CN113219414A - Novel method for eliminating earth surface deformation direction ambiguity of satellite interference radar - Google Patents
Novel method for eliminating earth surface deformation direction ambiguity of satellite interference radar Download PDFInfo
- Publication number
- CN113219414A CN113219414A CN202110436113.6A CN202110436113A CN113219414A CN 113219414 A CN113219414 A CN 113219414A CN 202110436113 A CN202110436113 A CN 202110436113A CN 113219414 A CN113219414 A CN 113219414A
- Authority
- CN
- China
- Prior art keywords
- radar
- earth surface
- deformation
- satellite
- interference
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 41
- 239000011159 matrix material Substances 0.000 claims abstract description 31
- 238000005315 distribution function Methods 0.000 claims abstract description 8
- 238000004364 calculation method Methods 0.000 claims description 8
- 238000006073 displacement reaction Methods 0.000 claims description 8
- 230000000694 effects Effects 0.000 claims description 5
- 230000001174 ascending effect Effects 0.000 claims description 4
- 239000013074 reference sample Substances 0.000 claims description 3
- 230000002194 synthesizing effect Effects 0.000 claims description 3
- 239000000126 substance Substances 0.000 claims description 2
- 238000012544 monitoring process Methods 0.000 abstract description 10
- 238000005259 measurement Methods 0.000 description 5
- 238000010586 diagram Methods 0.000 description 4
- 230000007547 defect Effects 0.000 description 3
- 230000000630 rising effect Effects 0.000 description 3
- 239000002689 soil Substances 0.000 description 3
- 238000010276 construction Methods 0.000 description 2
- 238000005457 optimization Methods 0.000 description 2
- 238000012360 testing method Methods 0.000 description 2
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 2
- 238000013459 approach Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000007596 consolidation process Methods 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- 238000003384 imaging method Methods 0.000 description 1
- 230000007774 longterm Effects 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 230000035699 permeability Effects 0.000 description 1
- 238000007781 pre-processing Methods 0.000 description 1
- 230000002265 prevention Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 239000000523 sample Substances 0.000 description 1
- 230000009897 systematic effect Effects 0.000 description 1
- 238000012795 verification Methods 0.000 description 1
- 238000003809 water extraction Methods 0.000 description 1
Images
Classifications
-
- 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
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
- G01S7/023—Interference mitigation, e.g. reducing or avoiding non-intentional interference with other HF-transmitters, base station transmitters for mobile communication or other radar systems, e.g. using electro-magnetic interference [EMI] reduction techniques
-
- 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
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
- G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
- G01S7/418—Theoretical aspects
Abstract
The invention discloses a novel method for eliminating earth surface deformation direction ambiguity of a satellite interference radar, which comprises the steps of utilizing the relation between phase differences among a plurality of satellite interference radar image pairs and distances among orbits, combining a weighted least square method, utilizing probability density distribution functions of different coherence phases to calculate the variance of the satellite interference radar image pairs, and taking the inverse matrix of a variance matrix as a weighted matrix so as to determine the horizontal and vertical motion deformation of the earth surface. The multi-mode satellite-borne radar interferogram integrating the multi-beam or lifting rail eliminates the interference of system errors on the earth surface deformation observed by the satellite interference radar, improves the accuracy of the satellite interference radar for observing and acquiring the three-dimensional deformation of the earth surface, and can be applied to real earth surface three-dimensional deformation such as ground settlement, landslide and the like, and provides reliable technical support for real-time dynamic and macroscopic large-scale monitoring.
Description
Technical Field
The invention belongs to the technical field of radar monitoring, and particularly relates to a new method for eliminating earth surface deformation direction ambiguity of a satellite interference radar.
Background
With the increasing speed of urban construction, the hazard of surface deformation to human living environment constitutes a potential risk. The ground surface deformation mainly comprises instantaneous sudden deformation and continuous slow deformation, the instantaneous sudden deformation refers to deformation caused by natural factors such as volcanic eruption, debris flow, tsunami, earthquake motion and the like, the continuous slow deformation mainly induces ground subsidence and the like caused by large-scale urban engineering construction and excessive underground water extraction, the ground subsidence has the characteristics of slow cause development, long duration and high prevention and control difficulty, and the ground subsidence causes great harm to high-speed railways, buildings, infrastructures, lifeline engineering and the like. Therefore, it is important to continuously monitor the slow deformation such as ground subsidence for a long time.
At present, the common ground surface deformation monitoring method mainly adopts equipment such as a precise level gauge, a distance meter, a GPS, a bedrock mark, a layered mark and the like to measure deformation information of the ground surface based on a single-point or net arrangement method, has high monitoring precision, but consumes a large amount of manpower and material resources, is difficult to carry out deformation monitoring in a large scale range, and has the advantages of all-time, all-weather, wide coverage, repeatable observation, high precision and the like by a satellite interference monitoring technology, thereby providing an effective means for high-precision ground surface deformation monitoring. However, the radar measures the skew distance, so that it is not possible to distinguish whether the displacement is from the horizontal direction or the vertical direction, i.e. there is a directional ambiguity. The satellite interference radar measurement only acquires the ground surface deformation component along the radar sight (LoS), and cannot acquire the three-dimensional deformation (vertical, east-west and north-south deformation) of the real ground surface, namely the ground surface deformation direction of the satellite interference radar is fuzzy, so that the defects limit the field of monitoring the three-dimensional deformation of the real ground surface of the satellite interference radar in the fields of ground settlement, landslide, volcanic activity, earthquake and the like.
The satellite interference radar deformation observation has the defect of inherent direction ambiguity in the slope distance measurement, and is easy to receive the interference of system errors on the earth surface deformation, thereby causing the problem of space-time incoherent observation. Therefore, a new method for eliminating the ambiguity of the earth surface deformation direction of the satellite interference radar is needed.
Disclosure of Invention
The invention aims to provide a novel method for eliminating the ambiguity of the earth surface deformation direction of a satellite interference radar, which aims to solve the problems in the prior art.
In order to achieve the purpose, the invention adopts the following technical scheme:
the invention comprises the following steps:
s1: collecting radar observation data at different moments and track pitch angle and azimuth angle data of two groups of tracks;
s2, forming a space-time interference structure according to the radar observation data at different moments, synthesizing a Doppler function by utilizing the estimation of the pitch angle and the azimuth angle of the two tracks to obtain the optimal interference correlation, and calculating the difference between the two tracks to obtain a phase difference to estimate the surface deformation quantity;
s3: and eliminating residual stripes of the system by performing least square matching on the ground true value and the phase gradient of the model.
S4: according to the satellite interference radar image pairs of the ascending orbit and the descending orbit, the distance relation between the phase difference and the orbit between the interference radar image pairs is utilized, the weighted least square method is combined, the probability density distribution function of different coherence phases is utilized to calculate the variance and construct a variance matrix;
s5: and calculating a horizontal motion component and a vertical motion component of the earth surface deformation by using the inverse matrix of the variance matrix as a weighting matrix so as to eliminate the earth surface deformation influence of the satellite interference radar.
Further, the calculation formula of the phase difference obtained by differentiating the two tracks in the step S2 is as follows
Where λ is the carrier wavelength, Δ RdIs the amount of surface deformation, B1Is a base line, θ1For radar angle of incidence, α1Is an angle of inclination.
Is caused by topographic effects, and the influence of the topographic terms should be removed only when considering the deformation.
Further, the method for eliminating the residual fringes of the system in step S3 includes generating a reference interferogram, and estimating coefficients in the phase gradient by a least square method using a true terrestrial phase gradient sample of the flat area, so as to eliminate the residual fringes of the system, wherein the reference interferogram is represented as a second order polynomial function of the slant range r and the azimuth time:
with the true ground of the flat region, the phase gradient samples in the r and eta directions are selected, coefficient a1，a2，a3，a4The estimation can be performed by a least squares method.
Wherein n is the selected reference sample number; min is the minimization operation.
Further, the calculation formula of the phase difference Φ between the n interference SAR image pairs in the step S4 is
Φ＝4πδr/Λ
Wherein phi is [ psi1，ψ2，ψ3...ψn]T，δr/Λ＝[δr1/λ1，δr2/λ2，δr3/λ3，..δrn/λn]T，λ1，λ2λ3，...λnThe carrier wavelengths of the 1 st, 2 nd, 3 rd, … … th, n-th satellite interferometric radar pairs are indicated.
Further, the phase difference Φ is phase unwrapped to invert the slope δ r. Amount of deformation (dx)2+dy2+dz 2)1/2The relationship with the skew distance delta r is
Ax＝δr
Wherein
And is
Wherein theta is1，θ2，...θnIs the angle of incidence of the 1 st, 2 nd, 3 rd, … … th, n-th interference image pair; beta is a1，β2，...βnIs the tracking angle of the 1 st, 2 nd, 3 rd, … … th, n image pairs (clockwise from north); dx, dy, dz may be the three unknown displacement components in the east-west, north-south and vertical directions, respectively.
To estimate the unknown displacement x, | Ax- δ r non-calculation from n interference pairs2To obtain a weighted least squares solution, to use a weighted least squares method, i.e., a solution where WAx is W δ r, where W is a weighting matrix,
wherein C ═ WTW, the weight of each pair of interferograms may be determined by the quality of the interferograms in terms of coherence, baseline, etc.
Further, in step S5, the variance is calculated according to the probability density distribution function theorem of different coherence phases, and then the inverse matrix of the variance matrix is used as the weighting matrix to eliminate the ambiguity in the three-dimensional direction at the slant angle. The variance is calculated as follows:
wherein sigma2＝∫ψ2pψ(ψ)dψ；pψAnd (psi) an interference phase probability density function.
Further, the calculation formula of the horizontal motion component and the vertical motion component of the surface deformation in step S5 is as follows:
wherein the content of the first and second substances,
three unknown bits in east-west, north-south and vertical directionsThe amount of the shift. Component of deformation, C ═ wTW, W are weighting matrices, δ r the distance between the tracks, Ax ═ δ r.
Compared with the prior art, the invention has the beneficial effects that:
the multi-mode satellite-borne radar interferogram integrating the multi-beam or lifting rail eliminates the interference of system errors on the earth surface deformation observed by the satellite interference radar, improves the accuracy of the satellite interference radar for observing and acquiring the three-dimensional deformation of the earth surface, and can be applied to real earth surface three-dimensional deformation such as ground settlement, landslide and the like, and provides reliable technical support for real-time dynamic and macroscopic large-scale monitoring.
Drawings
FIG. 1 is a flow chart of a new method for eliminating ambiguity of earth surface deformation direction of a satellite interference radar according to the present invention;
FIG. 2 is an exemplary illustration of a color synthetic satellite image overlaid on a DEM with an ALOS PALSAR acquired image of a geographic location of a study area of the present invention;
FIG. 3 is a comparison graph of original satellite interference radar fringes and reference and fine satellite interference radar fringes after the system residual effect is eliminated by a least square method according to the invention;
FIG. 4 is an imaging geometry of a satellite interferometric radar image pair s1, s2 obtained from radar left and right views in accordance with the present invention;
FIG. 5 is a three sets of surface deformation patterns observed along the slope at different times in the area of interest in accordance with the present invention;
FIG. 6 is a three-dimensional component diagram of the earth's surface deformation after the direction ambiguity is eliminated by the least square method by integrating the data of the up-tracking and down-tracking satellite interference radar of the present invention, and a comparison diagram of the three-dimensional component diagram and the vertical settlement of the precise leveling measurement.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments.
The new method for eliminating the satellite interference radar earth surface deformation direction ambiguity based on the weighting optimization is described below by taking an actual scene example, and the authenticity of the InSAR settlement map obtained by the method is verified by comparing the settlement map with the precise leveling result of the test field.
As shown in fig. 1, the present invention comprises the steps of:
s1: collecting radar observation data at different moments and track pitch angle and azimuth angle data of two groups of tracks;
the research site example of the invention is a turbid stream alluvial fan located in Zhaohui county and Yunlin county in Taiwan, the total area of the region is 2364 square kilometers, the average altitude is below 100 meters, the region is an important agricultural region, the strength and the permeability of the soil are low, the water level is easy to obviously reduce due to excessive extraction of underground water from the soil layer, and the soil layer consolidation is easy to suffer from serious ground settlement. FIG. 2 is an example of a color synthetic satellite image overlaid on a DEM with an ALOS PALSAR acquired image of the geographic location of the area under study in accordance with the present invention;
s2, forming a space-time interference structure according to the radar observation data at different moments, synthesizing a Doppler function by utilizing the estimation of the pitch angle and the azimuth angle of the two tracks to obtain the optimal interference correlation, and calculating the difference between the two tracks to obtain a phase difference to estimate the surface deformation quantity;
the phase difference obtained by differentiating the two tracks is
Where λ is the carrier wavelength, Δ RdIs the amount of surface deformation, B1Is a base line, θ1For radar angle of incidence, α1Is an angle of inclination.
Is caused by topographic effects, and the influence of the topographic terms should be removed only when considering the deformation.
S3: and eliminating residual fringes of the phase difference of the system by performing least square matching on the ground true value and the phase gradient of the model.
Residual fringes may exist due to preprocessing errors associated with small estimation parameters such as doppler coefficients. By generating a reference interferogram, coefficients in the phase gradient are estimated by a least square method by means of real ground phase gradient samples of a flat area, thereby eliminating residual fringes of the system. The reference interferogram is represented as a second order polynomial function of the slope distance r and the azimuth time η:
the phase gradients in the r and η directions are:
with the true ground of the flat region, samples of the phase gradient in the r and η directions are selected. The estimation of the coefficient a in the phase gradient can be performed by the least squares method1，a2，a3，a4。
Wherein n is a selected reference sample; min is the minimization operation.
Using the ALOS-PALSAR data of 23/11/2008 and 18/2/2007, fig. 3(a) and (b) show the original fringes without residual fringes removed and the original differential fringes, respectively, it can be easily seen that there are still fringes along the rugged mountain area that resemble the contour of the terrain and these fringes should be removed. The simulated reference fringes are given in fig. 3(c), which gives the clear fringes resulting from systematic error over the entire area. By subtracting the original fringe pattern 3(b) from fig. 3(c), a fine differential fringe pattern as shown in fig. 3(d) can be obtained, so that the residual fringe pattern covering the spurious information has been reduced to an acceptable level.
S4: according to the satellite interference radar image pairs of the ascending orbit and the descending orbit, the distance relation between the phase difference and the orbit between the interference radar image pairs is utilized, the weighted least square method is combined, the probability density distribution function of different coherence phases is utilized to calculate the variance and construct a variance matrix;
the phase difference between n interference image pairs is related to the distance between tracks, δ r
Φ＝4πδr/Λ
Wherein phi is [ psi1，ψ2，ψ3...ψn]T，δr/Λ＝[δr1/λ1，δr2/λ2，δr3/λ3，..δrn/λn]T，λ1，λ2，λ3，...λnRepresenting the carrier wavelengths of the 1 st, 2 nd, 3 rd, … … th, n-th interference image pair.
Phase unwrapping is performed to invert the slope distance δ r. Amount of deformation (dx)2+dy2+dz2)1/2The relationship with the skew distance delta r is
Ax＝δr
Wherein
And is
Wherein theta is1，θ2，...θnIs the angle of incidence of the 1 st, 2 nd, 3 rd, … … th, n-th interference image pair; beta is a1，β2，...βnIs the tracking angle of the 1 st, 2 nd, 3 rd, … … th, n image pairs (clockwise from north); dx, dy, dz may be the three unknown displacement components in the east-west, north-south and vertical directions, respectively.
The earth surface deformation causes phase change among repeated orbit observation, but the phase change has no direction information of deformation amount, so that the earth surface deformation is from the starThe deformation obtained from the radar data can not directly obtain the vertical or horizontal component of the deformation, and the method can eliminate the problem of fuzzy ground deformation direction of the satellite interference radar based on weighting optimization. As shown in FIG. 4, consider two pairs of interferograms, s1，s2Respectively, an ascending rail, a right-side view, a descending rail and a left-side view. Between two observations, the ground point is displaced from p to p ', we want to know the horizontal motion component dx, dy and the vertical motion component dz of the deformation quantity | p-p' |.
To estimate the unknown displacement x from n interferometric pairs, we seek | Ax- δ r2To obtain a weighted least squares solution. To obtain the best estimate, a weighted least squares approach, i.e., a solution of WAx ═ W δ r, where W is the weighting matrix,
wherein C ═ WTW, the weight of each pair of interferograms may be determined by the quality of the interferograms in terms of coherence, baseline, etc.
S5: and calculating a horizontal motion component and a vertical motion component of the earth surface deformation by using the inverse matrix of the variance matrix as a weighting matrix so as to eliminate the earth surface deformation influence of the satellite interference radar.
The variance is solved according to the probability density distribution function theoretical expression of different coherence phases, and the inverse matrix of the variance matrix is used as a weighting matrix to eliminate the ambiguity in the three-dimensional direction on the slant range.
Wherein sigma2＝∫ψ2pψ(ψ)dψ；pψAnd (psi) a phase probability density function.
As shown in fig. 5, the three deformation observation data sets obtained after phase unwrapping along the skew have the same observed deformation in the down-track and up-track modes, and the ambiguity of the deformation direction can be eliminated according to the above steps.
As shown in fig. 6(a), a three-dimensional component diagram of the earth surface deformation after the direction ambiguity is eliminated by using the least square method is given by integrating the rising orbit and falling orbit star interference radar data: the dx, dy, dz components, in centimeters per year (cm/yr). As is apparent from fig. 6(a), due to the characteristics of the satellite orbit, the x, y components along the satellite orbit have only noise levels, which are negligible, and the vertical deformation (z component) whether uplift or settlement, which is mainly caused by the vertical motion due to settlement, can be accurately estimated, especially in the vicinity of the epicenter, and the magnitude of the horizontal motion is small. In order to verify the authenticity of the settlement map of the satellite interference radar obtained by the invention, a mutual superposition map of the settlement map measured by the satellite interference radar and a precision leveling result of a test field is shown in fig. 6(b), a contour line takes centimeter/year (cm/yr) as a unit, the settlement map and the precision leveling result have excellent consistency both in quantity and quality, the epicenter position is consistent with the spatial deformation distribution, and the verification result well verifies the effectiveness of a new method for determining whether the ground surface deformation is a bump type or a settlement type by integrating the orbit lifting data and the orbit lowering data. The result shows that under the centimeter resolution, the satellite interference radar detection result and the leveling result have good consistency no matter in a space mode or in a scale, so that the authenticity of the satellite interference radar settlement map obtained by the method is verified. The new method provided by the invention shows that the reliable deformation estimation at different dip angles combines the multi-mode radar observation data of long-term observation and short-term observation.
The invention provides a novel method for eliminating the fuzzy direction of the earth surface deformation of a satellite interference radar, which can effectively estimate the three-dimensional deformation of the real earth surface. Aiming at the defect that the satellite interference radar deformation observation has inherent direction ambiguity in the slope distance measurement, the invention combines the satellite interference radar image pairs of the two observation modes of the rising orbit and the falling orbit based on the measurement of the rising orbit and the falling orbit which have the same interference phase mode and are not influenced by the radar observation direction, utilizes the distance relation between the phase difference between a plurality of satellite interference radar image pairs and the orbit, combines a weighted least square method, utilizes probability density distribution functions of different coherence phases to calculate the variance of the satellite interference radar image pairs, and then uses the inverse matrix of the variance matrix as a weighted matrix, thereby determining the horizontal motion component and the vertical motion component of the earth surface deformation. The method well fuses multi-mode satellite-borne radar interferograms based on multi-beam or lifting rails, effectively solves the problem of space-time incoherent, not only improves the precision of the satellite interference radar for observing and obtaining the three-dimensional deformation of the earth surface, but also eliminates the interference of system errors on the earth surface deformation observed by the satellite interference radar, and can be applied to real-time dynamic and macroscopic large-scale monitoring of the three-dimensional deformation of the earth surface such as ground settlement, landslide and the like.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art should be considered to be within the technical scope of the present invention, and the technical solutions and the inventive concepts thereof according to the present invention should be equivalent or changed within the scope of the present invention.
Claims (7)
1. A new method for eliminating the earth surface deformation direction ambiguity of a satellite interference radar is characterized by comprising the following steps:
s1: collecting radar observation data at different moments and track pitch angle and azimuth angle data of two groups of tracks;
s2, forming a space-time interference structure according to the radar observation data at different moments, synthesizing a Doppler function by utilizing the estimation of the pitch angle and the azimuth angle of the two tracks to obtain the optimal interference correlation, and calculating the difference between the two tracks to obtain a phase difference to estimate the surface deformation quantity;
s3: and eliminating residual stripes of the system by performing least square matching on the ground true value and the phase gradient of the model.
S4: according to the satellite interference radar images of the ascending orbit and the descending orbit, the distance relation between the phase difference and the orbit between interference radar image pairs is utilized, the weighted least square method is combined, the probability density distribution function of different coherence phases is utilized to calculate the variance and construct a variance matrix;
s5: and calculating a horizontal motion component and a vertical motion component of the earth surface deformation by using the inverse matrix of the variance matrix as a weighting matrix so as to eliminate the earth surface deformation influence of the satellite interference radar.
2. The method as claimed in claim 1, wherein the calculation formula of the phase difference obtained by differentiating the two orbits in step S2 is as follows
Where λ is the carrier wavelength, Δ RdIs the amount of surface deformation, B1Is a base line, θ1For radar angle of incidence, α1Is an angle of inclination.
Is caused by topographic effects, and the influence of the topographic terms should be removed only when considering the deformation.
3. The method of claim 1, wherein the step S3 of removing the residual fringes of the system comprises generating a reference interferogram, estimating coefficients in the phase gradient by a least square method using the true terrestrial phase gradient samples of the flat region, so as to remove the residual fringes of the system, wherein the reference interferogram is represented as a second-order polynomial function of the slant range r and the azimuth time:
with the true ground of the flat region, the phase gradient samples in the r and eta directions are selected, coefficient a1，a2，a3，a4The estimation can be performed by a least squares method.
Wherein n is the selected reference sample number; min is the minimization operation.
4. The new method for eliminating the ambiguity of the earth surface deformation direction of the satellite interference radar according to claim 1, wherein the calculation formula of the phase difference Φ between the n interference SAR image pairs in the step σ 4 is as follows
Φ＝4πδr/Λ
Wherein phi is [ psi1，ψ2，ψ3…ψn]T，δr/Λ＝[δr1/λ1，δr2/λ2，δr3/λ3，..δrn/λn]T，λ1，λ2，λ3，...λnThe carrier wavelengths of the 1 st, 2 nd, 3 rd, … … th, n-th satellite interferometric radar pairs are indicated.
5. The new method for eliminating the ambiguity of the earth surface deformation direction of the satellite interference radar as claimed in claim 1, wherein the phase difference Φ is subjected to phase unwrapping to invert the slope distance δ r. Amount of deformation (dx)2+dy2+dz2)1/2The relationship with the skew distance delta r is
Ax＝δr
Wherein
And is
Wherein theta is1，θ2，...θnIs the angle of incidence of the 1 st, 2 nd, 3 rd, … … th, n-th interference image pair; beta is a1，β2，...βnIs the tracking angle of the 1 st, 2 nd, 3 rd, … … th, n image pairs (clockwise from north); dx, dy, dz can be east-west, north-south and vertical directions respectivelyThree unknown displacement components.
To estimate the unknown displacement x, | Ax- δ r non-calculation from n interference pairs2To obtain a weighted least squares solution, to use a weighted least squares method, i.e., a solution where WAx is W δ r, where W is a weighting matrix,
wherein C ═ WTW, the weight of each pair of interferograms may be determined by the quality of the interferograms in terms of coherence, baseline, etc.
6. The method of claim 1, wherein the variance is calculated in step S5 according to the theoretic expression of probability density distribution function of different coherence phases, and the inverse matrix of the variance matrix is used as the weighting matrix to eliminate ambiguity in three-dimensional direction at the slant angle. The variance is calculated as follows:
wherein sigma2＝∫ψ2pψ(ψ)dψ；pψ(ψ): an interferometric phase probability density function.
7. The new method for eliminating the ambiguity of the earth surface deformation direction of the satellite interference radar as claimed in claim 1, wherein the calculation formula of the horizontal motion component and the vertical motion component of the earth surface deformation in the step S5 is as follows:
wherein the content of the first and second substances,
three unknown displacement components in the east-west, north-south and vertical directions. Component of deformation, C ═ WTW, W is a weighting matrix, δ r is the distance between the tracks, Ax ═ δ r.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110436113.6A CN113219414B (en) | 2021-04-22 | 2021-04-22 | Novel method for eliminating satellite interference radar surface deformation direction blurring |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110436113.6A CN113219414B (en) | 2021-04-22 | 2021-04-22 | Novel method for eliminating satellite interference radar surface deformation direction blurring |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113219414A true CN113219414A (en) | 2021-08-06 |
| CN113219414B CN113219414B (en) | 2024-04-02 |
Family
ID=77088620
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110436113.6A Active CN113219414B (en) | 2021-04-22 | 2021-04-22 | Novel method for eliminating satellite interference radar surface deformation direction blurring |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113219414B (en) |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110058236A (en) * | 2019-05-21 | 2019-07-26 | 中南大学 | It is a kind of towards three-dimensional Ground Deformation estimation InSAR and GNSS determine Quan Fangfa |
| CN111458709A (en) * | 2020-06-08 | 2020-07-28 | 河南大学 | Satellite-borne radar wide-area earth surface two-dimensional deformation field monitoring method and device |
-
2021
- 2021-04-22 CN CN202110436113.6A patent/CN113219414B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110058236A (en) * | 2019-05-21 | 2019-07-26 | 中南大学 | It is a kind of towards three-dimensional Ground Deformation estimation InSAR and GNSS determine Quan Fangfa |
| US20210011149A1 (en) * | 2019-05-21 | 2021-01-14 | Central South University | InSAR and GNSS weighting method for three-dimensional surface deformation estimation |
| CN111458709A (en) * | 2020-06-08 | 2020-07-28 | 河南大学 | Satellite-borne radar wide-area earth surface two-dimensional deformation field monitoring method and device |
Non-Patent Citations (2)
| Title |
|---|
| JIUU-YEE YEN 等: "Evaluation of earthquake potential and surface deformation by Differential Interferometry", 《REMOTE SENSING OF ENVIRONMENT》, pages 782 - 795 * |
| 王霞迎 等: "地表形变时间序列InSAR监测法综述", 《地球物理学进展》, vol. 33, no. 4, pages 1430 - 1437 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113219414B (en) | 2024-04-02 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Kimura et al. | Detection of landslide areas using satellite radar interferometry | |
| Catalão et al. | Merging GPS and atmospherically corrected InSAR data to map 3-D terrain displacement velocity | |
| Murakami et al. | Coseismic crustal deformations of 1994 Northridge, California, earthquake detected by interferometric JERS 1 synthetic aperture radar | |
| CN111474544A (en) | Landslide deformation monitoring and early warning method based on SAR data | |
| Kenyi et al. | Estimation of rock glacier surface deformation using SAR interferometry data | |
| CN106526590A (en) | Method for monitoring and resolving three-dimensional ground surface deformation of industrial and mining area by means of multi-source SAR image | |
| Sumantyo et al. | Long-term consecutive DInSAR for volume change estimation of land deformation | |
| Tang et al. | Atmospheric correction in time-series SAR interferometry for land surface deformation mapping–A case study of Taiyuan, China | |
| CN113238228B (en) | Three-dimensional earth surface deformation obtaining method, system and device based on level constraint | |
| CN113219414B (en) | Novel method for eliminating satellite interference radar surface deformation direction blurring | |
| Artese et al. | Monitoring of land subsidence in Ravenna municipality using integrated SAR-GPS techniques: Description and first results | |
| Pawluszek-Filipiak et al. | Comparison of PSI and DInSAR approach for the subsidence monitoring caused by coal mining exploitation | |
| Wieczorek | EVALUATION OF DEFORMATIONS IN THE URBAN AREA OF OLSZTYN USING SENTINEL-1 SAR INTERFEROMETRY. | |
| Atanasova et al. | Application of interferometry in landslide area analysis | |
| Pérez-Falls et al. | Land subsidence in Villahermosa Tabasco Mexico, using radar interferometry | |
| Vöge et al. | Monitoring dams and reservoir slopes with interferometric SAR | |
| Sedighi et al. | Subsidence Detection Using InSAR and Geodetic Measurements in the North-West of Iran | |
| Wang et al. | Deformation monitoring and evaluation of mountain slope stability combined with ground-based radar and spaceborne InSAR methods | |
| Catalao et al. | Mapping vertical land movement in Singapore using InSAR GPS | |
| Sharov et al. | Survey of glacial dynamics in Novaya Zemlya using satellite radar interferometry | |
| Nandika et al. | Vertical land motion and inundation processes based on the integration of remotely sensed data and IPCC AR5 scenarios in coastal Semarang, Indonesia | |
| Xie et al. | Landslide evolution assessment based on sequential InSAR methods in the Kunming transmission line corridor | |
| Lu et al. | Digital elevation model generation from satellite interferometric synthetic aperture radar | |
| Wdowinski et al. | Wetland InSAR | |
| Fornaro et al. | Potentialities of the use of spaceborne radar systems in the monitoring of structures and infrastructures |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |