CN115508827A - Electromagnetic environment information representation and organization method of electromagnetic multi-domain grid model - Google Patents
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Abstract
The invention provides an electromagnetic environment information representation and organization method of an electromagnetic multi-domain grid model, which comprises the following steps: step 1: firstly, carrying out multi-scale division on hollow domain information in a six-domain characterization model of the electromagnetic environment by adopting a GeoSOT-3D space grid subdivision framework, then discretizing six-domain characterization by adopting a geographic space grid division concept, designing a corresponding coding mode, and forming an electromagnetic multi-domain grid together with an airspace grid, wherein a single multi-domain grid is used as a basic unit of electromagnetic environment data organization; step 2: designing a corresponding electromagnetic information multi-domain grid storage structure based on the constructed electromagnetic multi-domain grid, and realizing the electromagnetic information multi-domain grid storage structure as a physical layer for data organization and storage; and step 3: based on the constructed electromagnetic multi-domain grid, a coding algebra operation system is adopted to calculate the propagation path of the electromagnetic radiation source and the coverage area of the radar, and the electromagnetic data obtained by calculation or measurement is subjected to true three-dimensional expression with selectable scale.
Description
Technical Field
The invention belongs to the technical field of electromagnetic environment, and particularly relates to an electromagnetic environment information representation and organization method of an electromagnetic multi-domain grid model.
Background
With the transformation of war forms and army construction to informatization, the human beings open a fifth dimensional space-an electromagnetic space on the basis of a four-dimensional battlefield space on land, sea, air and sky, and form a new battlefield environment-an electromagnetic environment. Due to the opening of electromagnetic space, the relatively independent space, air, ground and sea become a complete large three-dimensional battlefield, and the utilization and control of the electromagnetic spectrum become the core capacity factor of modern war. Meanwhile, the development trend of informatization, intellectualization and precision combat of modern wars brings exponential explosion and growth of electromagnetic environment information, and new requirements are provided for the management of the electromagnetic environment information: not only needs to construct a global electromagnetic environment basic data model, but also needs to satisfy the requirement of quick update of real-time perception electromagnetic environment detection data, and also needs to have the capability of intelligent deduction. Therefore, the electromagnetic environment can carry out global frequency marking like surveying and mapping, and a three-dimensional global space electromagnetic grid is drawn; the electromagnetic environment can be sensed and predicted in a full-dimensional manner like weather; the system can also be used for marking electromagnetic tags like an identification system of enemies and peoples to realize rapid and autonomous frequency-using interaction among different systems. Thus, accurate perception and fine characterization of the electromagnetic environment is critical.
In the past, the electromagnetic environment of a certain region is generally flat, electromagnetic radiation sources are mainly distributed, time-varying characteristics are not obvious, and the problems that three-dimensional electromagnetic environment information is difficult to uniformly organize, efficiently calculate and integrally express exist. Taking aviation airspace information management as an example, in the flying process of an aircraft, the factors such as take-off, cruising, time, space and the like according to a set route and speed generate a superposition effect on frequency spectrum characteristics, and the superposition effect and the electromagnetic environment along the line generate mutual influence. However, the electromagnetic environment information is not uniformly described in space at present, and the isomorphic analysis efficiency is poor, so that the electromagnetic environment data and the flight route data are difficult to be integrated, associated and organized. In addition, the existing spatial information calculation mode based on longitude and latitude elevation points has the problems of non-uniform grid division, weak geographical relevance, poor calculation real-time performance and the like, cannot process electromagnetic environment data information of multiple domains (time domain, frequency domain, airspace, energy domain and the like) in real time, is difficult to effectively describe the internal structure and the motion characteristics of a multi-domain spatial object, and further influences the efficient application of electromagnetic environment data and the reasonable configuration of electromagnetic equipment resources. In addition, the change of the electromagnetic environment data is accompanied by the generation of the time information data. The time information has wide sources, different structures and various scales, and by adopting the existing time coding model, ambiguity can be generated by time identification, multi-scale time information is difficult to uniformly organize, and the multi-scale time calculation efficiency needs to be improved.
From the above analysis, no matter in military or civil fields, the core bottleneck problems that electromagnetic environment information lacks unified time and space information, the computational efficiency is low, and the like are solved, and important application requirements of unified organization, unified expression and unified management and control are provided for the electromagnetic environment information, so that the core is to solve the problem of how to efficiently organize, calculate and express multi-domain electromagnetic environment information and time dimension thereof to meet the requirements.
In order to improve the efficient and fine expression capability of the electromagnetic environment information, the electromagnetic environment needs to be described in a grid mode in a layered and lattice-by-lattice mode, the problem of describing the electromagnetic environment data in domains such as time domain, frequency domain, space domain and the like is solved, and a global unified electromagnetic environment data organization framework is constructed. The invention tries to construct a uniform electromagnetic environment data field by taking a multi-domain grid as a unit and discretizing electromagnetic environment information such as a time domain, a frequency domain, a space domain and the like on the basis of a time-space electromagnetic environment data model and an earth three-dimensional subdivision data model, develops the research on the problems of visualization of electromagnetic environment data, radiation source propagation path calculation and the like on the basis of the unified electromagnetic environment data field, and provides a new theoretical basis and technical support for constructing a next-generation intelligent electromagnetic environment information system.
Disclosure of Invention
The invention aims to provide an electromagnetic environment information representation and organization method of an electromagnetic multi-domain grid model.
The technical scheme adopted by the invention is as follows:
the method for representing and organizing the electromagnetic environment information of the electromagnetic multi-domain grid model comprises the following steps:
step 1: firstly, carrying out multi-scale division on hollow domain information in a six-domain characterization model of the electromagnetic environment by adopting a GeoSOT-3D space grid subdivision framework, then discretizing six-domain characterization by adopting a geographic space grid division concept, designing a corresponding coding mode, and forming an electromagnetic multi-domain grid together with an airspace grid, wherein a single multi-domain grid is used as a basic unit of electromagnetic environment data organization;
and 2, step: designing a corresponding electromagnetic information multi-domain grid storage structure based on the constructed electromagnetic multi-domain grid, and realizing the electromagnetic information multi-domain grid storage structure as a physical layer for data organization and storage;
and step 3: based on the constructed electromagnetic multi-domain grid, a coding algebra operation system is adopted to calculate the propagation path of the electromagnetic radiation source and the coverage area of the radar, and the electromagnetic data obtained by calculation or measurement is subjected to true three-dimensional expression with selectable scale.
Preferably, in step 1, the six-domain characterization includes a time domain, a frequency domain, a space domain, an energy domain and a modulation domain characterization, and the basic characteristics of the electromagnetic environment data are constantly changed in the time domain, the frequency domain and the space domain, the time domain, the frequency domain and the space domain are relatively independent, and the data association of any time period, any frequency band and any space in the electromagnetic environment is realized by performing association processing on the time domain, the frequency domain and the space domain.
Preferably, in step 2, the time domain, frequency domain, space domain and energy domain data of the electromagnetic environment in each grid are discretized by an encoding method, and the multi-domain grid is taken as a basic unit, and the encoding process is as follows:
(1) The time domain is subdivided and decoded as follows:
adopting GeoSOT time grid coding, discretizing time into time intervals with different lengths, and endowing unique binary codes to ensure that the time is discretized into time periods with lengths so as to form a time discretization frame in the electromagnetic environment information organization;
(2) And (3) carrying out subdivision coding on the frequency domain, namely the frequency subdivision decoding process is as follows:
the frequency decoding is established on the basis of segmented expression, a frequency range from 0.1Hz to 1PHz is divided into 16 segments by taking 10 octaves as a unit, and each frequency segment is coded according to the sequence from low to high, wherein the coding comprises the following steps:
the first step is as follows: according to the frequency value f to be expressed, determining the segment number FS where the frequency value f is located to obtain the quantization frequency QF FS ，QF FS ＝SF 7 ×10 -7 Wherein, SF 7 Is the frequency band starting frequency;
the second step: quantizing the frequency value, expressing the quantized result in hexadecimal system, retaining 7 effective bits and less than 7 effective bits, and adding 0 to obtain the quantized frequency value f Q ；
The third step: and merging the frequency band code and the frequency quantization value, and increasing a frequency signal flag word 0x46 to obtain the final frequency code.
(3) And (3) subdividing and decoding the airspace, namely the space grid coding process is as follows: the longitude and latitude of the earth are expanded for three times, from 360 degrees multiplied by 180 degrees to 512 degrees multiplied by 512 degrees, from 1 degree to 64', from 1' to 64', and 2n recursive subdivision is realized on the basis, so that a 32-grade longitude and latitude integer grid series reaching centimeter-grade precision is obtained;
(4) And (3) carrying out subdivision decoding on the energy domain, namely the power grid coding process comprises the following steps:
the power coding is also based on the segmented expression, namely, the power range of 1aW to 100MW is averagely divided into 13 segments by taking 100 octaves as a unit, and each power segment is coded according to the sequence from low to high, wherein the coding comprises the following steps:
the first step is as follows: according to the power value p to be expressed, determining the frequency segment number PS where the power value p is located to obtain a quantization power unit QP PS ，QP Ps ＝SP 2 ×10 -2 Wherein, SP BP Starting power for the power segment;
the second step is that: quantizing the power value, expressing the quantized result with hexadecimal system, retaining 4 effective bits and less than 4 bits, and supplementing 0 to obtain quantized power value p Q ；
The third step: combining the power segment code and the power quantization value, and increasing a power information flag word 0x50 to obtain a final power code;
(5) Subdividing the modulation domain
Electromagnetic signals in a space are radar or communication signals, the signals are continuous waves or impulse sequences, the modulation mode is divided into analog modulation, 0 and digital modulation, the modulation usually converts three parameters of amplitude, phase and frequency, and then the modulation information coding design is as follows: encoding the 1 st bit to distinguish radar and communication signals, the second bit to distinguish continuous signals and pulse signals, the 3 rd bit to distinguish analog modulation and digital modulation, and the 4 th and 5 th bits to distinguish frequency modulation, amplitude modulation, phase modulation and other types of modulation modes; the 6 th to 16 th bits determine the specific modulation modes under different signal pattern types;
(6) Subdivision coding of polarization domain
The polarization mode is divided into linear polarization, circular polarization and elliptical polarization, and the circular polarization and the elliptical polarization are divided into left-hand circular polarization and right-hand circular polarization, left-hand elliptical polarization and right-hand elliptical polarization;
for linear polarization, the polarization mode can be uniquely determined by determining the polarization angle; for circular polarization and elliptical polarization, not only the left-hand polarization and the right-hand polarization need to be distinguished, but also the polarization angle needs to be quantitatively expressed, and a classification and quantitative expression combined expression method can be adopted
Therefore, the polarization mode is distinguished by placing a 2-bit binary code at the beginning of the code: linear polarization, left-hand circular polarization, right-hand circular polarization, 7-bit binary codes determine horizontal direction angles, 5-bit binary codes determine vertical direction angles, the horizontal direction angles and the vertical direction angles are sequentially spliced, 14-position binary codes are totally used, namely, a polarization mode can be uniquely determined, in order to be beneficial to computer storage, 2 bits are added on the basis of 14-bit codes and are set to 00, and 16 bits are totally formed into 2 bytes.
Preferably, the time domain association is as follows:
given a spatial location, the correlation of electromagnetic energy over a period of time for a particular frequency is essentially a matter of calculating the mean of the electromagnetic energy over the observation period, which can be expressed as:
wherein T is an observation period; t is Δ For quantization time, N is the quantized value of T,
for the average power over the observation period, p (t) is the instantaneous power distribution; p is a radical of Q (nT Δ ) Is p (nT) Δ ) The quantized value of (a).
Preferably, the frequency domain correlation is as follows:
given a spatial location, at a particular time, the correlation of electromagnetic energy over a range of frequencies, in essence, computes the problem of averaging electromagnetic energy over the observed frequency bandwidth, which can be expressed as:
wherein F is the observation frequency bandwidth; f Δ Is a quantized frequency; m is the quantized value of F;
is the average power within the observation frequency bandwidth F; p (f) is the power density distribution; p is a radical of Q (mF Δ ) Is p (mF) Δ ) The quantized value of (a).
Preferably, the spatial correlation is as follows:
given a frequency, the correlation of electromagnetic energy over a spatial range at a particular time is essentially a matter of calculating the mean of the electromagnetic energy in the observation space, which can be expressed as:
in the formula, V is an observation space; v Δ Is a quantization space; i, J and K are quantized values of V;
is the average power in the observation space V; p (v) is the power spatial distribution; p is a radical of Q (iV Δ ，jV Δ ，kV Δ ) Is p (iV) Δ ，jV Δ ，kV Δ ) The quantized value of (a).
Preferably, in step 3, the radar coverage calculation process is as follows:
by adopting a stereo subdivision data model, the detection range of a radar and the coverage range of topographic data can be equally divided and differentiated, complex calculation is converted into intersection operation of subdivision volume element coding sets, and the calculation flow is as follows:
1) Calculating the maximum radar detection range R without terrain influence max ；
In free space, the radar is at a determined pitch angle θ, azimuth angle, when no environmental effects are considered
The detection range of (c) is determined by the radar equation:
in the formula, P t To transmit power, P r Is the received power; f t Is the directional pattern propagation factor of the transmitting antenna to the target; f r Is the directional pattern propagation factor of the receiving antenna and the target; g t Is the transmit antenna power gain; g r Is the receive antenna power gain; σ is the cross-sectional area of the radar target; λ is the radar wavelength; according to the radar basic parameters and the radar equation, the radar pitch angle theta is calculated i (i is more than or equal to 1 and less than or equal to m, m is sampling number of pitch angle) and azimuth angle
J is more than or equal to 1 and less than or equal to n, and n is the sampling number of the azimuth angle, so as to obtain the detection range of the radar;
2) Selecting a proper subdivision level according to the requirement precision and the detection range without influence according to the principle of stereo subdivision, and converting the detection range into a code set of the same level
3) Loading terrain data near the detection range, and converting the terrain data into a coding set
4) Performing intersection operation on the two code sets, wherein the intersection is the range blocked by the terrain
The invention has the beneficial effects that:
the invention is based on a gridded electromagnetic environment data field, adopts a coding algebra operation system, and develops two types of electromagnetic environment application research: the electromagnetic radiation source propagation path calculation and electromagnetic information data three-dimensional presentation technology is adopted, so that an electromagnetic environment information gridding space system is constructed, the calculation efficiency of an electromagnetic environment is greatly improved, and the expression form of the electromagnetic environment is enriched.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a representation of an electromagnetic information space characterization feature;
FIG. 2 is a schematic diagram of GeoSOT time trellis coding;
FIG. 3 illustrates frequency range segmentation and coding in frequency subdivision coding;
FIG. 4 is a power range segmentation and coding in power subdivision coding;
FIG. 5 is a schematic view of polarization angle division;
FIG. 6 is a schematic diagram of the electromagnetic multi-domain information tensor storage logic;
FIG. 7 is a schematic storage diagram of a multi-domain grid Zhang Lianghua for electromagnetic information;
FIG. 8 is a process of visualization of data of an electromagnetic environment data field;
FIG. 9 is an electromagnetic environment data field mapping framework.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention.
Electromagnetic environment information space characterization characteristic and grid organization mechanism research
The electromagnetic environment is the data sum of signal characteristics and signal density for all frequency devices in the domain of action. The method is one of main media for spatial information dependence, and most of information acquisition and transmission are completed in the field. With the continuous development and breakthrough of electronic technology, electronic devices are widely applied, the data density of the electromagnetic environment is higher and higher, the patterns are more and more complex and changeable, and the data information contained in the formed information space is extremely numerous and complex.
On the one hand, for such an information space, it is necessary to perform inductive analysis on spectrum information existing in the space on the basis of researching electromagnetic wave distribution characteristics, and form a complete spectrum characterization characteristic with application requirements as a background, so that continuous, silent and intangible electromagnetic environment data becomes a discrete and digitized information space. On the other hand, in a huge electromagnetic environment data space, a data structure which is favorable for real-time calculation and analysis is formed by organizing data in a multistage manner on the basis of a geographic information environment.
The embodiment specifically provides an electromagnetic environment information characterization and organization method of an electromagnetic multi-domain grid model, which includes the steps of 1: firstly, carrying out multi-scale division on hollow domain information in a six-domain characterization model of the electromagnetic environment by adopting a GeoSOT-3D space grid subdivision framework, then discretizing six-domain characterization by adopting a geographic space grid division concept, designing a corresponding coding mode, and forming an electromagnetic multi-domain grid together with an airspace grid, wherein a single multi-domain grid is used as a basic unit of electromagnetic environment data organization;
step 2: designing a corresponding electromagnetic information multi-domain grid storage structure based on the constructed electromagnetic multi-domain grid, and realizing the structure as a physical layer for data organization and storage;
and step 3: based on the constructed electromagnetic multi-domain grid, a coding algebra operation system is adopted to calculate the propagation path of the electromagnetic radiation source and the coverage area of the radar, and the electromagnetic data obtained by calculation or measurement is subjected to true three-dimensional expression with selectable scale.
In step 1, in the information society, because the electronic information equipment is not only huge in quantity, complex in system, diverse in variety, but also wide in frequency application, electromagnetic signals in the space are very dense, and a very complex electromagnetic environment is formed. In a certain space, the complex electromagnetic environment is composed of electromagnetic signals with various distribution numbers, complex patterns, dense overlapping and dynamic overlapping of time domain, frequency domain, space domain, energy domain and modulation domain, thereby presenting various expression forms on different domains. As shown in fig. 1.
The change is expressed in the time domain and is dynamic. In the social environment, only a small amount of natural electromagnetic signals exist, and a large amount of electromagnetic signals are generated under artificial control. Therefore, the amount, kind and density of the generated electromagnetic signals will vary with time at different times and different places, and the variation is difficult to predict effectively.
The spectrum is shown to be infinitely wide in the frequency domain, with a dense pattern. The frequency spectrum is the expression form of the electromagnetic signal in the frequency domain, on one hand, due to the rapid development of the information technology and the large use of various different frequency-using devices, the frequency spectrum occupied by the electromagnetic signal is wider and wider, and almost all the frequency bands of the electromagnetic signal are covered. On the other hand, due to the influence of factors such as atmospheric attenuation, ionospheric reflection and absorption, the applicable spectrum range is limited in the actual application process, so that electromagnetic signals are densely overlapped in a local frequency interval.
The method has the advantages of ubiquitous appearance in the airspace and universality. The electromagnetic wave itself has widely distributed characteristics, in space it is invisible and untouchable, but it is really present in every location in space, including different domains of land, sea, air, sky and even saibo.
The signal energy density is not uniform in the energy domain. Under the influence of electromagnetic wave propagation factors, signal power of electromagnetic signals is continuously reduced due to the influence of adverse conditions such as increase of propagation distance, absorption attenuation of air and moisture and the like, and a terminal receiving antenna has to have large enough directional gain and sensitivity to receive communication signals and perform subsequent signal processing. The whole earth is covered by electromagnetic signals, signals of various types and systems such as communication signals, navigation signals, measurement and control signals and the like are interwoven together, and main lobe and side lobe beams of a pair of antennas are added, so that the signal energy density of the whole electromagnetic environment is uneven, and the whole electromagnetic environment falls down and fluctuates.
The representation in the modulation domain is a complex modulation scheme. Conventional communication modulation mainly includes spread spectrum modulation techniques and narrowband modulation techniques like Direct Sequence Spread Spectrum (DSSS), frequency Hopping (FHSS), QPSK, MSK, and QAM. With the development of the technology level, the high-speed digital processing technology brings new vitality to the traditional voice coding, data coding and data transmission, and various novel modulation technologies and multiple access technologies are widely applied to communication.
The time domain, the frequency domain, the space domain, the energy domain and the modulation domain respectively reflect different characteristics of the electromagnetic environment, and together form a complete electromagnetic environment. The time domain characteristics can reflect the number of radiation sources and the on-off time; the frequency domain characteristics can represent the frequency spectrum occupancy of the electromagnetic environment; spatial characteristics reflect the spatial distribution of the radiation source; the energy domain characteristics show the change of the relative position of a radiation source-a receiver; the modulation domain embodies the modulation scheme of the electromagnetic signal.
The electromagnetic environment information can be respectively described by a plurality of domains of time domain, frequency domain, space domain and energy domain, but the information of the domains is continuous information which is not beneficial to computer storage and processing, so that the electromagnetic environment information represented by the time domain, the frequency domain, the space domain, the energy domain and the like needs to be discretized and digitalized, and the discretization and the digitization can be realized by subdividing and coding the information.
Discretizing time domain, frequency domain, space domain and energy domain data of the electromagnetic environment in each grid in a coding mode, and taking a multi-domain grid as a basic unit, wherein the coding process comprises the following steps:
(1) The time domain is subdivided and decoded as follows:
adopting GeoSOT time grid coding, discretizing time into time intervals with different lengths, and endowing unique binary codes to ensure that the time is discretized into time periods with lengths so as to form a time discretization frame in the electromagnetic environment information organization; as shown in fig. 2.
(2) And (3) carrying out subdivision decoding on the frequency domain, namely the frequency subdivision decoding process is as follows:
the frequency decoding is based on the segmented expression, the frequency range of 0.1Hz to 1PHz is divided into 16 segments by taking 10 octaves as a unit, and each frequency segment is encoded from low to high, as shown in fig. 3, the encoding comprises the following steps (taking f =1.234567MHz as an example):
the first step is as follows: determining the segment number FS =7 of the frequency value f =1.234567MHz to be expressed, and obtaining the quantization frequency QF FS ，QF FS ＝SF 7 ×10 -7 ＝10 6 ×10 -7 =0.1, wherein, SF 7 Is the frequency band starting frequency;
the second step: quantizing the frequency value, expressing the quantized result with hexadecimal system, retaining 7 effective bits and less than 7 effective bits, and adding 0 to obtain the quantized frequency value
The third step: and merging the frequency band code and the frequency quantization value, increasing the frequency signal flag word 0x46, and finally obtaining the frequency code of 1.234567MHz as 0x4670BC6146.
The frequency coding scheme has the following remarkable advantages:
1) Each frequency band has the same 10 octave bandwidth no matter the frequency is high or low; 2) Has the same frequency expression precision (as shown in Table 1) in the whole frequency domain range, namely 10 -7 Magnitude; 3) The ten-bit one-dimensional hexadecimal frequency coding has simple conversion and high retrieval and correlation efficiency.
TABLE 1 frequency division and segmentation coding
(3) And (3) subdividing and decoding the airspace, namely the space grid coding process is as follows: the longitude and latitude of the earth are expanded for three times, the longitude and latitude are expanded from 360 degrees multiplied by 180 degrees to 512 degrees multiplied by 512 degrees, 1 degree is expanded to 64',1' is expanded to 64', and 2n recursive subdivision is realized on the basis, so that a longitude and latitude integer grid series with 32-level precision reaching centimeter level is obtained; each GeoSOT grid is endowed with a unique code, the grid codes keep the dimensions of integer degree, minute and second and have four coding forms of four-system 1-dimensional codes, two-system 2-dimensional codes or decimal 2-dimensional codes; a specific hierarchy in the GeoSOT grid is selected as a basic tuple, any specified geographic grid based on longitude and latitude subdivision can be formed in a polymerization mode, and a globally unique code is automatically given to a surface patch of the polymerization grid.
(4) And (3) carrying out subdivision decoding on the energy domain, namely the power grid coding process comprises the following steps:
the power coding is also based on the segmented expression, that is, the power range of 1aW to 100MW is divided into 13 segments on the average in units of 100 octaves, and each power segment is coded in the order from low to high (as shown in fig. 4), and the coding includes the following steps (for example, p =345 nW):
the first step is as follows: according to the power value p required to be expressed, the number PS =5 of the frequency band where the power value p is located is determined, and a quantization power unit QP is obtained PS ，QP Ps ＝SP 2 ×10 -2 ＝10 -8 ×10 -2 ＝10 -10 Wherein, SP BP Starting power for the power section;
the second step is that: quantizing the power value, expressing the quantized result in hexadecimal system, retaining 4 effective bits and less than 4 effective bits, and adding 0 to obtain quantized power value
The third step: inserting power segment code 5 before the first bit of the power quantization value, and inserting power flag word 0x50 before the power segment code, and finally obtaining 345nW frequency code of 0x5050D80.
The power coding scheme has the remarkable advantages that:
1) Each power stage has the same 100 times power Cheng Kuandu (as shown in table 2) regardless of power level;
2) The power expression precision is better than 10 < -2 > (better than 0.05 dB) in the whole power domain range;
3) Seven-bit one-dimensional hexadecimal power coding, simple conversion and high retrieval and correlation efficiency.
TABLE 2 Power segment partitioning and segmentation coding
(5) Subdividing the modulation domain
Modulation method of communication signal:
the signal modulation mode comprises the following steps: AM, FM, ASK, FSK, PSK, BPSK, MSK, QAM, QPSK, QQPSK, CPFSK, SSB, USB, mark X II, modes
Common modulation mode
Radar signal pattern
Continuous wave signal, normal pulse signal, pulse Doppler signal, pulse repetition frequency spread signal, pulse repetition frequency hopping signal, pulse repetition frequency sliding signal, pulse repetition frequency dithering signal, frequency agility signal, frequency diversity signal, pulse compression signal, pulse coding signal, etc
The main electromagnetic signals in space are radar or communication signals, the signals are continuous waves or shock sequences, the modulation mode is divided into analog modulation, 0 and digital modulation, and the modulation generally converts three parameters of amplitude, phase and frequency. Therefore, the following modulation information coding scheme can be designed: coding a 1 st bit to distinguish radar and communication signals, a second bit to distinguish continuous signals and pulse signals, a 3 rd bit to distinguish analog modulation and digital modulation, and a 4 th bit and a 5 th bit to distinguish frequency modulation, amplitude modulation, phase modulation and other types of modulation modes; bits 6-16 determine the specific modulation scheme under different signal pattern classes.
(6) Subdivision coding of polarization domain
At any fixed point in space, the law of the change of the electric field vector along with time is called as the mode of electromagnetic wave polarization.
The polarization modes include linear polarization, circular polarization and elliptical polarization, and the circular polarization and the elliptical polarization include left-hand circular polarization, right-hand circular polarization, left-hand elliptical polarization and right-hand elliptical polarization.
For linear polarization, the polarization mode can be uniquely determined by determining a polarization angle; for circular polarization and elliptical polarization, not only left-hand polarization and right-hand polarization need to be distinguished, but also polarization angles need to be quantitatively expressed, so that an expression method combining classification and quantitative expression can be adopted.
As shown in FIG. 5, the polarization angle can be expressed by defining the horizontal direction angle θ ∈ [0 DEG to 360 DEG ], and the vertical direction angle α ∈ [0 DEG to 90 deg ]. Since the polarization angle affects the efficiency of the antenna energy reception, it is generally considered that the energy reception loss is acceptable within 10%, and therefore the accuracy of the polarization angle Δ =3 ° (better than 3 °) can be determined accordingly. I.e., θ ∈ [ 0-120 Δ ], α ∈ [ 0-30 Δ ], bits are conveniently halved, where θ and α are expanded to 384 ° and 96 °, i.e., 128 Δ and 32 Δ, respectively.
Therefore, the polarization mode is distinguished by placing a 2-bit binary code at the beginning of the code: linear polarization, left-hand circular polarization, right-hand circular polarization, 7-bit binary codes determining horizontal direction angles, 5-bit binary codes determining vertical direction angles, and sequentially splicing, wherein 14-position binary codes are totally used, and then the polarization mode can be uniquely determined. But for computer storage, 2 bits (set as 00) are added on the basis of 14-bit coding, and 16 bits form 2 bytes.
The electromagnetic environment data is basically characterized in that the electromagnetic environment data is constantly changed in three domains of a time domain, a frequency domain and a space domain, the three spaces of the time domain, the frequency domain and the space domain are relatively independent, and the data association of any time period, any frequency band and any space in the electromagnetic environment is realized by performing association processing on the time domain, the frequency domain and the space domain.
(1) Time domain correlation of electromagnetic information
Given a spatial location, the correlation of electromagnetic energy over a period of time for a particular frequency is essentially a matter of calculating the mean of the electromagnetic energy over the observation period, which can be expressed as:
in the formula, T is an observation time interval; t is a unit of Δ For quantization time, N is the quantized value of T,
for the average power over the observation period, p (t) is the instantaneous power distribution; p is a radical of Q (nT Δ ) Is p (nT) Δ ) The quantized value of (a).
(2) Frequency correlation of electromagnetic information
Given a spatial location, at a particular time, the correlation of electromagnetic energy over a range of frequencies, essentially a problem of calculating the mean of electromagnetic energy over the observed frequency bandwidth, can be expressed as:
wherein F is the observation frequency bandwidth; f Δ Is a quantized frequency; m is the quantization value of F;
is the average power within the observation frequency bandwidth F; p (f) is the power density distribution; p is a radical of Q (mF Δ ) Is p (mF) Δ ) The quantized value of (a).
(3) Spatial correlation of electromagnetic information
Given a frequency, the correlation of electromagnetic energy over a spatial range at a particular time is essentially a matter of calculating the mean of the electromagnetic energy in the observation space, which can be expressed as:
in the formula, V is an observation space; v Δ Is a quantization space; i, J and K are quantized values of V;
is the average power in the observation space V; p (v) is the power spatial distribution; p is a radical of Q (iV Δ ，jV Δ ，kV Δ ) Is p (iV) Δ ，jV Δ ，kV Δ ) The quantized value of (a).
The electromagnetic environment can be characterized by the characteristics of domains such as time domain, frequency domain, space domain, energy domain and the like, N attribute information or characteristics of the domains form an N-dimensional space, electromagnetic environment data in each multi-domain grid becomes one point of the characteristic space, and the electromagnetic environment data of thousands of multi-domain grids form an electromagnetic environment data field in the characteristic space.
Each data object in an electromagnetic environment data field contributes to the potential at any point in the field, and the magnitude of the contribution is proportional to the mass of the object and inversely proportional to the square of the distance between the two. Assume that the space Ω has n attribute objects { x }in total 1 ，X 2 ，...，X n }, object x i Has a mass of m i Let x i Representing the position of the object, x in the data field i The potential function at x is:
wherein, | | x-x i Is x to x i The distance of (a); σ is an influence factor, and generally, σ =2. For the
x j At x i Potential energy in the data field of
Comprises the following steps:
the space Ω contains a plurality of objects, all of which together form the potential field of Ω. The potential at y in Ω is expressed as:
the method comprises the steps of dividing an electromagnetic space into discrete volume data structures according to a mesh division idea, discretizing time domain, frequency domain, space domain and energy domain data of an electromagnetic environment in each mesh in a coding mode, and using multi-domain meshes as basic units, so that the problem that space information and electromagnetic attribute information are correlated is solved, multi-dimensional electromagnetic information data are displayed three-dimensionally based on an electromagnetic environment data field, and the relation among the multi-domain data of the electromagnetic environment can be researched by means of a data field theory.
Electromagnetic transforms characterize a data field as electromagnetic data in different domains and dimensions. The data organization of the electromagnetic environment data field is a data model for researching how the data of the electromagnetic environment data field is effectively organized based on a geographical conversion system, so that the data is scientifically and efficiently stored, applied and analyzed. The data model generally has a raster data model and a vector data model. The grid data model is a discretized electromagnetic space covering the entire continuous space in multiple dimensions. The raster data model is the simplest and most intuitive data model, which divides the electromagnetic space into uniform meshes, each serving as a pixel.
The vector data model represents various geographic elements as accurately as possible by recording basic elements such as points, lines, surfaces and the like in the form of coordinate points. The coordinate space represented by the vector data is continuous, and thus any position, length, area, etc. of the geographic space can be precisely defined. The accuracy of vector data is limited mainly by the accuracy of the digitization settings and the length of the numeric record word. The data structure records the coordinates of the sampling points on the basis of the geometric space coordinates, so that the target can be identified accurately. The data model can store complex data with minimum data redundancy, has the characteristics of high data accuracy, small storage space and the like compared with a grid structure, and is an efficient graph data structure.
In an electromagnetic environment data field, electromagnetic waves have vector characteristics, and geographic environments need to be processed in a rasterization mode, so that position data and attribute data of the electromagnetic environment data field do not have consistency, and data organization needs to take both into consideration. Such data may be managed by file-relational database mixture management, full-relational management, object-relational database management, or the like.
In step 2, a multi-domain grid is used as a basic unit for organizing electromagnetic data, namely, the electromagnetic space is divided into a discrete tensor data structure according to the multi-domain grid. Specifically, each type of electromagnetic data coding and addressing unit needs to correspond to a globally unique GeoSOT3D + time code, and the tensor coding basic model structure designed by the invention is shown as a table and is composed of three parts, namely, a GeoSOT geographic code, a time code and an electromagnetic feature code.
| GeoSOT geocoding | Time coding | Electromagnetic signature coding |
Tensor data coding model
The electromagnetic tensor storage structure can be regarded as high-order expansion of a GeoSOT subdivision frame, and meanwhile, the electromagnetic tensor storage structure is a data model aiming at a local space-time range and a specific attribute interval. The tensor model has the characteristics of continuous indexing, high-order expansion and the like, so that the data model is more suitable for association and management of electromagnetic high-dimensional data, and supports electromagnetic calculation and information mining in a region to lay a good organization foundation.
If the data model is embodied as a system, as shown in fig. 6-7, it can be divided into a user layer, a model layer, and an application layer as shown. The user layer needs to determine the representation dimension, range and level of the electromagnetic data, disassemble and input original data, and simultaneously can input operation instructions such as indexing according to the dimension, inquiring according to attributes, updating according to the block and the like; the model layer comprises a GeoSOT tensor data model and a tensor coding addressing auxiliary unit, data model construction and grid association are carried out on original data input of a user, and each grid is associated with a corresponding coding value and corresponding electromagnetic attribute information; the application layer is used for performing data operation according to the requirements and instructions of users, and due to the regular organization of the GeoSOT tensor data model, tensor analysis and operation of various data can be provided by adopting the characteristics and the principle of tensor analysis, and the calculation and use efficiency of the data is improved.
In step 3, the propagation path trellis is computed: and deducing various electromagnetic propagation paths under the environmental condition of the monitoring area by combining three-dimensional geographic information and a building model of the spatial area, and calculating multipath and shielding caused by terrain and buildings. In order to ensure the high efficiency and real-time performance of the operation, a GPU parallel operation mode is adopted, and the propagation paths of the radiation sources in all directions are calculated. In the path deduction process, a model is organized according to three-dimensional grid coded data, any entity of an electromagnetic space is divided in a user-defined mode according to actual requirements, and then a path is directly deduced according to a continuous coding calculation mode.
The radar coverage calculation process is as follows:
by adopting a stereo subdivision data model, the detection range of a radar and the coverage range of topographic data can be equally divided and differentiated, complex calculation is converted into intersection operation of subdivision volume element coding sets, and the calculation flow is as follows:
1) Calculating the maximum radar detection range R without terrain influence max ；
In free space, the radar is at a determined pitch angle θ, azimuth angle, when any environmental effects are not considered
The detection range of (c) is determined by the radar equation:
in the formula, P t To transmit power, P r Is the received power; f t Is the directional pattern propagation factor of the transmitting antenna to the target; f r Is the directional pattern propagation factor of the receiving antenna and the target; g t Is the transmit antenna power gain; g r Is the receive antenna power gain; σ is the cross-sectional area of the radar target; λ is the radar wavelength; according to the radar basic parameters and the radar equation, the radar pitch angle theta is calculated i (i is more than or equal to 1 and less than or equal to m, m is sampling number of pitch angle) and azimuth angle
J is more than or equal to 1 and less than or equal to n, and n is the sampling number of the azimuth angle, so as to obtain the detection range of the radar;
2) Selecting a proper subdivision level according to the requirement precision and the detection range without influence according to the principle of stereo subdivision, and converting the detection range into a code set of the same level
3) Loading the topographic data near the detection range and obtaining the topographic dataConversion into coded sets
4) Performing intersection operation on the two code sets, wherein the intersection is the range blocked by the terrain
The processing algorithm does not need to adopt a ray method to calculate the intersection operation of the ray and the surface in the three-dimensional space, namely, the step of simultaneous vector equations is omitted. The algorithm is related to the parameters of the actual radar only in the first step of calculating the detection range, in the subsequent process, the calculation of subdivision volume element codes is adopted, the coding calculation is bit operation in a computer, and the algorithm complexity o (NlogN) is realized. When the radar basic parameter changes dynamically, only the R of the first step needs to be changed max Namely, the calculation is convenient.
Multidimensional electromagnetic information data stereo presentation technology based on electromagnetic environment data field
The multidimensional electromagnetic information data three-dimensional visualization technology is to perform visualization-based mapping on multi-domain information of an electromagnetic environment to form a visualized data field, and draw the visualized data field on a screen in a scientific and intuitive manner, so that the spatial characteristics of the electromagnetic environment are presented. The core of the method lies in the drawing of electromagnetic environment data field data, wherein the electromagnetic environment data field drawing is to convert redundant data into visual graphs or images by establishing the mapping relation (transfer function) between discrete point data in an electromagnetic environment data field and three-dimensional geometric graphs. The electromagnetic environment data field data has the characteristics of multiple signal types, fuzzy distribution boundaries and complex internal details, specific attribute information of an electromagnetic environment needs to be described, and the overall characteristics and the internal details of an electromagnetic environment space need to be displayed.
The technology is based on the construction of an electromagnetic environment data field, a drawing algorithm is applied, three-dimensional geographic information is combined, drawing and real-time rendering of electromagnetic data are smoothly carried out, and an electromagnetic situation expression form with multi-resolution levels, multi-mode expression, multi-view integration and multi-data fusion is provided for information such as dynamic and static radiation source entities, equipment distribution and electromagnetic situations.
The multidimensional electromagnetic data visualization technology mainly solves three problems: the method comprises the steps of constructing the electromagnetic environment data field, three-dimensional visualization mapping, drawing and interactive display of the mapping process and the like, wherein the whole electromagnetic environment data field data visualization process is shown in fig. 8.
Electromagnetic environment data field data visualization is at the core of the overall process. The method solves the problem of how to convert discrete point data in an electromagnetic environment data field into a three-dimensional geometric figure for drawing. "mapping" means the selection and design of visualization schemes and visualization areas, i.e., the decision of what should be seen in the final image, how to represent interesting properties and features in the raw data in terms of shape, lightness, color and other attributes, and to interpret the various phenomena and laws implied in the data in the most efficient graphical representation.
The visual mapping comprises two aspects, namely visual scheme design which determines what should be seen in the final rendering interface and selection of shape, brightness, color and transparency; and secondly, graphic plotting, namely converting data, attributes and the like into images for display, wherein the images comprise observation transformation, scanning transformation, geometric transformation of the images, color quantization, dynamic plotting of the images and the like.
The electromagnetic environment data field drawing technology is used for converting discrete point data in an electromagnetic environment data field into a visualized graphic image, and the visualization scheme is configured as shown in fig. 9 below.
The optical visualization mapping maps the data values of the electromagnetic environment data field into different optical attribute parameters, and the direct volume rendering and surface rendering algorithms convert geometric figures and optical attributes into graphic images which can be displayed by hardware equipment. The mixed rendering is to mix surface rendering and volume rendering for use according to visualization requirements in a virtual geographic environment to obtain a required display effect.
The above description is only for the purpose of illustrating the technical solutions of the present invention and not for the purpose of limiting the same, and other modifications or equivalent substitutions made by those skilled in the art to the technical solutions of the present invention should be covered within the scope of the claims of the present invention without departing from the spirit and scope of the technical solutions of the present invention.
Claims (7)
1. The method for representing and organizing the electromagnetic environment information of the electromagnetic multi-domain grid model is characterized by comprising the following steps of:
step 1: firstly, carrying out multi-scale division on hollow domain information in a six-domain characterization model of the electromagnetic environment by adopting a GeoSOT-3D space grid subdivision framework, then discretizing six-domain characterization by adopting a geographic space grid division concept, designing a corresponding coding mode, and forming an electromagnetic multi-domain grid together with an airspace grid, wherein a single multi-domain grid is used as a basic unit of electromagnetic environment data organization;
and 2, step: designing a corresponding electromagnetic information multi-domain grid storage structure based on the constructed electromagnetic multi-domain grid, and realizing the electromagnetic information multi-domain grid storage structure as a physical layer for data organization and storage;
and 3, step 3: based on the constructed electromagnetic multi-domain grid, a coding algebra operation system is adopted to calculate the propagation path of the electromagnetic radiation source and the coverage area of the radar, and the electromagnetic data obtained by calculation or measurement is subjected to true three-dimensional expression with selectable scale.
2. The method for characterizing and organizing electromagnetic environment information of the electromagnetic multi-domain grid model according to claim 1, wherein in step 1, the six-domain characterization includes time domain, frequency domain, space domain, energy domain and modulation domain characterization, and the basic characteristics of the electromagnetic environment data are continuously changed in three domains of time domain, frequency domain and space domain, the three spaces of time domain, frequency domain and space domain are relatively independent, and the data association of any time period, any frequency band and any space in the electromagnetic environment is realized by performing association processing on time domain, frequency domain and space domain.
3. The method for characterizing and organizing the electromagnetic environment information of the electromagnetic multi-domain grid model according to claim 2, wherein in step 2, the time domain, the frequency domain, the spatial domain, and the energy domain data of the electromagnetic environment in each grid are discretized by encoding, and the multi-domain grid is taken as a basic unit, and the encoding process is as follows:
(1) The time domain is subdivided and decoded as follows:
adopting GeoSOT time grid coding, discretizing time into time intervals with different lengths, and endowing unique binary codes to ensure that the time is discretized into time periods with lengths so as to form a time discretization frame in the electromagnetic environment information organization;
(2) And (3) carrying out subdivision coding on the frequency domain, namely the frequency subdivision decoding process comprises the following steps:
the frequency decoding is established on the basis of segmented expression, a frequency range from 0.1Hz to 1PHz is divided into 16 segments by taking 10 octaves as a unit, and each frequency segment is coded according to the sequence from low to high, wherein the coding comprises the following steps:
the first step is as follows: according to the frequency value f to be expressed, determining the segment number FS where the frequency value f is located to obtain the quantization frequency QF FS ，QF FS ＝SF 7 ×10 -7 Wherein, SF 7 Is the frequency band starting frequency;
the second step is that: quantizing the frequency value, expressing the quantized result with hexadecimal system, retaining 7 effective bits and less than 7 bits, and supplementing 0 to obtain frequency quantized value f Q ；
The third step: merging the frequency band code and the frequency quantization value, and increasing a frequency signal flag word 0x46 to obtain a final frequency code;
(3) And (3) subdividing and decoding the airspace, namely the space grid coding process is as follows: the longitude and latitude of the earth are expanded for three times, the longitude and latitude are expanded from 360 degrees multiplied by 180 degrees to 512 degrees multiplied by 512 degrees, 1 degree is expanded to 64',1' is expanded to 64', and 2n recursive subdivision is realized on the basis, so that a longitude and latitude integer grid series with 32-level precision reaching centimeter level is obtained;
(4) And (3) carrying out subdivision decoding on the energy domain, namely the power grid coding process comprises the following steps:
the power coding is also based on the segmented expression, namely, the power range of 1aW to 100MW is averagely divided into 13 segments by taking 100 octaves as a unit, and each power segment is coded according to the sequence from low to high, wherein the coding comprises the following steps:
the first step is as follows: according to the power value p to be expressed, determining the frequency segment number PS where the power value p is located to obtain a quantization power unit QP PS ，QP Ps ＝SP 2 ×10 -2 Wherein, SP BP Starting power for the power section;
the second step is that: quantizing the power value, expressing the quantized result with hexadecimal system, retaining 4 effective bits and less than 4 bits, and supplementing 0 to obtain quantized power value p Q ；
The third step: combining the power segment code and the power quantization value, and increasing a power information flag word 0x50 to obtain a final power code;
(5) Subdividing the modulation domain
Electromagnetic signals in a space are radar or communication signals, the signals are continuous waves or impulse sequences, the modulation mode is divided into analog modulation, 0 and digital modulation, the modulation generally converts three parameters of amplitude, phase and frequency, and then the modulation information coding design is as follows: encoding the 1 st bit to distinguish radar and communication signals, the second bit to distinguish continuous signals and pulse signals, the 3 rd bit to distinguish analog modulation and digital modulation, and the 4 th and 5 th bits to distinguish frequency modulation, amplitude modulation, phase modulation and other types of modulation modes; the 6 th to 16 th bits determine the specific modulation modes under different signal pattern types;
(6) Subdivision coding of polarization domain
The polarization mode is divided into linear polarization, circular polarization and elliptical polarization, and the circular polarization and the elliptical polarization are divided into left-hand circular polarization and right-hand circular polarization, left-hand elliptical polarization and right-hand elliptical polarization;
for linear polarization, the polarization mode can be uniquely determined by determining a polarization angle; for circular polarization and elliptical polarization, not only left-hand polarization and right-hand polarization need to be distinguished, but also polarization angles need to be quantitatively expressed, and a classification and quantitative expression combined expression method can be adopted
Therefore, the polarization mode is distinguished by placing a 2-bit binary code at the beginning of the code: linear polarization, left-hand circular polarization, right-hand circular polarization, 7-bit binary codes determine horizontal direction angles, 5-bit binary codes determine vertical direction angles, the horizontal direction angles are sequentially spliced, 14-position binary codes are used, namely, the polarization mode can be uniquely determined, in order to be beneficial to computer storage, 2 bits are added on the basis of 14-bit codes and are set to be 00, and 16 bits form 2 bytes.
4. The method for electromagnetic environment information characterization and organization of an electromagnetic multi-domain lattice model according to claim 3, characterized in that the time domain correlation is as follows:
given a spatial location, the correlation of electromagnetic energy over a period of time for a particular frequency is essentially a matter of calculating the mean of the electromagnetic energy over the observation period, which can be expressed as:
in the formula, T is an observation time interval; t is Δ For the quantization time, N is the quantization value of T,
for the average power over the observation period, p (t) is the instantaneous power distribution; p is a radical of Q (nT Δ ) Is p (nT) Δ ) The quantized value of (a).
5. The method of claim 3, wherein the frequency domain correlation is as follows:
given a spatial location, at a particular time, the correlation of electromagnetic energy over a range of frequencies, essentially a problem of calculating the mean of electromagnetic energy over the observed frequency bandwidth, can be expressed as:
wherein F is the observation frequency bandwidth; f Δ Is a quantized frequency; m is the quantized value of F;
is the average power within the observation frequency bandwidth F; p (f) is the power density distribution; p is a radical of Q (mF Δ ) Is p (mT) Δ ) The quantized value of (a).
6. A method of characterizing and organizing electromagnetic environment information of an electromagnetic multi-domain grid model according to claim 3, characterized in that the spatial correlation is as follows:
given a frequency, the correlation of electromagnetic energy over a spatial range at a particular time is essentially a matter of calculating the mean of the electromagnetic energy in the observation space, which can be expressed as:
in the formula, V is an observation space; v Δ Is a quantization space; i, J and K are quantized values of V;
is the average power within the observation space V; p (v) is the power spatial distribution; p is a radical of Q (iV Δ ，jV Δ ，kV Δ ) Is p (iV) Δ ，jV Δ ，kV Δ ) The quantized value of (a).
7. The method for characterizing and organizing electromagnetic environment information of an electromagnetic multi-domain mesh model according to claim 1, wherein in step 3, the radar coverage calculation process is as follows:
by adopting a stereo subdivision data model, the detection range of a radar and the coverage range of topographic data can be equally divided and differentiated, complex calculation is converted into intersection operation of subdivision volume element coding sets, and the calculation flow is as follows:
1) Calculating the maximum radar detection range R without terrain influence max ；
In free space, the radar is at a determined pitch angle θ, azimuth angle, when no environmental effects are considered
The detection range of (c) is determined by the radar equation:
in the formula, P t For the transmission power, P r Is the received power; f t Is the directional pattern propagation factor of the transmitting antenna to the target; f r Is the directional pattern propagation factor of the receiving antenna and the target; g t Is the transmit antenna power gain; g r Is the receive antenna power gain; σ is the cross-sectional area of the radar target; λ is the radar wavelength; according to the radar basic parameters and the radar equation, the pitch angle theta of the radar is calculated i (i is more than or equal to 1 and less than or equal to m, m is sampling number of pitch angle) and azimuth angle
J is more than or equal to 1 and less than or equal to n, and n is the sampling number of the azimuth angle, so as to obtain the detection range of the radar;
2) Selecting a proper subdivision level according to the requirement precision and the detection range without influence according to the principle of stereo subdivision, and converting the detection range into a code set of the same level
3) Loading terrain data near the detection range, and converting the terrain data into a coding set
4) Performing intersection operation on the two code sets, wherein the intersection is the range blocked by the terrain
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