CN111862267A - Global spectrum temperature map construction method and system - Google Patents
Global spectrum temperature map construction method and system Download PDFInfo
- Publication number
- CN111862267A CN111862267A CN202010724893.XA CN202010724893A CN111862267A CN 111862267 A CN111862267 A CN 111862267A CN 202010724893 A CN202010724893 A CN 202010724893A CN 111862267 A CN111862267 A CN 111862267A
- Authority
- CN
- China
- Prior art keywords
- satellite
- grid
- generator
- global
- temperature map
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T11/00—2D [Two Dimensional] image generation
- G06T11/20—Drawing from basic elements, e.g. lines or circles
- G06T11/206—Drawing of charts or graphs
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/29—Geographical information databases
Abstract
The embodiment of the application discloses a method and a system for building a global spectrum temperature map, wherein the method comprises the steps that a satellite-borne spectrometer generates the global spectrum temperature map according to an acquired global spectrum power map, the global spectrum temperature map is divided into a plurality of grid areas according to the resolution of a satellite, and then the global spectrum temperature map corresponding to each frequency point is built according to the divided grid areas. Therefore, a global spectrum temperature map under each frequency point is formed based on the subdivided grid region, and the purpose of improving the spatial resolution of satellite spectrum sensing can be effectively achieved.
Description
Technical Field
The embodiment of the application relates to the field of data processing, in particular to a method and a system for building a global spectrum temperature map.
Background
In the existing satellite mobile communication system, a radio system is generally used for sensing spectrum utilization so that a sensing node can access a vacant spectrum, and the stable operation of the radio system depends on the accuracy and reliability of spectrum sensing.
At present, there are three measurement modes for the ground spectrum interference temperature: firstly, the sensing terminal detects the ambient interference temperature by itself and calculates the interference state of the same frequency band authorized terminal after the sensing terminal accesses the same frequency band authorized terminal, but the method is easy to have the problems of hiding the terminal and exposing the terminal. The problem of hiding the terminal is shown in fig. 1, where a is assumed to be an authorized terminal transmitter, B is assumed to be an authorized terminal receiver, 1 is assumed to be a sensing terminal transmitter, and 2 is assumed to be a sensing terminal receiver. Since the sensing terminal transmitter 1 is outside the maximum communication distance range (shown by the dotted line in the figure) of the authorization terminal transmitter a, it cannot be detected that the authorization terminal transmitter a sends a message to the authorization terminal receiver B, and then the sending of the message from the sensing terminal transmitter 1 to the sensing terminal receiver 2 may affect the receiving of the message by the authorization terminal receiver B. Based on the same assumption, the problem of exposing the terminal is shown in fig. 2, because the sensing terminal transmitter 1 is within the maximum communication distance range of the authorization terminal transmitter a, it detects that the authorization terminal transmitter a is sending a message to the authorization terminal receiver B, thereby abandoning the communication with the sensing terminal receiver 2, but because the authorization terminal receiver B is outside the maximum communication range of the sensing terminal transmitter 1, the communication between the sensing terminal transmitter 1 and the sensing terminal receiver 2 does not affect the message reception of the authorization terminal receiver B, thereby causing the phenomenon of low idle spectrum utilization. Secondly, the detection machine is placed to continuously detect the ambient interference temperature and report the ambient interference temperature to the sensing terminal, but the method is limited by detection correlation and the installation position of the detection machine and cannot be used in many scenes. And thirdly, the affected authorized terminals detect the ambient interference temperature and report the ambient interference temperature to each sensing terminal, but the existing authorized terminals are required to have the capability of measuring the interference temperature.
In order to solve the above problems, the existing technical solution adopts a multi-antenna common sensing and multi-node cooperative spectrum sensing manner. However, there are many differences between the satellite system and the terrestrial system, and in order to ensure the accuracy and reliability of the satellite spectrum sensing, the spatial resolution of the spectrum sensing in the satellite system needs to be improved.
Disclosure of Invention
In order to solve at least one of the above technical problems, embodiments of the present application provide the following solutions.
In a first aspect, an embodiment of the present application further provides a global spectrum temperature map construction method, where the method includes:
the satellite-borne frequency spectrograph generates a global frequency spectrum temperature map according to the acquired global frequency spectrum power map;
the satellite-borne frequency spectrograph divides the global frequency spectrum temperature map into a plurality of grid areas according to the resolution of a satellite;
and the satellite-borne frequency spectrograph constructs a global spectrum temperature map corresponding to each frequency point according to the grid areas.
In a second aspect, an embodiment of the present application further provides a global spectrum temperature mapping system, where the system includes: a satellite-borne spectrometer;
the satellite-borne spectrometer is used for generating a global spectrum temperature map according to the acquired global spectrum power map;
the satellite-borne spectrometer is used for dividing the global spectrum temperature map into a plurality of grid areas according to the resolution of a satellite;
and the satellite-borne frequency spectrograph is used for constructing a global frequency spectrum temperature map corresponding to each frequency point according to the grid areas.
The embodiment of the application provides a global spectrum temperature map construction method and a global spectrum temperature map construction system, wherein the method comprises the steps that a satellite-borne spectrometer generates a global spectrum temperature map according to an acquired global spectrum power map, the global spectrum temperature map is divided into a plurality of grid areas according to the resolution of a satellite, and then the global spectrum temperature map corresponding to each frequency point is constructed according to the divided grid areas. Therefore, a global spectrum temperature map under each frequency point is formed based on the subdivided grid region, and the purpose of improving the spatial resolution of satellite spectrum sensing can be effectively achieved.
Drawings
Fig. 1 is a schematic diagram of a hidden terminal;
FIG. 2 is a schematic view of an exposed terminal;
FIG. 3 is a schematic diagram of satellite in-orbit collection of ground interference temperatures;
FIG. 4 is a flowchart of a global spectrum temperature map construction method according to an embodiment of the present application;
FIG. 5 is a diagram illustrating terrestrial global spectrum sensing for a satellite according to an embodiment of the present invention;
fig. 6 is a flowchart of constructing a global spectrum temperature map corresponding to each frequency point in the embodiment of the present application.
Detailed Description
The present application will be described in further detail with reference to the following drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the application and are not limiting of the application. It should be further noted that, for the convenience of description, only some of the structures related to the present application are shown in the drawings, not all of the structures.
In addition, in the embodiments of the present application, the words "optionally" or "exemplarily" are used for indicating as examples, illustrations or explanations. Any embodiment or design described herein as "optionally" or "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments or designs. Rather, use of the words "optionally" or "exemplarily" etc. is intended to present the relevant concepts in a concrete fashion.
In a satellite system, since the coverage area of a satellite receiving beam is larger than the ground, for example, the diameter of the coverage area of a low-orbit satellite receiving antenna with the height of 1000km reaches 2987km, and the spatial resolution in an equatorial region is 27 ° × 27 ° (latitude × longitude), however, in fact, the region with high spectrum utilization rate is usually a densely-populated city, and the actual spectrum usage condition of the region of interest cannot be accurately expressed by the sensing range of 3000 km. In addition, since the satellite continuously observes the ground in the on-orbit state, and the spectral power perceived by the satellite does not come from a certain point on the ground, but all power values in a certain area, as shown in fig. 3, the curve represents the track of the satellite sub-satellite point, each circle represents the range of data collected by the satellite-borne spectrometer when the satellite sub-satellite point is at the center of the circle, and as can be seen from the figure, the areas where data are collected at different times t1, t2, t3 and t4 overlap. The overlapping of the satellite spectrum sensing data also makes the task of improving the spatial resolution of the satellite spectrum sensing difficult.
The current method is to use Two-Dimensional iterative partitioning (TDDIP) to solve the problem, and the TDDIP is mainly based on dividing the measurement result of the beam into small blocks and calculating the measurement value of each small block by means of mathematical iteration. However, this method has strong dependence on measured spectrum values of some regions, and is implemented on the assumption that the region area is in direct proportion to the contribution of the region to the spectral power distribution. This assumption leads to the inability of this method to accurately describe the spectral distribution within a small area. For example, several sources of interference are located at the outer edge of the investigation region, and in practice the spectrum of the investigation region should be affected by the sources of interference, but due to the iterative calculation, the sources of interference do not appear in the perceived spectrum of the investigation region.
Based on the technical defect, the embodiment of the application provides a global spectrum temperature map construction method, which aims to achieve the purpose of improving the spatial resolution of satellite spectrum sensing by subdividing a global spectrum temperature map into a plurality of grid regions, wherein each grid region corresponds to one spectrum distribution generator, the generators are subject to spectrum constraints collected by all beams covering the grid, and the generators corresponding to the grid are trained by using the constraint conditions to obtain the most appropriate generator parameters, namely, the generators corresponding to each grid can generate the spectrum temperature map of the grid. Specifically, as shown in fig. 4, the method may include the steps of:
s401, the satellite-borne spectrometer generates a global spectrum temperature map according to the acquired global spectrum power map.
The satellite-borne frequency spectrograph can continuously collect the power of the ground in the investigation frequency band so as to obtain a global spectrum power diagram. The investigation frequency band may be a frequency band set manually, and further, each power in the acquired global spectrum power map may be converted into an equivalent temperature value, so as to generate a global spectrum temperature map.
For example, the above-mentioned manner of converting the power into an equivalent temperature value may be implemented in any manner known in the art. For example, the conversion is performed in the following manner:
wherein, P (f)cAnd B) represents a frequency point of fcThe bandwidth is the average interference level in the B Hz frequency band, k is Boltzmann constant and is 1.38 multiplied by 10-23J/K，T(fcAnd B) represents a frequency point of fcAnd the bandwidth is an equivalent temperature value after the frequency spectrum power of the B Hz frequency band is converted.
S402, the satellite-borne spectrometer divides the global spectrum temperature map into a plurality of grid areas according to the resolution of the satellite.
Assuming that the satellite receiving antenna beam is regarded as a square, the satellite terrestrial global spectrum sensing diagram is shown in fig. 5, the satellite flies along the direction of change of the latitude shown in fig. 5, the beam returns to the starting latitude after the time T elapses after the local sphere makes one circle, but the beam is displaced along the direction of change of the longitude due to the rotation of the earth. After the global spectrum temperature map is acquired based on step S401, the acquired global spectrum temperature map may be divided into a plurality of grid regions according to the resolution of the satellite.
Illustratively, the global spectral temperature map may be partitioned in the following manner: determining the number of grid areas in the longitude direction according to the orbit number of the satellite in the longitude change direction and the resolution of the satellite; and determining the number of grid areas in the latitude direction according to the number of the measured values of each orbit number of the satellite in the latitude change direction and the resolution of the satellite.
For example, assuming that the number of orbits of the satellite in the direction of change of longitude is N, the number of measurement values of each orbit in the direction of change of latitude is M, and the actual spectrum sensing spatial resolution of the satellite is a ° × b °, the division result is G1×G2(latitude × longitude), wherein,
and S403, the satellite-borne spectrometer constructs a global spectrum temperature map corresponding to each frequency point according to the grid areas.
In the embodiment of the application, the satellite-borne spectrometer continuously collects the spectrum temperature according to the sampling interval, and if B is the bandwidth width of the investigation frequency and m is the sampling interval, the satellite-borne spectrometer can collect the spectrum temperature values of B/m frequency points. And then, under each frequency point, constructing a corresponding global spectrum temperature map based on each grid region in a contour line mode. Therefore, a global spectrum temperature map under each frequency point can be obtained, namely B/m global spectrum temperature maps are obtained.
The embodiment of the application provides a global spectrum temperature map construction method, a satellite-borne spectrometer generates a global spectrum temperature map according to an acquired global spectrum power map, divides the global spectrum temperature map into a plurality of grid areas according to the resolution of a satellite, and further constructs a global spectrum temperature map corresponding to each frequency point according to the divided grid areas. Therefore, a global spectrum temperature map under each frequency point is formed based on the subdivided grid region, and the purpose of improving the spatial resolution of satellite spectrum sensing can be effectively achieved.
As shown in fig. 6, in an example, the step S403 may include, but is not limited to, the following steps:
s601, training a discriminator corresponding to each wave beam at a certain frequency point.
In the embodiment of the present application, one discriminator may be set for each beam, and the initial distribution of the discriminators may be
For determining the gap between the data generated by the generator and the real data.
Illustratively, an implementation of this step may repeat the following process for the arbiter for each beam n times: and obtaining a generation sample corresponding to each wave beam according to the data generated by the generator corresponding to the grid area covered by each wave beam, and updating the parameters of the discriminator according to the generation sample, the real data sampled by each wave beam and the maximized first loss function.
For example, assume that m samples are obtained from gaussian distribution p (z), and for each grid region covered by each beam, a correspondence is made between the grid regionsGenerate respective generation data
Then for each beam, the samples generated for each grid area within its coverage are
Wherein, wkRepresents the weight occupied by the kth grid area covered by the beam, and
representing the ith data generated by the generator corresponding to the kth grid region. Sampling the frequency spectrum temperature chart received by each wave beam to obtain real data
The parameters of the arbiter are updated according to the generated samples, the true data sampled for each beam, and the maximized first loss function.
The first loss function is
Where m denotes the actual data or the number of data generated by the generator, xiRepresenting the ith real data, DjRepresents the function of the discriminator corresponding to the jth beam, n represents the number of grid areas covered by the beam, k represents the kth grid area,
indicating correspondence of each beamA sample is generated.
Further, the parameters of the above-mentioned discriminator may be updated according to a first update formula.
For example, the first update formula may be
Wherein, eta is the learning rate,
are parameters of the discriminator.
And S602, training generators corresponding to each grid area at a certain frequency point according to the trained discriminators.
As shown in fig. 5, it is assumed that the physical coverage area of each beam is simply divided into 4 grid regions, and the gray grid region shown in fig. 5 is covered by four beams (four different gray-scale blocks), so for this gray grid region, it is necessary to consider other beams in all the beams covering this grid region, that is, it is necessary to consider the gray grid region shown in fig. 5 and 8 grid regions around it, and 8 grid regions around it are also covered by corresponding beams, so it is necessary to construct generators for all grid regions at the same time, so that the results generated by the generators can be merged into a global spectral temperature map.
Assume that the initial distribution of generators constructed for each grid region is
I.e. a parameter of
And (3) controlling distribution, wherein the frequency spectrum temperature distributions of all grid regions are independent, and the results generated by the generator of each grid region are superposed and spliced to obtain the global frequency spectrum temperature distribution generated by the generator.
For example, the implementation manner of this step may be to obtain sampling samples according to the gaussian distribution corresponding to each grid region, generate theoretical data according to the sampling samples using the generator corresponding to the grid region, and update the parameter of the generator according to the trained discriminator, the theoretical data, and the maximized second loss function.
In the embodiment of the present application, the temperature spectrum graph can be regarded as a graph with frequency on the horizontal axis and equivalent temperature on the vertical axis, that is, regarded as a one-dimensional vector, and any distribution can be fitted due to the fact that the neural network only has a nonlinear activation function. Therefore, the core of this step is to sample the normal distribution and train the generator to generate an optimized spectral temperature distribution.
For example, assuming m samples are taken from the Gaussian distribution P (z), theoretical data is generated from the constructed generator
The trained arbiter trains the generator according to the theoretical data and the maximized second loss function, and updates parameters of the generator.
The second loss function is
Where m denotes the number of true data sampled for the spectral temperature map received for each beam or the number of samples sampled from a gaussian distribution, xiRepresenting the ith real data, DjFunction representing the discriminator corresponding to the jth beam, GkFunction corresponding to generator representing kth grid area, Gk(zi) Representing theoretical data.
Further, the parameters of the generator may be updated according to a second update formula.
Illustratively, the second update formula may be
η in the above formula is the learning rate,
to a parameter of the generator, ajRepresents the proportion of the jth beam covering the corresponding grid area of the generator, and
l represents the number of beams covering the grid area corresponding to the generator.
It will be appreciated by those skilled in the art that in updating the generator parameters, it is necessary to use the derivative of the second loss function with respect to the generator parameters, where the derivative of the first term in the second loss function is 0.
And S603, constructing a global spectrum temperature map under a certain frequency point according to the data generated by the generator of each grid region after training under the condition that the training result of the discriminator meets the preset condition.
In the process of training the discriminator, the discriminator is trained for n times by using real data sampled by each wave beam, namely after iterating for n times, the parameters of the discriminator are updated
And then training the generator once according to the trained discriminator, and updating the parameters of the generator.
And under the condition that the training result of the discriminator meets the preset condition, for example, the generator is trained for Q times, namely, under the condition that the discriminator is trained for n multiplied by Q times, constructing a global spectrum temperature map under a certain frequency point according to the spectrum temperature maps of the corresponding grids generated by the generator of each grid region after training.
S604, repeatedly executing the above steps S601 to S603 until generating the global spectrum temperature map under all the frequency points.
In the embodiment of the application, the generators corresponding to the grid regions are trained by using the discriminators corresponding to all beams covering the grid regions to obtain the most suitable parameters of the generators corresponding to the grid regions, and the spectral temperature diagram of the grid is obtained from the data generated by the trained generators corresponding to each grid region, so that the spatial resolution of satellite spectrum sensing can be effectively improved.
The embodiment of the application also provides a global spectrum temperature map construction system, which comprises a satellite-borne spectrometer, a generator and a discriminator;
the satellite-borne spectrometer is used for generating a global spectrum temperature map according to the acquired global spectrum power map and dividing the global spectrum temperature map into a plurality of grid areas according to the resolution of the satellite. For example, the satellite-borne spectrometer may continuously collect the power of the ground in the survey frequency band through the satellite to obtain a global spectrum power map, and then generate a global spectrum temperature map according to the global spectrum power map.
Furthermore, the satellite-borne spectrometer is also used for constructing a global spectrum temperature map corresponding to each frequency point according to the plurality of grid areas.
In one example, the generator may be configured to generate theoretical data from sampled samples of a gaussian distribution corresponding to each grid region;
the discriminator can be used for training the generators corresponding to each grid region under a certain frequency point so as to discriminate the difference between the data generated by the generators and the real data;
further, the generator is also used for generating a frequency spectrum temperature map of a corresponding grid area under a certain frequency point;
and the satellite-borne spectrometer constructs a global spectrum temperature map under a certain frequency point according to the spectrum temperature map generated by the corresponding generator of each grid region.
In an example, the training mode of the arbiter corresponding to each beam at a certain frequency point may be that a generated sample corresponding to each beam is obtained according to data generated by the generator corresponding to the grid area covered by each beam; the parameters of the discriminator are updated according to the generated samples, the real data sampled for each beam, and the maximized first loss function, which is the above equation (4).
Further, the parameter of the above-mentioned discriminator may be updated by a first update formula, wherein the first update formula is the above-mentioned formula (5).
In an example, the training mode of the trained discriminator for training the generators corresponding to the grid regions at a certain frequency point may be: acquiring sampling samples according to the Gaussian distribution corresponding to each grid area, and generating theoretical data by using a generator corresponding to the grid area according to the sampling samples; the parameters of the generator are updated according to the trained discriminators, the theoretical data, and a maximized second loss function, which may be equation (6) above.
Further, the parameters of the generator may be updated by a second updating formula, wherein the second updating formula is formula (7).
The global spectrum temperature map building system can realize the global spectrum temperature map building method provided by the figures 4 and 6, and has corresponding devices and beneficial effects for realizing the method.
From the above description of the embodiments, it is obvious for those skilled in the art that the present application can be implemented by software and necessary general hardware, and certainly can be implemented by hardware, but the former is a better embodiment in many cases. Based on such understanding, the technical solutions of the present application may be embodied in the form of a software product, which may be stored in a computer-readable storage medium, such as a floppy disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a FLASH Memory (FLASH), a hard disk or an optical disk of a computer, and includes several instructions to enable a computer device (which may be a personal computer, a server, or a network device) to implement the functions described in the embodiments of the present application.
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present application and the technical principles employed. It will be understood by those skilled in the art that the present application is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the application. Therefore, although the present application has been described in more detail with reference to the above embodiments, the present application is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present application, and the scope of the present application is determined by the scope of the appended claims.
Claims (10)
1. A global spectrum temperature map construction method is characterized by comprising the following steps:
the satellite-borne frequency spectrograph generates a global frequency spectrum temperature map according to the acquired global frequency spectrum power map;
the satellite-borne frequency spectrograph divides the global frequency spectrum temperature map into a plurality of grid areas according to the resolution of a satellite;
and the satellite-borne frequency spectrograph constructs a global spectrum temperature map corresponding to each frequency point according to the grid areas.
2. The method of claim 1, wherein the on-board spectrometer divides the global spectral temperature map into a plurality of grid regions according to a resolution of a satellite, comprising:
determining the number of grid areas in the longitude direction according to the orbit number of the satellite in the longitude change direction and the resolution of the satellite;
and determining the number of grid areas in the latitude direction according to the number of the measurement values of each orbit number of the satellite in the latitude change direction and the resolution of the satellite.
3. The method according to claim 1 or 2, wherein the satellite-borne spectrometer constructs a global spectrum temperature map corresponding to each frequency point according to the plurality of grid regions, and the method comprises the following steps:
the method comprises the following steps: training a discriminator corresponding to each wave beam at a certain frequency point;
step two: training generators corresponding to all grid areas under a certain frequency point according to the trained discriminators;
step three: under the condition that the training result of the discriminator meets a preset condition, constructing a global spectrum temperature map under a certain frequency point according to data generated by the generator of each grid region after training;
and repeating the first step to the third step until a global spectrum temperature map under all the frequency points is generated.
4. The method of claim 3, wherein the training of the discriminator corresponding to each beam at a certain frequency point comprises:
obtaining a generation sample corresponding to each wave beam according to data generated by a generator corresponding to a grid area covered by each wave beam;
updating parameters of the discriminator according to the generated samples, real data sampled by each wave beam and a maximized first loss function;
wherein the first loss function is
m represents the actual data or the number of data generated by the generator, xiRepresenting the ith real data, DjRepresents the function of the discriminator corresponding to the jth beam, n represents the number of grid areas covered by the beam, k represents the kth grid area,
representing the generated samples, w, for each beamkRepresenting the weight occupied by the kth mesh region covered by the beam,
the ith data generated by the trained generator corresponding to the kth grid region is represented.
5. The method of claim 4, wherein updating the parameters of the arbiter comprises:
updating the parameters of the discriminator according to a first updating formula;
wherein the first update formula is
Eta is learningThe ratio of the total weight of the particles,
is a parameter of the discriminator.
6. The method of claim 3, wherein training the generator corresponding to each grid region at a certain frequency point according to the trained discriminator comprises:
acquiring sampling samples according to the Gaussian distribution corresponding to each grid area, and generating theoretical data by using a generator corresponding to the grid area according to the sampling samples;
updating the parameters of the generator according to the trained discriminator, the theoretical data and a maximized second loss function;
wherein the second loss function is
m denotes the number of real data or sample samples, xiRepresenting the ith real data, DjFunction representing the discriminator corresponding to the jth beam, GkFunction corresponding to generator representing kth grid area, Gk(zi) Representing theoretical data.
7. The method of claim 6, wherein updating the parameters of the generator comprises:
updating the parameters of the generator according to a second updating formula;
wherein the second update formula is
Eta is the learning rate, and is the learning rate,
as a parameter of the generator, ajRepresents the proportion of the jth beam covering the grid area corresponding to the generator, and l represents the net corresponding to the generatorThe number of beams in the grid area.
8. A global spectral temperature mapping system, comprising: a satellite-borne spectrometer;
the satellite-borne spectrometer is used for generating a global spectrum temperature map according to the acquired global spectrum power map;
the satellite-borne spectrometer is used for dividing the global spectrum temperature map into a plurality of grid areas according to the resolution of a satellite;
and the satellite-borne frequency spectrograph is used for constructing a global frequency spectrum temperature map corresponding to each frequency point according to the grid areas.
9. The system of claim 8, wherein the satellite-based spectrometer is configured to determine the number of grid regions in the longitudinal direction based on the number of orbits of the satellite in the longitudinal direction and the resolution of the satellite, and to determine the number of grid regions in the latitudinal direction based on the number of measurements of each orbit of the satellite in the latitudinal direction and the resolution of the satellite.
10. The system of claim 8 or 9, further comprising a generator and a discriminator;
the generator is used for generating theoretical data according to the sampling samples of the Gaussian distribution corresponding to each grid area;
the discriminator is used for training the generators corresponding to the grid areas under a certain frequency point;
and the generator is also used for generating a frequency spectrum temperature map of a corresponding grid at a certain frequency point under the condition that the training result of the discriminator meets a preset condition.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010724893.XA CN111862267B (en) | 2020-07-24 | 2020-07-24 | Global spectrum temperature map construction method and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010724893.XA CN111862267B (en) | 2020-07-24 | 2020-07-24 | Global spectrum temperature map construction method and system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111862267A true CN111862267A (en) | 2020-10-30 |
| CN111862267B CN111862267B (en) | 2021-06-08 |
Family
ID=72950501
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010724893.XA Active CN111862267B (en) | 2020-07-24 | 2020-07-24 | Global spectrum temperature map construction method and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111862267B (en) |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20160171728A1 (en) * | 2013-07-24 | 2016-06-16 | Valiber Ltd. | Methods and systems for communicating a sensation |
| CN105868529A (en) * | 2016-03-18 | 2016-08-17 | 北京师范大学 | Near-surface daily mean atmospheric temperature retrieval method based on remote control |
| CN106792731A (en) * | 2016-12-23 | 2017-05-31 | 中国电子科技集团公司第五十四研究所 | Satellite communication power distribution method based on non-cooperative game |
| CN109891197A (en) * | 2016-11-01 | 2019-06-14 | 光纳株式会社 | Brillouin scattering measuring method and Brillouin scattering measurement device |
| CN110865832A (en) * | 2019-09-26 | 2020-03-06 | 北京和德宇航技术有限公司 | Communication protocol upgrading method, device and system based on low earth orbit satellite |
| CN111049599A (en) * | 2019-12-09 | 2020-04-21 | 物格微电子(珠海)有限公司 | Calibration method of two-point modulation wireless communication transmitter |
-
2020
- 2020-07-24 CN CN202010724893.XA patent/CN111862267B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20160171728A1 (en) * | 2013-07-24 | 2016-06-16 | Valiber Ltd. | Methods and systems for communicating a sensation |
| CN105868529A (en) * | 2016-03-18 | 2016-08-17 | 北京师范大学 | Near-surface daily mean atmospheric temperature retrieval method based on remote control |
| CN109891197A (en) * | 2016-11-01 | 2019-06-14 | 光纳株式会社 | Brillouin scattering measuring method and Brillouin scattering measurement device |
| CN106792731A (en) * | 2016-12-23 | 2017-05-31 | 中国电子科技集团公司第五十四研究所 | Satellite communication power distribution method based on non-cooperative game |
| CN110865832A (en) * | 2019-09-26 | 2020-03-06 | 北京和德宇航技术有限公司 | Communication protocol upgrading method, device and system based on low earth orbit satellite |
| CN111049599A (en) * | 2019-12-09 | 2020-04-21 | 物格微电子(珠海)有限公司 | Calibration method of two-point modulation wireless communication transmitter |
Non-Patent Citations (2)
| Title |
|---|
| 杨志伟: "认知无线电的频谱探测方案研究", 《中国优秀博硕士学位论文全文数据库 (硕士) 工程科技Ⅱ辑》 * |
| 路海升: "认知无线电频谱探测与管理技术研究", 《中国优秀硕士学位论文全文数据库 信息科技辑》 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111862267B (en) | 2021-06-08 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Overeem et al. | Retrieval algorithm for rainfall mapping from microwave links in a cellular communication network | |
| Loew et al. | A dynamic approach for evaluating coarse scale satellite soil moisture products | |
| Makela et al. | Large-scale measurements of thermospheric dynamics with a multisite Fabry-Perot interferometer network: Overview of plans and results from midlatitude measurements | |
| Pignalberi et al. | Effective solar indices for ionospheric modeling: a review and a proposal for a real-time regional IRI | |
| US20180122128A1 (en) | Iterative ray-tracing for autoscaling of oblique ionograms | |
| CN114049570B (en) | Satellite-borne remote sensing water vapor space inversion method and system based on neural network | |
| Gong et al. | Temporal filtering of InSAR data using statistical parameters from NWP models | |
| CN113253233B (en) | Analysis processing method and system based on all-sky meteor radar signals | |
| RU2683113C1 (en) | Method of determining characteristics of auroral ovals and state of magnetic field of earth | |
| Shen et al. | 3-D tomographic reconstruction of rain field using microwave signals from LEO satellites: Principle and simulation results | |
| Mukesh et al. | Ordinary kriging-and cokriging-based surrogate model for ionospheric TEC prediction using NavIC/GPS data | |
| Šúri et al. | Comparison of direct normal irradiation maps for Europe | |
| Ma et al. | Determination of GPS receiver differential biases by neural network parameter estimation method | |
| Lee et al. | Three-dimensional tomography of ionospheric variability using a dense GPS receiver array | |
| Yu et al. | Using the GPS observations to reconstruct the ionosphere three-dimensionally with an ionospheric data assimilation and analysis system (IDAAS) | |
| CN111862267B (en) | Global spectrum temperature map construction method and system | |
| van de Kamp et al. | Effect of the ionosphere on defocusing of space-based radars | |
| Jiang et al. | Comparison of the Kriging and neural network methods for modeling foF2 maps over North China region | |
| Parker et al. | Modelling the main ionospheric trough using the Electron Density Assimilative Model (EDAM) with assimilated GPS TEC | |
| Pietrella et al. | A comparative study of ionospheric IRIEup and ISP assimilative models during some intense and severe geomagnetic storms | |
| CN113093225B (en) | Wide-area and local-area fused high-precision ionospheric scintillation model establishment method | |
| Kutiev et al. | Real time 3-D electron density reconstruction over Europe by using TaD profiler | |
| Jiang et al. | Compressive Sensing-Based 3-D Rain Field Tomographic Reconstruction Using Simulated Satellite Signals | |
| Said et al. | Empirical Parameterization of Broadband VLF Attenuation in the Earth‐Ionosphere Waveguide | |
| Nigussie et al. | Modeling the East African Ionosphere |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |