracy in computation, so use following Simultaneous Equations during evaluator coefficient by difference between equation
(31)
Step B3, overlapping multinomial model is used to calculate E layer section based on E layer data pre-processed results:
Frequency
the reality at place is high
be expressed as:
(32)
In formula
with
it is wave frequency
,
with
the virtual height at place
,
with
reference
the value determined, it is by virtual height data
,
with
calculate and obtain:
(33)
(34)
(35)。
4. a kind of vertical survey ionogram inversion method based on overlapping multinomial model according to claim 1, it is characterized in that, described step C specifically comprises:
Step C1, Gu Kuan
dark with paddy
estimate:
After using overlapping multinomial model inverting complete E layer section based on E layer data after pre-service, according to E layer section maximal value, namely to face frequently corresponding reality high for E layer, estimates that paddy layer parameter paddy is wide
dark with paddy
, expression is:
，
(36)
Wherein
the reality of facing correspondence frequently for E layer is high,
According to the paddy layer parameter estimated, build " three-segment type " paddy layer, be specially:
(37)
Wherein
for E layer faces frequently, coefficient
with
by
with
determine for 2, coefficient
with
by
with
determine for 2;
Or increase " two segment types " paddy layer, be specially
(38)
Wherein coefficient
with
by
with
determine for 2, coefficient
with
by
with
determine for 2;
Step C2, F layer profile inversion:
(1) F layer maximum frequency is less than
corresponding real high of plasma frequency calculate:
When paddy layer parameter paddy is wide
dark with paddy
after tentatively estimating, based on data after structure three-segment type or two segment type paddy layer models and the pre-service of F layer, use the overlapping multinomial model of same step B to calculate F layer and be less than maximum frequency
reality corresponding to plasma frequency high;
(2) F layer maximum frequency
corresponding real high calculating:
Calculate maximum frequency
corresponding reality is high
need to determine
value, the ionosphere for stock size has:
(39)
In formula
represent frequency interval
(equal
),
the threshold frequency of presentation layer;
(3) F range upon range of mountains height calculates:
Use threshold frequency
calculate ionosphere peak height
, pass through frequency by parabola of fit
with
corresponding reality is high
with
realize, be specifically expressed as:
(40)
Step C3, Gu Kuan
dark with paddy
finally determine:
Vertical incidence radio wave attenuation real pass that is high and detection record virtual height in ionosphere is:
(41)
Wherein
for in electric wave ripple frequency
and plasma frequency
the group refractive index that place is corresponding, according to the section of above-mentioned steps inverting, calculates corresponding virtual height data based on the relation between real high and virtual height, then calculates actual measurement virtual height
error with calculating virtual height, is specially:
(42)
By the mode of optimizing in the wide and dark certain limit of paddy of paddy, will make
reach the wide and dark parameter of paddy of minimum paddy and be defined as paddy layer sectional parameter.
5. a kind of vertical survey ionogram inversion method based on overlapping multinomial model according to claim 1, it is characterized in that, described step D is specially:
Based on making actual measurement virtual height in step C and calculating virtual height error
reach minimum that group inverting F layer cross-sectional data, be defined as final F layer section.
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