CN112379377A - Distributed InSAR satellite long strip surveying and mapping optimization SAR task planning method and system - Google Patents
Distributed InSAR satellite long strip surveying and mapping optimization SAR task planning method and system 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
- G01S13/88—Radar or analogous systems specially adapted for specific applications
- G01S13/89—Radar or analogous systems specially adapted for specific applications for mapping or imaging
- G01S13/90—Radar or analogous systems specially adapted for specific applications for mapping or imaging using synthetic aperture techniques, e.g. synthetic aperture radar [SAR] techniques
- G01S13/9021—SAR image post-processing techniques
- G01S13/9023—SAR image post-processing techniques combined with interferometric techniques
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- 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
- G01S13/88—Radar or analogous systems specially adapted for specific applications
- G01S13/89—Radar or analogous systems specially adapted for specific applications for mapping or imaging
- G01S13/90—Radar or analogous systems specially adapted for specific applications for mapping or imaging using synthetic aperture techniques, e.g. synthetic aperture radar [SAR] techniques
- G01S13/904—SAR modes
- G01S13/9041—Squint mode
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Abstract
The invention provides a distributed InSAR satellite long strip mapping optimization SAR task planning method and a system, comprising the following steps: step 1: performing task planning of two continuous regression cycles for the same region according to the satellite mapping task; step 2: the following is done for two rails spaced one full regression cycle apart: first rail G1: the satellite single imaging time is t1 seconds; second rail G2: the satellite single imaging time is t2 seconds; and step 3: splitting the tasks of G1 and G2 according to the maximum imaging times N of a single track of the system; and 4, step 4: and (3) splicing the ground images, namely splicing the imaging data for many times according to the front and back sequence to form a long strip surveying and mapping product. The method can be used for task planning of optimizing SAR working parameters based on the distributed InSAR satellite in a long-strip working mode, and solves the problems of sampling window deviation, system performance reduction and the like caused by SAR long-strip working.
Description
Technical Field
The invention relates to the technical field of aerospace systems, in particular to a distributed InSAR satellite strip surveying and mapping optimization SAR task planning method and system.
Background
Interferometric synthetic aperture radar (InSAR) is an important remote sensing means for obtaining high-precision ground elevation models (DSMs). The method comprises the steps of observing the same area at different viewing angles by using two SAR antennas distributed along a vertical course, carrying out interference processing on two acquired complex SAR images, solving the slope distance difference between the phase center of a main radar antenna and a secondary radar antenna and a target, and further obtaining a DSM (digital surface model) of an observation area. The distributed satellite InSAR system installs two SAR on two flying satellites in formation and simultaneously observes the earth, can overcome the problems of time decoherence and low baseline precision and the like of repeated navigation of the InSAR, and can obtain high-precision DSM.
Distributed InSAR satellites generally have the following characteristics:
(1) the strict regression orbit (or quasi-strict regression orbit) is adopted, the satellite subsatellite point trajectories are basically overlapped at intervals of the whole regression period, the design is favorable for developing global surveying and mapping task planning, and the execution of the satellite mission task is more efficient and stable;
(2) the SAR satellite is limited by requirements of energy, thermal control, reliability and the like, and cannot continuously work for a long time when in orbit operation, and in order to efficiently obtain geographic information of a global target area, a surveying and mapping satellite ground system generally uses enough satellite observable time during task planning as much as possible;
(3) at least 20s of preparation time is needed between two adjacent imaging of SAR loads to complete the execution of functions such as wave bit code conversion, internal calibration, inter-satellite synchronization and the like;
(4) the method is limited by the synchronous state kept by the double satellites, and the working parameters cannot be switched simultaneously to adapt to the change of the SAR slope distance when the double-satellite SAR load is imaged in orbit;
(5) ground application systems have a strong demand for long strip surveying and mapping.
The SAR slope distance change of the distributed InSAR satellite is obvious due to terrain fluctuation and satellite height change in a long strip working mode, and the longer the single imaging time is, the more obvious the SAR slope distance change is. The method is limited by a two-satellite synchronous state, and the working parameters are difficult to switch simultaneously when the two-satellite SAR load runs in an orbit so as to adapt to the change of the SAR slope distance, thereby causing the problems of sampling gate offset, observation area offset, system performance reduction and the like. The SAR slant range change speed can be effectively controlled by shortening the single imaging time, so that the satellite system keeps high-performance operation, but the satellite surveying and mapping efficiency and the mission planning are seriously influenced. Therefore, how to realize the task planning of the distributed InSAR satellite in the long-strip working mode becomes one of the important works of the distributed InSAR satellite system design.
With the rapid development of the satellite-borne InSAR technology, the requirement on the mapping efficiency of the distributed InSAR satellite is higher and higher, so how to promote the strip mapping and the task planning becomes a direction in which important research needs to be carried out urgently.
Patent document CN102479085 discloses an "agile satellite mission planning method", which is different from the present invention in that: the method mainly solves the problems that a task planning method for optimizing SAR working parameters by a distributed InSAR satellite ' strip surveying and mapping task ' meets the requirement for efficient global coverage, and the method mainly solves the problems that an agile satellite ' and an observation task planning method do not meet the requirement for efficient global coverage, and has obvious differences in application direction, application range and technical approaches.
Patent document CN109002966 discloses "a multi-star mission planning method based on K-means clustering", which is different from the present invention in that: the patent mainly solves the problem that a task planning method for optimizing SAR working parameters of a distributed InSAR satellite strip surveying and mapping task has requirements on load types and global coverage, mainly solves the problem that a simple task planning method only considers energy and orbit based on K-means clustering multi-satellite is not specially considered for load types, global coverage and task planning fineness, is not suitable for surveying and mapping task planning of the distributed InSAR satellite, and has obvious differences in application direction, application range and technical approach.
A satellite imaging mission planning algorithm to minimize the time to complete the survey, space control, 201604. The main differences are: first, the patent improves the working performance of the satellite, and the article focuses on improving the performance of the satellite, but does not improve the performance of the satellite; the second patent is applicable to the conventional mapping task planning of the satellite in the 'full life cycle', and the paper mainly demonstrates the imaging observation task under the 'emergency' condition, and takes the minimized time for completing the mapping task as the optimization target; the two methods have obvious differences in application direction, application range and technical approach.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide a distributed InSAR satellite long strip mapping optimization SAR task planning method and system.
According to one aspect of the invention, a distributed InSAR satellite strip mapping optimization SAR task planning method is provided, which comprises the following steps:
step 1: performing task planning of two continuous regression cycles for the same region according to the satellite mapping task;
step 2: the following is done for two rails spaced one full regression cycle apart:
first rail G1: the satellite single imaging time is t1 seconds;
second rail G2: the satellite single imaging time is t2 seconds;
and step 3: splitting the tasks of G1 and G2 according to the maximum imaging times N of a single track of the system:
the first orbit G1 'is characterized in that in a G1 planning range, the imaging time of the satellite is N times of imaging, each time is t1/N +0.5 second, the adjacent imaging time interval is t1/N second, in a G2 planning range, the imaging time of the satellite is N times of imaging, each time is t2/N +0.5 second, the adjacent imaging time interval is t2/N second, the second orbit G2' is in a G1 planning range, the imaging time of the satellite is N times of imaging, each time is t1/N +0.5 second, the adjacent imaging time interval is t1/N second, in a G2 planning range, the imaging time of the satellite is N times of imaging, each time is t2/N +0.5 second, and the adjacent imaging time interval is t2/N second;
and 4, step 4: and (3) splicing the ground images, namely splicing the imaging data for many times according to the front and back sequence to form a long strip surveying and mapping product.
Preferably, the SAR slope distance change is obvious due to terrain fluctuation and satellite height change of the SAR satellite in a long strip working mode, the center slope distance of the satellite-borne SAR in a flat area is set to be Rs1, the center slope distance of the satellite-borne SAR in a terrain fluctuation area is set to be Rs2, the imaging parameters of the satellite-borne SAR satellite are calculated according to the forecast flat target slope distance Rs1, a task instruction packet is compiled, the task period is influenced by the satellite orbit height and the terrain fluctuation change, the target slope distance Rs2 in an actual working state is continuously changed, the actual observation position of the SAR is deviated, and the problems of sampling gate offset, observation area deviation and system performance reduction are caused under the actual slope distance Rs2 due to the fact that the imaging parameters in the SAR instruction packet are calculated according to the slope distance Rs 1.
Preferably, the sun synchronous orbit satellite under the orbit height of 500km is calculated, SAR adopts an incidence angle theta of 36 degrees, the orbit height and the ground object elevation change within 5 minutes of work is delta H of 5km, and the slope distance change is carried out
ΔRs＝ΔH/cos(θ)＝12.36km
Corresponding ground observation position error will reach
ΔW＝ΔRs×sin(θ)＝3.64km
By combining the current domestic engineering practice situation, the sensitivity reduction of the SAR image edge system caused by the position deviation amount reaches 0.5-1 dB.
Preferably, due to the limitation of the double-satellite inter-satellite load synchronization requirement of the distributed InSAR satellite, the SAR working parameters cannot be switched in the same load task process, so that the influence of the slant distance difference between the Rs2 and the Rs1 on the satellite product quality is further aggravated by long-strip surveying and mapping, and the problems of sampling gate bias, observation area bias and system performance degradation are aggravated.
Preferably, the single imaging time is shortened to effectively control the SAR slope distance change speed so as to keep the satellite system in high-performance operation, similarly taking a sun synchronous orbit satellite at the orbit height of 500km as an example, the SAR adopts an incidence angle of theta of 36 degrees, and if the orbit height and the ground object elevation change of 30s are changed into delta H of 500m, the slope distance change is carried out
ΔRs＝ΔH/cos(θ)＝1.236km
Corresponding ground observation position error will reach
ΔW＝ΔRs×sin(θ)＝364m
And the sensitivity reduction of the SAR image edge system caused by the position deviation amount can be controlled within an acceptable range by combining the current domestic engineering practice situation.
Preferably, the SAR range change speed can be effectively controlled by shortening the single imaging time, but at the cost of severely impacting satellite mapping efficiency and mission planning.
Preferably, the distributed InSAR satellite generally takes large-area target mapping as a mission task, if the single imaging time is short, a fragmented mapping product can be generated, the late-stage splicing and the mapping efficiency of quickly acquiring the target full-area mapping product are influenced, and the contradiction between the satellite mapping performance and the satellite mapping efficiency can be effectively solved by designing a short-time imaging task planning strategy and innovating a ground image splicing method.
Preferably, the task planning of two continuous regression periods is considered in a comprehensive mode by adjusting the satellite use strategy, so that two-rail data separated by one whole regression period are respectively inserted and completed in two rails of the two regression periods, the single imaging time can be effectively reduced by sacrificing a small amount of mapping time, the satellite system can keep high-performance operation, and the satellite mapping efficiency and the task planning can be guaranteed.
Preferably, through strategy adjustment of short-time imaging mapping task planning, target area mapping products which are crossed from front to back for the first time to the Nth time are obtained, enough image overlapping parts are reserved between adjacent mapping products and used for splicing front and back images, manual splicing is carried out on the target area mapping products which are crossed from front to back for multiple times according to the geographical position sequence, and finally long-strip mapping products are obtained.
According to another aspect of the invention, a distributed InSAR satellite strip mapping optimization SAR task planning system is provided, which comprises:
module M1: performing task planning of two continuous regression cycles for the same region according to the satellite mapping task;
module M2: the following is done for two rails spaced one full regression cycle apart:
first rail G1: the satellite single imaging time is t1 seconds;
second rail G2: the satellite single imaging time is t2 seconds;
module M3: splitting the tasks of G1 and G2 according to the maximum imaging times N of a single track of the system:
the first orbit G1 'is characterized in that in a G1 planning range, the imaging time of the satellite is N times of imaging, each time is t1/N +0.5 second, the adjacent imaging time interval is t1/N second, in a G2 planning range, the imaging time of the satellite is N times of imaging, each time is t2/N +0.5 second, the adjacent imaging time interval is t2/N second, the second orbit G2' is in a G1 planning range, the imaging time of the satellite is N times of imaging, each time is t1/N +0.5 second, the adjacent imaging time interval is t1/N second, in a G2 planning range, the imaging time of the satellite is N times of imaging, each time is t2/N +0.5 second, and the adjacent imaging time interval is t2/N second;
module M4: and (3) splicing the ground images, namely splicing the imaging data for many times according to the front and back sequence to form a long strip surveying and mapping product.
Compared with the prior art, the invention has the following beneficial effects:
1. the method can be used for task planning of optimizing SAR working parameters based on the distributed InSAR satellite in a long-strip working mode, and solves the problems of sampling window deviation, system performance reduction and the like caused by SAR long-strip working.
2. According to the invention, through adjusting the satellite use strategy and comprehensively considering the task planning of two continuous regression periods, two-orbit data separated by one whole regression period are respectively and alternately finished in two orbits of the two regression periods, and the single imaging time can be effectively reduced by sacrificing a small amount of mapping time (as shown in figure 1, 2N seconds are lost), so that the satellite system keeps high-performance operation, and the satellite mapping efficiency and the task planning can also be ensured.
Drawings
Other features, objects and advantages of the invention will become more apparent upon reading of the detailed description of non-limiting embodiments with reference to the following drawings:
FIG. 1 is a processing step of a distributed InSAR satellite strip mapping optimization SAR task planning method of the present invention;
FIG. 2 is a schematic diagram of imaging of a satellite-borne SAR flat area;
FIG. 3 is a schematic diagram of imaging of a satellite-borne SAR imaging topographic relief area;
FIG. 4 is a comparison diagram of imaging actual positions of a satellite-borne SAR flat area and a terrain undulating area;
FIG. 5 is a schematic diagram of a prior art method mission planning;
fig. 6 is a schematic diagram of task planning in accordance with the present invention.
Detailed Description
The present invention will be described in detail with reference to specific examples. The following examples will assist those skilled in the art in further understanding the invention, but are not intended to limit the invention in any way. It should be noted that it would be obvious to those skilled in the art that various changes and modifications can be made without departing from the spirit of the invention. All falling within the scope of the present invention.
In this embodiment, the processing steps of the distributed InSAR satellite strip mapping optimization SAR task planning method are as shown in fig. 1, and the SAR slant range of the SAR satellite changes obviously due to the terrain fluctuation and the satellite height change in the strip operating mode of the SAR satellite, which is detailed in fig. 2, 3, and 4. FIG. 2 is a schematic diagram of imaging of a satellite-borne SAR in a flat area, with a center slant distance of Rs 1; FIG. 3 is a schematic diagram of imaging of a satellite-borne SAR in a topographic relief area, wherein the center slant range is Rs 2; fig. 4 shows a comparison graph of the imaging actual positions of the satellite-borne SAR in a flat area and a topographic relief area.
The imaging parameters of the satellite-borne SAR satellite are calculated according to the forecast flat target slope distance Rs1, a task instruction packet is compiled, the task period is influenced by the satellite orbit height and the topographic fluctuation change, the target slope distance Rs2 in the actual working state is continuously changed, the offset of the actual observation position of the SAR is caused, and the problems of sampling gate offset, observation area offset, system performance reduction and the like are caused under the actual slope distance Rs2 due to the fact that the imaging parameters in the SAR instruction packet are calculated according to the slope distance Rs 1.
Calculating a sun synchronous orbit satellite under the height of 500km of orbit, adopting an incidence angle theta of 36 degrees for SAR, changing the height of the orbit and the height of the ground object into delta H of 5km in 5 minutes of work, and changing the slope distance
ΔRs＝ΔH/cos(θ)＝12.36km
Corresponding ground observation position error will reach
ΔW＝ΔRs×sin(θ)＝3.64km
By combining the current domestic engineering practice situation, the sensitivity reduction of the SAR image edge system caused by the position deviation amount reaches 0.5-1 dB.
In addition, due to the limitation of the load synchronization requirement between double stars of the distributed InSAR satellite, the SAR working parameters cannot be switched in the same load task process, so that the influence of the slant distance difference between the Rs2 and the Rs1 on the satellite product quality is further aggravated by long-strip surveying and mapping, and the problems of sampling gate bias, observation area deviation, system performance reduction and the like are aggravated.
Therefore, for distributed InSAR satellites, it is not feasible to avoid bias in the geostationary position of a bistatic SAR during a single imaging task by switching SAR operating parameters.
The SAR slant range change speed can be effectively controlled by shortening the single imaging time, so that the satellite system can keep high-performance operation.
Similarly, taking a sun synchronous orbit satellite at 500km orbit altitude as an example, the SAR adopts an incident angle theta of 36 degrees, and if the orbit altitude and the ground object elevation change within 30s of work is Δ H of 500m, the slope distance change is
ΔRs＝ΔH/cos(θ)＝1.236km
Corresponding ground observation position error will reach
ΔW＝ΔRs×sin(θ)＝364m
And the sensitivity reduction of the SAR image edge system caused by the position deviation amount can be controlled within an acceptable range by combining the current domestic engineering practice situation.
The SAR slant range change speed can be effectively controlled by shortening the single imaging time, but the satellite mapping efficiency and the mission planning are seriously influenced at the cost.
The distributed InSAR satellite usually takes large-area target surveying and mapping as a mission task, if the single imaging time is short, a fragmented surveying and mapping product can be generated, the later-stage splicing and the surveying and mapping efficiency of the target whole-area surveying and mapping product can be influenced, and the contradiction between the satellite surveying and mapping performance and the satellite surveying and mapping efficiency can be effectively solved by designing a short-time imaging task planning strategy and innovating a ground image splicing method.
Fig. 5 is a schematic diagram of task planning in the prior art, and the task planning of two continuous regression periods is considered in an overall manner by adjusting the satellite use strategy, so that two-rail data separated by one whole regression period are respectively inserted and completed in two rails of the two regression periods, as shown in fig. 6, the single imaging time can be effectively reduced by sacrificing a small amount of mapping time (2N seconds are lost for splicing front and back images as shown in fig. 1), thereby the satellite system can keep high-performance operation, and the satellite mapping efficiency and the task planning can be ensured.
Through the strategy adjustment of short-time imaging mapping task planning, as shown in fig. 6, the target area mapping products which are crossed from beginning to end for the first time to the nth time can be obtained, enough image overlapping parts are reserved between the adjacent mapping products, the method can be used for splicing images from beginning to end, the target area mapping products which are crossed from beginning to end for multiple times are spliced manually according to the sequence of geographic positions, and finally long-strip mapping products are obtained, so that through short-time imaging mapping and task planning strategy adjustment, the problem of ground observation position deviation caused by the fact that SAR imaging parameters of a distributed InSAR satellite cannot be switched through a single task is effectively solved, the system performance is improved, and the efficient mapping capability of a satellite system is kept.
Those skilled in the art will appreciate that, in addition to implementing the system and its various devices, modules, units provided by the present invention as pure computer readable program code, the system and its various devices, modules, units provided by the present invention can be fully implemented by logically programming method steps in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers and the like. Therefore, the system and various devices, modules and units thereof provided by the invention can be regarded as a hardware component, and the devices, modules and units included in the system for realizing various functions can also be regarded as structures in the hardware component; means, modules, units for performing the various functions may also be regarded as structures within both software modules and hardware components for performing the method.
The foregoing description of specific embodiments of the present invention has been presented. It is to be understood that the present invention is not limited to the specific embodiments described above, and that various changes or modifications may be made by one skilled in the art within the scope of the appended claims without departing from the spirit of the invention. The embodiments and features of the embodiments of the present application may be combined with each other arbitrarily without conflict.
Claims (10)
1. A distributed InSAR satellite strip mapping optimization SAR task planning method is characterized by comprising the following steps:
step 1: performing task planning of two continuous regression cycles for the same region according to the satellite mapping task;
step 2: the following is done for two rails spaced one full regression cycle apart:
first rail G1: the satellite single imaging time is t1 seconds;
second rail G2: the satellite single imaging time is t2 seconds;
and step 3: splitting the tasks of G1 and G2 according to the maximum imaging times N of a single track of the system:
the first orbit G1 'is characterized in that in a G1 planning range, the imaging time of the satellite is N times of imaging, each time is t1/N +0.5 second, the adjacent imaging time interval is t1/N second, in a G2 planning range, the imaging time of the satellite is N times of imaging, each time is t2/N +0.5 second, the adjacent imaging time interval is t2/N second, the second orbit G2' is in a G1 planning range, the imaging time of the satellite is N times of imaging, each time is t1/N +0.5 second, the adjacent imaging time interval is t1/N second, in a G2 planning range, the imaging time of the satellite is N times of imaging, each time is t2/N +0.5 second, and the adjacent imaging time interval is t2/N second;
and 4, step 4: and (3) splicing the ground images, namely splicing the imaging data for many times according to the front and back sequence to form a long strip surveying and mapping product.
2. The distributed InSAR satellite strip surveying and mapping optimization SAR task planning method according to claim 1, characterized in that the SAR slope distance changes obviously due to terrain fluctuation and satellite height change of an SAR satellite in a strip working mode, the center slope distance of a satellite-borne SAR in a flat area is set to be Rs1, the center slope distance of the satellite-borne SAR in a terrain fluctuation area is set to be Rs2, the satellite-borne SAR satellite calculates imaging parameters according to forecast flat target slope distance Rs1, a task instruction packet is compiled, the influence of satellite orbit height and terrain fluctuation change during a task is realized, the target slope distance Rs2 in an actual working state is changed continuously, the deviation of an actual observation position of the SAR is also caused, and the problems of sampling gate bias, observation area deviation and system performance reduction are caused under the actual slope distance Rs2 because the imaging parameters in the SAR instruction packet are calculated according to the slope distance Rs 1.
3. The distributed InSAR satellite strip mapping optimization SAR task planning method according to claim 2, characterized in that the solar synchronous orbit satellite under 500km orbit height is calculated, SAR adopts an incidence angle theta of 36 degrees, the orbit height and ground feature elevation change in 5 minutes of work is delta H of 5km, and the slope distance change
ΔRs＝ΔH/cos(θ)＝12.36km
Corresponding ground observation position error will reach
ΔW＝ΔRs×sin(θ)＝3.64km
By combining the current domestic engineering practice situation, the sensitivity reduction of the SAR image edge system caused by the position deviation amount reaches 0.5-1 dB.
4. The distributed InSAR satellite long-strip mapping optimization SAR task planning method according to claim 3, characterized in that due to limitation of load synchronization requirements between the distributed InSAR satellites and the satellites, SAR working parameters cannot be switched in the same load task process, so that long-strip mapping further aggravates the influence of the Rs2 and Rs1 slant distance difference on satellite product quality, and aggravates the problems of sampling gate bias, observation area bias and system performance degradation.
5. The distributed InSAR satellite strip mapping optimization SAR task planning method according to claim 4, characterized in that the SAR slope distance change speed can be effectively controlled by shortening the single imaging time, so that the satellite system can keep high-performance operation, also taking a sun synchronous orbit satellite at 500km orbit height as an example, the SAR adopts an incidence angle of theta-36 degrees, if the orbit height and the ground object elevation change of 30s are changed into delta H-500 m, the slope distance change is 500m
ΔRs＝ΔH/cos(θ)＝1.236km
Corresponding ground observation position error will reach
ΔW＝ΔRs×sin(θ)＝364m
And the sensitivity reduction of the SAR image edge system caused by the position deviation amount can be controlled within an acceptable range by combining the current domestic engineering practice situation.
6. The distributed InSAR satellite strip mapping optimization SAR task planning method according to claim 5, wherein the SAR slant range change speed can be effectively controlled by shortening the single imaging time, but the cost is that the satellite mapping efficiency and the task planning are seriously affected.
7. The distributed InSAR satellite strip mapping optimization SAR task planning method according to claim 6, characterized in that the distributed InSAR satellite usually takes large-area target mapping as a mission task, if the single imaging time is short, a fragmented mapping product is generated, the mapping efficiency of late-stage splicing and rapid acquisition of the target full-area mapping product is affected, and the contradiction between satellite mapping performance and efficiency can be effectively solved by designing a short-time imaging task planning strategy and an innovative ground image splicing method.
8. The distributed InSAR satellite strip surveying and mapping optimization SAR task planning method according to claim 7, characterized in that task planning of two continuous regression periods is considered in a comprehensive manner by adjusting a satellite use strategy, so that two-orbit data separated by one whole regression period are respectively and alternately completed in two orbits of the two regression periods, and single imaging time can be effectively reduced by sacrificing a small amount of surveying and mapping time, thereby enabling a satellite system to keep high-performance operation, and ensuring satellite surveying and mapping efficiency and task planning.
9. The distributed InSAR satellite long-strip mapping optimization SAR task planning method according to claim 8, characterized in that through strategy adjustment of short-time imaging mapping task planning, target area mapping products which are crossed from front to back for the first time to the Nth time are obtained, enough image overlapping parts are left between adjacent mapping products for front and back image splicing, the target area mapping products which are crossed from front to back for multiple times are spliced manually according to a geographical position sequence, and finally, long-strip mapping products are obtained, so that through short-time imaging mapping and task planning strategy adjustment, the problem of ground observation position deviation caused by the fact that SAR imaging parameters cannot be switched by a single task of a distributed InSAR satellite is effectively solved, system performance is improved, and the mapping capability of a satellite system is maintained.
10. A distributed InSAR satellite strip mapping optimization SAR task planning system is characterized by comprising:
module M1: performing task planning of two continuous regression cycles for the same region according to the satellite mapping task;
module M2: the following is done for two rails spaced one full regression cycle apart:
first rail G1: the satellite single imaging time is t1 seconds;
second rail G2: the satellite single imaging time is t2 seconds;
module M3: splitting the tasks of G1 and G2 according to the maximum imaging times N of a single track of the system:
the first orbit G1 'is characterized in that in a G1 planning range, the imaging time of the satellite is N times of imaging, each time is t1/N +0.5 second, the adjacent imaging time interval is t1/N second, in a G2 planning range, the imaging time of the satellite is N times of imaging, each time is t2/N +0.5 second, the adjacent imaging time interval is t2/N second, the second orbit G2' is in a G1 planning range, the imaging time of the satellite is N times of imaging, each time is t1/N +0.5 second, the adjacent imaging time interval is t1/N second, in a G2 planning range, the imaging time of the satellite is N times of imaging, each time is t2/N +0.5 second, and the adjacent imaging time interval is t2/N second;
module M4: and (3) splicing the ground images, namely splicing the imaging data for many times according to the front and back sequence to form a long strip surveying and mapping product.
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| CN115657034A (en) * | 2022-12-29 | 2023-01-31 | 北京九天微星科技发展有限公司 | Wide swath imaging method and system |
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