CN111478741B - Satellite intelligent data transmission method and system based on remote sensing state estimation - Google Patents
Satellite intelligent data transmission method and system based on remote sensing state estimation Download PDFInfo
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Abstract
The invention provides a satellite intelligent data transmission method and a system based on remote sensing state estimation, which comprises the following steps: estimating the loss of the satellite-ground data transmission link in real time according to uplink power detection and link model estimation; calculating the maximum data transmission capacity of data transmission according to the loss of the satellite-ground data transmission link; identifying an interested remote sensing area through preprocessing target detection and hot spot area designation; adjusting the compression ratio and compression quality of the remote sensing data according to the obtained maximum data transmission capacity of data transmission and the data volume of the remote sensing area of interest; caching the preprocessed target detection data, the original remote sensing data and the compressed remote sensing data, and selecting and storing data information to be downloaded according to the maximum data transmission capacity and the data volume of the remote sensing area of interest; reading data to be downloaded, and adjusting a satellite data transmission link according to the data amount to be downloaded and the transmission link loss; the invention optimizes the code rate, the coding mode, the modulation mode and the transmitting power of the remote sensing data chain and improves the transmission capability of the remote sensing data.
Description
Technical Field
The invention relates to a satellite data transmission system, in particular to a satellite intelligent data transmission method and system based on remote sensing state estimation, which are applied to satellite data transmission design.
Background
The satellite data transmission system is used for transmitting satellite remote sensing data, and the effectiveness of transmission directly influences task operation of a satellite. The traditional data transmission adopts a fixed mode design, the remote sensing data is completely downloaded, and optimal transmission is not carried out aiming at an interested area, so that the data volume needing to be stored and transmitted is large, the storage and transmission resources of a satellite are limited, the working period of the remote sensing load is limited, meanwhile, the data chain adopts a fixed design, intelligent adjustment cannot be carried out aiming at the satellite-ground link state and the remote sensing data volume, and great resource waste exists. In order to improve the effective transmission capability of remote sensing data and fully utilize satellite-ground data transmission link resources, the invention provides a satellite intelligent data transmission method based on remote sensing state estimation, which estimates the loss of a satellite-ground data transmission link in real time and determines the satellite-ground data transmission capability; identifying an interested remote sensing area and adjusting compression parameters; selecting data information to be downloaded according to the data transmission capacity and the data volume of the region of interest; and then automatically adjusting satellite data transmission according to the selected downloaded remote sensing data volume, optimizing the code rate, the coding mode, the modulation mode and the transmitting power of a remote sensing data chain, improving the transmission capability of the remote sensing data and having good ground engineering application value.
The invention relates to a technology for solving the problem of intelligent satellite data transmission based on remote sensing state estimation. The method comprises the steps of retrieving similar patent documents, CN1O3312453A, namely a method for self-adaptive distance data transmission of an aircraft-mounted terminal, obtaining a satellite-ground distance through an inertial navigation system, calculating the satellite-ground distance by depending on the distance to calculate link loss, adjusting data transmission, and not considering the cooperative integrated management of optimization and link transmission of information of an interested area; CN1O7508659A adaptive coding modulation method for data transmission of inter-satellite link for satellite navigation system, which is oriented to inter-satellite transmission, does not consider the cooperative integrated management of region-of-interest information optimization and link transmission, and is different from the intelligent data transmission method for satellite based on remote sensing state estimation; the CN1O3324251A task scheduling optimization method of the satellite-borne data transmission system and the satellite-borne data transmission system is different from the satellite intelligent data transmission method based on remote sensing state estimation, and aims to solve the problems that the existing task scheduling method is low in system working efficiency and limited in data processing scale, and reduce FPGA reconstruction time. At present, no description or report similar to the related technology is found, and similar data at home and abroad is not collected.
Patent document CN105306156A (application number: 201510765749.X) discloses an automated testing system and method for remote sensing satellite data transmission products, comprising: PXI system controller: providing a real-time operating system for the whole PXI platform; PXI module set: the test device is connected with a PXI bus and provides a direct interface with a tested product; PXI case: a stable mechanical structure platform and a reliable power supply and heat dissipation system are provided for the PXI system; testing system software: and the PXI module set is matched with the PXI module set to realize corresponding functions and provide an interactive interface with a user.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide a satellite intelligent data transmission method and system based on remote sensing state estimation.
The invention provides a satellite intelligent data transmission method based on remote sensing state estimation, which comprises the following steps:
step M1: estimating the loss of the satellite-ground data transmission link in real time according to uplink power detection and link model estimation;
step M2: calculating to obtain the maximum data transmission capacity of data transmission according to the satellite-ground data transmission link loss obtained by real-time estimation and by combining the data transmission transmitting power of a satellite and the receiving capacity of a ground receiver;
step M3: identifying an interested remote sensing area through preprocessing target detection and hot spot area designation;
step M4: setting compression parameters according to the obtained maximum data transmission capacity of data transmission and the data volume of the remote sensing area of interest, and adjusting the compression ratio and the compression quality of the remote sensing data;
step M5: caching preprocessed target detection data, original remote sensing data and compressed remote sensing data, selecting and storing data information to be downloaded according to the maximum data transmission capacity of data transmission and the data volume of the remote sensing area of interest, and accordingly obtaining remote sensing data volume estimation to be downloaded;
step M6: reading data to be downloaded, and automatically adjusting a satellite data transmission link according to the remote sensing data amount to be downloaded and the satellite-ground data transmission link loss;
and after the downlink attenuation is obtained, the link model adjusts the link characteristics such as satellite transmitting power, data rate and the like through the downlink signal transmission model.
Preferably, the step M1 includes:
when the satellite uplink link is smooth, the satellite receives the ground uplink radio frequency signal in the same frequency band as the downlink data transmission, the power level of the uplink signal is detected and measured, the ground transmission power and the loss of the satellite receiver are known, the uplink attenuation is obtained, and the downlink data transmission link attenuation is consistent with the uplink attenuation in the same frequency band;
when the satellite uplink link is not communicated, estimating the space and the atmospheric loss including the link according to the orbit information of the satellite, the position information of the ground station and the atmospheric information injected on the ground, thereby obtaining the attenuation estimation of the downlink data transmission link.
Preferably, the step M3 includes: the method comprises the steps of identifying a remote sensing area with a target through on-satellite preprocessing target detection, and identifying an interested remote sensing area by specifying a hot spot area needing downloading or by taking a ground remote sensing specified area as the hot spot area through ground on-ground injection parameter information;
the preprocessing comprises machine learning, image recognition and detection of a target of remote sensing imaging;
the hot spot region comprises a sensitive region and a designated background region.
Preferably, the step M5 includes:
step M5.1: caching original remote sensing data, preprocessed target detection data and remote sensing compressed data in a remote sensing buffer area for selecting, storing and downloading;
step M5.2: selecting corresponding data of the remote sensing buffer area for storage according to the information of the remote sensing area of interest, and selecting and storing preprocessed target detection data and original remote sensing data when the remote sensing area of interest does not reach a preset value and the original remote sensing data accords with a preset downloading condition; when the remote sensing area of interest reaches a preset value and the original data cannot be downloaded, selecting and storing preprocessed target detection data and remote sensing compressed data to obtain selected stored remote sensing data;
step M5.3: and obtaining the remote sensing data quantity estimation to be downloaded according to the selected stored remote sensing data.
Preferably, the step M6 includes: according to the remote sensing data quantity estimation and satellite-ground data transmission link loss to be downloaded, the code rate, the coding mode, the modulation mode and the transmitting power of the remote sensing data link are determined, the selected stored remote sensing data are read, satellite data transmission is automatically adjusted, the transmitting power and the channel utilization rate are optimized, and the remote sensing data transmission capability is improved.
The invention provides a satellite intelligent data transmission system based on remote sensing state estimation, which comprises:
module M1: estimating the loss of the satellite-ground data transmission link in real time according to uplink power detection and link model estimation;
module M2: calculating to obtain the maximum data transmission capacity of data transmission according to the satellite-ground data transmission link loss obtained by real-time estimation and by combining the data transmission transmitting power of a satellite and the receiving capacity of a ground receiver;
module M3: identifying an interested remote sensing area through preprocessing target detection and hot spot area designation;
module M4: setting compression parameters according to the obtained maximum data transmission capacity of data transmission and the data volume of the remote sensing area of interest, and adjusting the compression ratio and the compression quality of the remote sensing data;
module M5: caching preprocessed target detection data, original remote sensing data and compressed remote sensing data, selecting and storing data information to be downloaded according to the maximum data transmission capacity of data transmission and the data volume of the remote sensing area of interest, and accordingly obtaining remote sensing data volume estimation to be downloaded;
module M6: reading data to be downloaded, and automatically adjusting a satellite data transmission link according to the remote sensing data amount to be downloaded and the satellite-ground data transmission link loss;
and after the downlink attenuation is obtained, the link model adjusts the link characteristics such as satellite transmitting power, data rate and the like through the downlink signal transmission model.
Preferably, said module M1 comprises:
when the satellite uplink link is smooth, the satellite receives the ground uplink radio frequency signal in the same frequency band as the downlink data transmission, the power level of the uplink signal is detected and measured, the ground transmission power and the loss of the satellite receiver are known, the uplink attenuation is obtained, and the downlink data transmission link attenuation is consistent with the uplink attenuation in the same frequency band;
when the satellite uplink link is not communicated, estimating the space and the atmospheric loss including the link according to the orbit information of the satellite, the position information of the ground station and the atmospheric information injected on the ground, thereby obtaining the attenuation estimation of the downlink data transmission link.
Preferably, said module M3 comprises: the method comprises the steps of identifying a remote sensing area with a target through on-satellite preprocessing target detection, and identifying an interested remote sensing area by specifying a hot spot area needing downloading or by taking a ground remote sensing specified area as the hot spot area through ground on-ground injection parameter information;
the preprocessing comprises machine learning, image recognition and detection of a target of remote sensing imaging;
the hot spot region comprises a sensitive region and a designated background region.
Preferably, said module M5 comprises:
module M5.1: caching original remote sensing data, preprocessed target detection data and remote sensing compressed data in a remote sensing buffer area for selecting, storing and downloading;
module M5.2: selecting corresponding data of the remote sensing buffer area for storage according to the information of the remote sensing area of interest, and selecting and storing preprocessed target detection data and original remote sensing data when the remote sensing area of interest does not reach a preset value and the original remote sensing data accords with a preset downloading condition; when the remote sensing area of interest reaches a preset value and the original data cannot be downloaded, selecting and storing preprocessed target detection data and remote sensing compressed data to obtain selected stored remote sensing data;
module M5.3: and obtaining the remote sensing data quantity estimation to be downloaded according to the selected stored remote sensing data.
Preferably, said module M6 comprises: according to the remote sensing data quantity estimation and satellite-ground data transmission link loss to be downloaded, the code rate, the coding mode, the modulation mode and the transmitting power of the remote sensing data link are determined, the selected stored remote sensing data are read, satellite data transmission is automatically adjusted, the transmitting power and the channel utilization rate are optimized, and the remote sensing data transmission capability is improved.
Compared with the prior art, the invention has the following beneficial effects:
1. the invention provides a satellite intelligent data transmission method based on remote sensing state estimation, which is based on region-of-interest detection and identification, optimizes necessary remote sensing download information, senses the satellite-ground link state in real time based on uplink detection, automatically adjusts the coding, modulation and power of downlink data transmission by combining the data volume to be downloaded, improves the quality and efficiency of satellite-ground data transmission and has good engineering application value;
2. the code rate, the coding mode, the modulation mode and the transmitting power of the remote sensing data chain are optimized, and the transmission capability of the remote sensing data is improved.
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 diagram illustrating an intelligent satellite data transmission method based on remote sensing state estimation according to the present invention;
FIG. 2 is a flow chart of a satellite intelligent data transmission method based on remote sensing state estimation;
FIG. 3 is a schematic diagram of a satellite-ground distance calculation;
FIG. 4 is a rain, cloud, fog induced attenuation curve;
FIG. 5 is an atmospheric absorption loss curve;
fig. 6 is a schematic diagram of antenna pointing deviation.
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.
The invention provides a satellite intelligent data transmission method based on remote sensing state estimation, which comprises the following steps: as shown in the figures 1-2 of the drawings,
step M1: estimating satellite-ground data transmission link loss in real time and satellite-ground channel data transmission capacity according to uplink power detection and link model estimation;
step M2: calculating to obtain the maximum data transmission capacity of data transmission according to the satellite-ground data transmission link loss obtained by real-time estimation and by combining the data transmission transmitting power of a satellite and the receiving capacity of a ground receiver, and taking the maximum data transmission capacity as a consideration factor of the selection decision of the remote sensing data;
step M3: identifying an interested remote sensing area through preprocessing target detection and hot spot area designation;
step M4: according to the obtained maximum data transmission capacity of data transmission and the data volume of the remote sensing area of interest, whether compressed data needs to be transmitted or not is evaluated, compression parameters are set, and the compression ratio and the compression quality of the remote sensing data are adjusted, so that the compressed data can be transmitted to the ground, and better compression quality can be considered.
Step M5: caching preprocessed target detection data, original remote sensing data and compressed remote sensing data, selecting and storing data information to be downloaded according to the maximum data transmission capacity of data transmission and the data volume of the remote sensing area of interest, and accordingly obtaining remote sensing data volume estimation to be downloaded;
step M6: reading data to be downloaded, and automatically adjusting a satellite data transmission link according to the remote sensing data amount to be downloaded and the satellite-ground data transmission link loss;
specifically, the step M1 includes:
when the satellite uplink link is smooth, the satellite receives the ground uplink radio frequency signal in the same frequency band as the downlink data transmission, the power level of the uplink signal is detected and measured, the ground transmission power and the loss of the satellite receiver are known, the uplink attenuation is obtained, and the downlink data transmission link attenuation is basically consistent with the uplink attenuation in the same frequency band;
in addition, because electromagnetic waves pass through different space environments such as an ionosphere, a troposphere and the like in the signal transmission process, the ionosphere flickers in the ionosphere, and rainfall attenuation, atmospheric absorption, scattering and absorption of cloud mist, snowfall and the like, and atmospheric refraction, sunscals and the like in the troposphere cause additional loss [ L ] of space propagation. The logarithmic expression for the transmission loss [ L ] is:
[L]＝[Lf]+[Lr]+[La]+[Lrp]+[Lp] (1)
wherein: [ L ]f]Represents the free space transmission loss in logarithmic values in decibels (dB); [ L ]r]Represents the rainfall loss in logarithmic values in decibels (dB); [ L ]a]Represents the atmospheric absorption loss, logarithmic, in decibels (dB); [ L ]p]Represents the polarization loss, logarithmic, in decibels (dB); [ L ]rp]Represents the directional loss of the receiving antenna, in logarithmic terms, in decibels (dB).
Detection power [ P ] of satellite uplink data transmission receiving linkr]uThe calculation formula is as follows:
[Pr]u＝[Pt]u+[Gt]u-[L]u+[Gr]u (2)
in which the uplink power P transmitted by the ground stationt]uGain of ground station antenna Gt]uAre all known in the art and are all known,
detection power [ P ]r]uGain of satellite receiving antenna obtained by real-time measurement
As determined at the time of product design.
Uplink transmission link attenuation L]uUndetermined, the uplink transmission link attenuation [ L ] can be calculated by the formula]uBecause the transmission path and frequency of the uplink and downlink data transmission are consistent, the downlink data transmission link is attenuated [ L ]]dUplink attenuation with same frequency band[L]uAnd (5) the consistency is achieved.
When the satellite uplink link is not communicated, estimating the space and the atmospheric loss including the link according to the orbit information of the satellite, the position information of the ground station and the atmospheric information injected on the ground, thereby obtaining the attenuation estimation of the downlink data transmission link.
Transmission loss [ L ]]The logarithmic expression of (d) is: [ L ]]＝[Lf]+[Lr]+[La]+[Lrp]+[Lp]Where the dominant loss is spatial link loss. The respective attenuation term estimation methods are as follows:
1) spatial loss estimation [ Lf]：
Wherein: d is the satellite-ground distance in km; λ is the operating wavelength; f is the operating frequency in GHz. The way the satellite-ground distance d is calculated is shown in fig. 3.
Wherein: alpha is a viewing angle; beta is the ground receiving elevation angle; rE6371km for earth radius; h is the track height.
According to the triangle theorem, there is the following relationship:
the satellite-ground distance can be calculated by the formula, and then the free space transmission loss is calculated.
2) Loss of rainfall [ Lr]And (3) estimating:
the increase in radio wave propagation loss caused by rainfall is called rain attenuation. The rain attenuation is generated by the absorption and scattering of microwave energy by raindrops, the action degree of the rain attenuation is determined by the microstructure of rainfall, such as the size distribution, the temperature, the speed and even the shape of the raindrops, and the rain attenuation is increased along with the increase of the frequency, and when the frequency band is higher than 10GHz, the rainfall causes the most important atmospheric attenuation factor in the process of electric wave propagation. Since rain fade cannot be predicted accurately, the value of rain fade is generally estimated only from empirical curves, leaving sufficient margin in link calculations, as shown in fig. 4.
Once the location of the ground station is determined, the precipitation rate R of the area can be determinedp(mm/h) and the annual time probability of occurrence p%. The precipitation distribution in asian regions is shown in fig. 4. Each region of China belongs to C, E, F, K, N, wherein the southeast region is the N region, and most of the middle region is the K region. And regularly injecting the weather grade of the area where the ground station belongs, and performing rain attenuation estimation on the satellite according to a rain, cloud and fog attenuation curve.
3) Atmospheric absorption loss [ La]
In clear weather, the atmosphere will cause additional absorption loss for the propagation of the electric waves. In the frequency range of 15GHz-35GHz, the loss due to the absorption of the electric wave by the water vapor molecules is predominant and there is a peak at 22GHz (but not more than 1dB under high elevation conditions). Whereas in the frequency range of 35GHz-80GHz, the absorption of mainly oxygen molecules increases the additional loss and has a larger loss peak (over 100dB) at 60 GHz. In general, the absorption loss increases with increasing frequency, but there is a lowest valley point at 30 GHz.
Like rain decay, atmospheric absorption loss cannot be quantitatively analyzed, and generally only an estimate is taken from empirical curves, as shown in fig. 5.
4) Polarization loss [ L ]p]
Polarization deviation may occur in the transmission process of the data transmission radio frequency signal, so that when energy is coupled to a receiving antenna from space, polarization loss exists, particularly, depolarization of radio waves caused by rainfall is obvious, and a value generally taken in link estimation is 1.5 dB.
5) Antenna pointing loss Lrp]
As shown in fig. 6, the terrestrial receive antenna gain is the peak of the antenna gain that can be achieved, i.e., the gain when the antenna beam is directed at the satellite. Since the ground station antenna is affected by wind, the satellite drifts in orbit or other technical reasons, and antenna pointing deviation occurs. The reduction in antenna gain caused by this condition is called antenna pointing loss. When the off-angle is less than 1.5 times the half-power beam angle, the influence of the pointing error on the antenna gain is reflected by the following equation:
wherein G ismAt maximum gain of the antenna, theta0.5Theta is the antenna pointing error (i.e., the angle of the antenna from the main axis) for the beamwidth of the antenna half-power point. Taking the logarithm of the above formula, as follows:
the calculation formula of the antenna pointing loss can be obtained:
controlling accuracy and beam width theta based on ground station pointing error when calculating link0.5The antenna directional loss and the polarization loss L can be calculatedp]As such, are accumulated as constant values in the link estimation.
Specifically, the step M3 includes: in order to reduce the remote sensing data volume, the remote sensing area with the target is identified through on-satellite preprocessing target detection, the detection threshold is reduced, the false alarm rate is improved, and the effective target is prevented from being missed; meanwhile, a hot spot area needing downloading is designated through ground upper injection parameter information or a ground remote sensing designated area is used as the hot spot area, and an interested remote sensing area is identified;
the preprocessing comprises machine learning, image recognition and detection of a target of remote sensing imaging;
the hot spot region comprises a sensitive region and a designated background region.
Specifically, the step M5 includes:
step M5.1: caching original remote sensing data, preprocessed target detection data and remote sensing compressed data in a remote sensing buffer area for selecting, storing and downloading;
step M5.2: selecting corresponding data of the remote sensing buffer area for storage according to the information of the remote sensing area of interest, and selecting and storing preprocessed target detection data and original remote sensing data when the remote sensing area of interest is not large and the original remote sensing data can be downloaded; when the remote sensing area of interest is large and the original data cannot be downloaded, selecting to store the preprocessed target detection data and the remote sensing compressed data to obtain the selected stored remote sensing data, and generally storing the preprocessed detection data and the original data;
step M5.3: obtaining remote sensing data quantity estimation to be downloaded according to the selected stored remote sensing data, and taking the remote sensing data quantity estimation as a consideration factor of satellite-ground data chain decision;
specifically, the step M6 includes: according to the remote sensing data quantity estimation and satellite-ground data transmission link loss to be downloaded, the code rate, the coding mode, the modulation mode and the transmitting power of the remote sensing data link are determined, the selected stored remote sensing data are read, satellite data transmission is automatically adjusted, the transmitting power and the channel utilization rate are optimized, and the remote sensing data transmission capability is improved.
And after the downlink attenuation is obtained, the link model adjusts the link characteristics such as satellite transmitting power, data rate and the like through the downlink signal transmission model.
Estimating and obtaining the downlink attenuation L by the uplink detection mode of the step M1]dAccording to the estimated satellite-ground transmission link [ L]dAnd the output power [ P ] of the known on-board satellite transmittert]dEmission gain [ G ]t]dGround station receiving capability [ G ]r/Tr]dChannel coding gain [ G ]c]dCan be calculated as follows
The value is obtained.
The downlink transmission signal model is as follows:
wherein, [ k ]]Logarithmic values of Boltzmann constants in decibels (dB). [ R ]c]maxThe logarithm of the maximum link transmission bit rate after channel coding is in decibel bits per second (dBbit/s); [ G ]c]Channel coding gain, logarithmic value, in decibels (dB).
E corresponding to bit error rate greater than system requirementb/N0A threshold value such that a maximum coding data rate R is obtainedc]maxThereby obtaining the maximum data transmission capability of the satellite at that time. If the transmission rate [ R ] required by the satellite datac]Less than [ R ]c]maxThen [ P ] can be decreasedt]dReducing power consumption of, or boosting, satellites
The demodulation quality of the data received by the ground station is improved. To sum up, can be found in
[Rc]、[Pt]dThe balance among the 3 variables is selected or rejected, and the automatic adjustment is carried out, so that the data transmission is ensured, the satellite function can be saved, and the intelligent automatic adjustment of a data chain is realized.
The invention provides a satellite intelligent data transmission system based on remote sensing state estimation, which comprises:
module M1: estimating satellite-ground data transmission link loss in real time and satellite-ground channel data transmission capacity according to uplink power detection and link model estimation;
module M2: calculating to obtain the maximum data transmission capacity of data transmission according to the satellite-ground data transmission link loss obtained by real-time estimation and by combining the data transmission transmitting power of a satellite and the receiving capacity of a ground receiver, and taking the maximum data transmission capacity as a consideration factor of the selection decision of the remote sensing data;
module M3: identifying an interested remote sensing area through preprocessing target detection and hot spot area designation;
module M4: according to the obtained maximum data transmission capacity of data transmission and the data volume of the remote sensing area of interest, whether compressed data needs to be transmitted or not is evaluated, compression parameters are set, and the compression ratio and the compression quality of the remote sensing data are adjusted, so that the compressed data can be transmitted to the ground, and better compression quality can be considered.
Module M5: caching preprocessed target detection data, original remote sensing data and compressed remote sensing data, selecting and storing data information to be downloaded according to the maximum data transmission capacity of data transmission and the data volume of the remote sensing area of interest, and accordingly obtaining remote sensing data volume estimation to be downloaded;
module M6: reading data to be downloaded, and automatically adjusting a satellite data transmission link according to the remote sensing data amount to be downloaded and the satellite-ground data transmission link loss;
specifically, the module M1 includes:
when the satellite uplink link is smooth, the satellite receives the ground uplink radio frequency signal in the same frequency band as the downlink data transmission, the power level of the uplink signal is detected and measured, the ground transmission power and the loss of the satellite receiver are known, the uplink attenuation is obtained, and the downlink data transmission link attenuation is basically consistent with the uplink attenuation in the same frequency band;
in addition, because electromagnetic waves pass through different space environments such as an ionosphere, a troposphere and the like in the signal transmission process, the ionosphere flickers in the ionosphere, and rainfall attenuation, atmospheric absorption, scattering and absorption of cloud mist, snowfall and the like, and atmospheric refraction, sunscals and the like in the troposphere cause additional loss [ L ] of space propagation. The logarithmic expression for the transmission loss [ L ] is:
[L]＝[Lf]+[Lr]+[La]+[Lrp]+[Lp] (1)
wherein: [ L ]f]Represents the free space transmission loss in logarithmic values in decibels (dB); [ L ]r]Represents the rainfall loss in logarithmic values in decibels (dB); [ L ]a]Represents the atmospheric absorption loss, logarithmic, in decibels (dB); [ L ]p]Represents the polarization loss, logarithmic, in decibels (dB); [ L ]rp]Represents the directional loss of the receiving antenna, in logarithmic terms, in decibels (dB).
Detection power [ P ] of satellite uplink data transmission receiving linkr]uThe calculation formula is as follows:
[Pr]u＝[Pt]u+[Gt]u-[L]u+[Gr]u (2)
in which the uplink power P transmitted by the ground stationt]uGain of ground station antenna Gt]uAre all known in the art and are all known,
detection power [ P ]r]uGain of satellite receiving antenna obtained by real-time measurement
As determined at the time of product design.
Uplink transmission link attenuation L]uUndetermined, the uplink transmission link attenuation [ L ] can be calculated by the formula]uBecause the transmission path and frequency of the uplink and downlink data transmission are consistent, the downlink data transmission link is attenuated [ L ]]dAttenuation [ L ] of uplink with same frequency band]uAnd (5) the consistency is achieved.
When the satellite uplink link is not communicated, estimating the space and the atmospheric loss including the link according to the orbit information of the satellite, the position information of the ground station and the atmospheric information injected on the ground, thereby obtaining the attenuation estimation of the downlink data transmission link.
Transmission loss [ L ]]The logarithmic expression of (d) is: [ L ]]＝[Lf]+[Lr]+[La]+[Lrp]+[Lp]Where the dominant loss is spatial link loss. The respective attenuation term estimation methods are as follows:
1) spatial loss estimation [ Lf]：
Wherein: d is the satellite-ground distance in km; λ is the operating wavelength; f is the operating frequency in GHz. The way the satellite-ground distance d is calculated is shown in fig. 3.
Wherein: alpha is a viewing angle; beta is the ground receiving elevation angle; rE6371km for earth radius; h is the track height.
According to the triangle theorem, there is the following relationship:
the satellite-ground distance can be calculated by the formula, and then the free space transmission loss is calculated.
2) Loss of rainfall [ Lr]And (3) estimating:
the increase in radio wave propagation loss caused by rainfall is called rain attenuation. The rain attenuation is generated by the absorption and scattering of microwave energy by raindrops, the action degree of the rain attenuation is determined by the microstructure of rainfall, such as the size distribution, the temperature, the speed and even the shape of the raindrops, and the rain attenuation is increased along with the increase of the frequency, and when the frequency band is higher than 10GHz, the rainfall causes the most important atmospheric attenuation factor in the process of electric wave propagation. Since rain fade cannot be predicted accurately, the value of rain fade is generally estimated only from empirical curves, leaving sufficient margin in link calculations, as shown in fig. 4.
Once the location of the ground station is determined, the precipitation rate R of the area can be determinedp(mm/h) and the annual time probability of occurrence p%. The precipitation distribution in asian regions is shown in fig. 4. Each region of China belongs to C, E, F, K, N, wherein the southeast region is the N region, and most of the middle region is the K region. And regularly injecting the weather grade of the area where the ground station belongs, and performing rain attenuation estimation on the satellite according to a rain, cloud and fog attenuation curve.
3) Atmospheric absorption loss [ La]
In clear weather, the atmosphere will cause additional absorption loss for the propagation of the electric waves. In the frequency range of 15GHz-35GHz, the loss due to the absorption of the electric wave by the water vapor molecules is predominant and there is a peak at 22GHz (but not more than 1dB under high elevation conditions). Whereas in the frequency range of 35GHz-80GHz, the absorption of mainly oxygen molecules increases the additional loss and has a larger loss peak (over 100dB) at 60 GHz. In general, the absorption loss increases with increasing frequency, but there is a lowest valley point at 30 GHz.
Like rain decay, atmospheric absorption loss cannot be quantitatively analyzed, and generally only an estimate is taken from empirical curves, as shown in fig. 5.
4) Polarization loss [ L ]p]
Polarization deviation may occur in the transmission process of the data transmission radio frequency signal, so that when energy is coupled to a receiving antenna from space, polarization loss exists, particularly, depolarization of radio waves caused by rainfall is obvious, and a value generally taken in link estimation is 1.5 dB.
5) Antenna pointing loss Lrp]
As shown in fig. 6, the terrestrial receive antenna gain is the peak of the antenna gain that can be achieved, i.e., the gain when the antenna beam is directed at the satellite. Since the ground station antenna is affected by wind, the satellite drifts in orbit or other technical reasons, and antenna pointing deviation occurs. The reduction in antenna gain caused by this condition is called antenna pointing loss. When the off-angle is less than 1.5 times the half-power beam angle, the influence of the pointing error on the antenna gain is reflected by the following equation:
wherein G ismAt maximum gain of the antenna, theta0.5Theta is the antenna pointing error (i.e., the angle of the antenna from the main axis) for the beamwidth of the antenna half-power point. Taking the logarithm of the above formula, as follows:
the calculation formula of the antenna pointing loss can be obtained:
controlling precision according to ground station pointing error during link calculationDegree and beam width theta0.5The antenna directional loss and the polarization loss L can be calculatedp]As such, are accumulated as constant values in the link estimation.
Specifically, the module M3 includes: in order to reduce the remote sensing data volume, the remote sensing area with the target is identified through on-satellite preprocessing target detection, the detection threshold is reduced, the false alarm rate is improved, and the effective target is prevented from being missed; meanwhile, a hot spot area needing downloading is designated through ground upper injection parameter information or a ground remote sensing designated area is used as the hot spot area, and an interested remote sensing area is identified;
the preprocessing comprises machine learning, image recognition and detection of a target of remote sensing imaging;
the hot spot region comprises a sensitive region and a designated background region.
Specifically, the module M5 includes:
module M5.1: caching original remote sensing data, preprocessed target detection data and remote sensing compressed data in a remote sensing buffer area for selecting, storing and downloading;
module M5.2: selecting corresponding data of the remote sensing buffer area for storage according to the information of the remote sensing area of interest, and selecting and storing preprocessed target detection data and original remote sensing data when the remote sensing area of interest is not large and the original remote sensing data can be downloaded; when the remote sensing area of interest is large and the original data cannot be downloaded, selecting to store the preprocessed target detection data and the remote sensing compressed data to obtain the selected stored remote sensing data, and generally storing the preprocessed detection data and the original data;
module M5.3: obtaining remote sensing data quantity estimation to be downloaded according to the selected stored remote sensing data, and taking the remote sensing data quantity estimation as a consideration factor of satellite-ground data chain decision;
specifically, the module M6 includes: according to the remote sensing data quantity estimation and satellite-ground data transmission link loss to be downloaded, the code rate, the coding mode, the modulation mode and the transmitting power of the remote sensing data link are determined, the selected stored remote sensing data are read, satellite data transmission is automatically adjusted, the transmitting power and the channel utilization rate are optimized, and the remote sensing data transmission capability is improved.
And after the downlink attenuation is obtained, the link model adjusts the link characteristics such as satellite transmitting power, data rate and the like through the downlink signal transmission model.
The downlink attenuation L is estimated and obtained by the uplink detection mode of the module M1]dAccording to the estimated satellite-ground transmission link [ L]dAnd the output power [ P ] of the known on-board satellite transmittert]dEmission gain [ G ]t]dGround station receiving capability [ G ]r/Tr]dChannel coding gain [ G ]c]dCan be calculated as follows
The value is obtained.
The downlink transmission signal model is as follows:
wherein, [ k ]]Logarithmic values of Boltzmann constants in decibels (dB). [ R ]c]maxThe logarithm of the maximum link transmission bit rate after channel coding is in decibel bits per second (dBbit/s); [ G ]c]Channel coding gain, logarithmic value, in decibels (dB).
E corresponding to bit error rate greater than system requirementb/N0A threshold value such that a maximum coding data rate R is obtainedc]maxThereby obtaining the maximum data transmission capability of the satellite at that time. If the transmission rate [ R ] required by the satellite datac]Less than [ R ]c]maxThen [ P ] can be decreasedt]dReducing power consumption of, or boosting, satellites
The demodulation quality of the data received by the ground station is improved. To sum up, can be found in
[Rc]、[Pt]dThe balance among the 3 variables is selected or rejected, and the automatic adjustment is carried out, so that the data transmission is ensured, the satellite function can be saved, and the intelligent automatic adjustment of a data chain is realized.
The method can be applied to a satellite data transmission system, necessary downloading information is optimized based on hot spot region designation and image preprocessing detection, the satellite-ground link state is dynamically sensed, the encoding, modulation and power of downlink data transmission are optimized by combining the data volume to be downloaded, and the quality and efficiency of satellite downloading remote sensing information are improved;
in conclusion, satellite-ground data transmission link loss is estimated in real time, an interested remote sensing area is identified, compression parameters are adjusted according to data transmission capacity and data volume of the interested area, and data information needing to be downloaded is selected and stored; and then automatically adjusting satellite data transmission according to the selected downloaded remote sensing data volume, optimizing the code rate, the coding mode, the modulation mode and the transmitting power of a remote sensing data chain, improving the transmission capability of the remote sensing data and having good ground engineering application value.
Those skilled in the art will appreciate that, in addition to implementing the systems, apparatus, and various modules thereof provided by the present invention in purely computer readable program code, the same procedures can be implemented entirely by logically programming method steps such that the systems, apparatus, and various modules thereof are provided in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers and the like. Therefore, the system, the device and the modules thereof provided by the present invention can be considered as a hardware component, and the modules included in the system, the device and the modules thereof for implementing various programs can also be considered as structures in the hardware component; modules for performing various functions may also be considered to be both software programs for performing the methods and structures within hardware components.
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 (8)
1. A satellite intelligent data transmission method based on remote sensing state estimation is characterized by comprising the following steps:
step M1: estimating the loss of the satellite-ground data transmission link in real time according to uplink power detection and link model estimation;
step M2: calculating to obtain the maximum data transmission capacity of data transmission according to the satellite-ground data transmission link loss obtained by real-time estimation and by combining the data transmission transmitting power of a satellite and the receiving capacity of a ground receiver;
step M3: identifying an interested remote sensing area through preprocessing target detection and hot spot area designation;
step M4: setting compression parameters according to the obtained maximum data transmission capacity of data transmission and the data volume of the remote sensing area of interest, and adjusting the compression ratio and the compression quality of the remote sensing data;
step M5: caching preprocessed target detection data, original remote sensing data and compressed remote sensing data, selecting and storing data information to be downloaded according to the maximum data transmission capacity of data transmission and the data volume of the remote sensing area of interest, and accordingly obtaining remote sensing data volume estimation to be downloaded;
step M6: reading data to be downloaded, and automatically adjusting a satellite data transmission link according to the remote sensing data amount to be downloaded and the satellite-ground data transmission link loss;
after the downlink attenuation is obtained, the link model adjusts the link characteristics of satellite transmitting power and data rate through a downlink signal transmission model;
the step M1 includes:
when the satellite uplink link is smooth, the satellite receives the ground uplink radio frequency signal in the same frequency band as the downlink data transmission, the power level of the uplink signal is detected and measured, the ground transmission power and the loss of the satellite receiver are known, the uplink attenuation is obtained, and the downlink data transmission link attenuation is consistent with the uplink attenuation in the same frequency band;
when the satellite uplink link is not communicated, estimating the space and the atmospheric loss including the link according to the orbit information of the satellite, the position information of the ground station and the atmospheric information injected on the ground, thereby obtaining the attenuation estimation of the downlink data transmission link.
2. The intelligent satellite data transmission method based on remote sensing state estimation according to claim 1, wherein the step M3 includes: the method comprises the steps of identifying a remote sensing area with a target through on-satellite preprocessing target detection, and identifying an interested remote sensing area by specifying a hot spot area needing downloading or by taking a ground remote sensing specified area as the hot spot area through ground on-ground injection parameter information;
the preprocessing comprises machine learning, image recognition and detection of a target of remote sensing imaging;
the hot spot region comprises a sensitive region and a designated background region.
3. The intelligent satellite data transmission method based on remote sensing state estimation according to claim 1, wherein the step M5 includes:
step M5.1: caching original remote sensing data, preprocessed target detection data and remote sensing compressed data in a remote sensing buffer area for selecting, storing and downloading;
step M5.2: selecting corresponding data of the remote sensing buffer area for storage according to the information of the remote sensing area of interest, and selecting and storing preprocessed target detection data and original remote sensing data when the remote sensing area of interest does not reach a preset value and the original remote sensing data accords with a preset downloading condition; when the remote sensing area of interest reaches a preset value and the original data cannot be downloaded, selecting and storing preprocessed target detection data and remote sensing compressed data to obtain selected stored remote sensing data;
step M5.3: and obtaining the remote sensing data quantity estimation to be downloaded according to the selected stored remote sensing data.
4. The intelligent satellite data transmission method based on remote sensing state estimation according to claim 1, wherein the step M6 includes: according to the remote sensing data quantity estimation and satellite-ground data transmission link loss to be downloaded, the code rate, the coding mode, the modulation mode and the transmitting power of the remote sensing data link are determined, the selected stored remote sensing data are read, satellite data transmission is automatically adjusted, the transmitting power and the channel utilization rate are optimized, and the remote sensing data transmission capability is improved.
5. A satellite intelligent data transmission system based on remote sensing state estimation is characterized by comprising:
module M1: estimating the loss of the satellite-ground data transmission link in real time according to uplink power detection and link model estimation;
module M2: calculating to obtain the maximum data transmission capacity of data transmission according to the satellite-ground data transmission link loss obtained by real-time estimation and by combining the data transmission transmitting power of a satellite and the receiving capacity of a ground receiver;
module M3: identifying an interested remote sensing area through preprocessing target detection and hot spot area designation;
module M4: setting compression parameters according to the obtained maximum data transmission capacity of data transmission and the data volume of the remote sensing area of interest, and adjusting the compression ratio and the compression quality of the remote sensing data;
module M5: caching preprocessed target detection data, original remote sensing data and compressed remote sensing data, selecting and storing data information to be downloaded according to the maximum data transmission capacity of data transmission and the data volume of the remote sensing area of interest, and accordingly obtaining remote sensing data volume estimation to be downloaded;
module M6: reading data to be downloaded, and automatically adjusting a satellite data transmission link according to the remote sensing data amount to be downloaded and the satellite-ground data transmission link loss;
after the downlink attenuation is obtained, the link model adjusts the link characteristics of satellite transmitting power and data rate through a downlink signal transmission model;
the module M1 includes:
when the satellite uplink link is smooth, the satellite receives the ground uplink radio frequency signal in the same frequency band as the downlink data transmission, the power level of the uplink signal is detected and measured, the ground transmission power and the loss of the satellite receiver are known, the uplink attenuation is obtained, and the downlink data transmission link attenuation is consistent with the uplink attenuation in the same frequency band;
when the satellite uplink link is not communicated, estimating the space and the atmospheric loss including the link according to the orbit information of the satellite, the position information of the ground station and the atmospheric information injected on the ground, thereby obtaining the attenuation estimation of the downlink data transmission link.
6. The intelligent satellite data transmission system based on remote sensing state estimation according to claim 5, wherein the module M3 comprises: the method comprises the steps of identifying a remote sensing area with a target through on-satellite preprocessing target detection, and identifying an interested remote sensing area by specifying a hot spot area needing downloading or by taking a ground remote sensing specified area as the hot spot area through ground on-ground injection parameter information;
the preprocessing comprises machine learning, image recognition and detection of a target of remote sensing imaging;
the hot spot region comprises a sensitive region and a designated background region.
7. The intelligent satellite data transmission system based on remote sensing state estimation according to claim 5, wherein the module M5 comprises:
module M5.1: caching original remote sensing data, preprocessed target detection data and remote sensing compressed data in a remote sensing buffer area for selecting, storing and downloading;
module M5.2: selecting corresponding data of the remote sensing buffer area for storage according to the information of the remote sensing area of interest, and selecting and storing preprocessed target detection data and original remote sensing data when the remote sensing area of interest does not reach a preset value and the original remote sensing data accords with a preset downloading condition; when the remote sensing area of interest reaches a preset value and the original data cannot be downloaded, selecting and storing preprocessed target detection data and remote sensing compressed data to obtain selected stored remote sensing data;
module M5.3: and obtaining the remote sensing data quantity estimation to be downloaded according to the selected stored remote sensing data.
8. The intelligent satellite data transmission system based on remote sensing state estimation according to claim 5, wherein the module M6 comprises: according to the remote sensing data quantity estimation and satellite-ground data transmission link loss to be downloaded, the code rate, the coding mode, the modulation mode and the transmitting power of the remote sensing data link are determined, the selected stored remote sensing data are read, satellite data transmission is automatically adjusted, the transmitting power and the channel utilization rate are optimized, and the remote sensing data transmission capability is improved.
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