CN108414994A - A kind of Ionospheric Parameters inverting based on wide-area distribution type shortwave net and a wide range of model reconstruction method - Google Patents
A kind of Ionospheric Parameters inverting based on wide-area distribution type shortwave net and a wide range of model reconstruction method Download PDFInfo
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- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
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Abstract
The present invention relates to a kind of Ionospheric Parameters invertings based on wide-area distribution type shortwave net and a wide range of model reconstruction method.The shortwave cooperative communication signal emitted in present invention synchronous acquisition net first；Then the signal quality received according to each website selects suitable receiving station, and estimate respectively it is each transmitting website to receiving station signal time delay；Then the delay data that each receiving station obtains is transmitted to center site server；It is finally finally inversed by current partial ionization layer parameter in the site server of center, and carries out a wide range of ionospheric model reconstruct accordingly.The present invention is without special design ionospheric detection equipment, current ionosphere cutoff frequency, bottom height and the parametric inversion of electron concentration maximum height can be realized and a wide range of ionospheric model of superjacent air space reconstructs, it can save and largely build a station, safeguard, managing and usage charges, the ionosphere model parameters of acquisition have important application value to short-wave signal high accuracy positioning and folded Clutter in Skywave Radars target following positioning.
Description
Technical Field
The invention belongs to the technical field of ionosphere detection and communication, and particularly relates to an ionosphere parameter inversion and large-range model reconstruction method based on a wide-area distributed short-wave network.
Background
The short-wave communication has the characteristics of simple equipment, mature hardware technology, flexible communication mode, long communication distance, difficult damage to a transmission medium of the communication medium which is transmitted through ionosphere refraction and the like, and is widely used in departments such as governments, military, diplomatic transaction, commerce and the like. However, the ionosphere is a nonlinear time-varying medium, and is affected by factors such as the sun and the earth magnetism, and the ionosphere has very complex characteristics such as "space-time-frequency-polarization", and has very important influence on the propagation of short-band electromagnetic waves therein, mainly manifested as effects such as refraction, dispersion, multimode, multipath, doppler, fading, loss, depolarization, and the like. Since the discovery of the ionosphere, people have begun to utilize the refractive properties of the ionosphere for long-distance over-the-horizon communication, and even the emerging sky-wave over-the-horizon radar. However, both short-wave communication or sky-wave radar and ground-wave radar need to know the state of the ionosphere in real time, and particularly in sky-wave radar target location tracking and short-wave radio direction finding positioning, current ionosphere model parameters need to be detected and acquired in real time.
At present, methods for detecting ionospheric parameters include ionospheric sag measurement, oblique measurement, and oblique return detection, which all require independent transceiver systems and information processing systems, and only obtain ionospheric state parameters of a certain point or a certain link, and to obtain ionospheric parameters over the entire territory, a large number of systems for ionospheric sag measurement, oblique measurement, and oblique return detection must be established, which requires a large amount of capital expenditure for station construction, maintenance, management, and use.
The invention provides an ionospheric parameter inversion and wide-range model reconstruction method based on a wide-area distributed short-wave network, which is a novel ionospheric inversion method for realizing wide-range ionospheric parameter inversion by utilizing transmitting and receiving equipment of the existing wide-area distributed short-wave network and a large number of self-transmitting and self-receiving short-wave signals in the network. Because the short wave networks are distributed in the whole country at present, a large number of short wave receiving and transmitting devices are arranged, and interconnection and intercommunication are realized, the invention provides an ionosphere parameter inversion and wide-range model reconstruction method based on the wide-area distributed short wave network, no equipment is required to be added, only an ionosphere inversion algorithm is added on the basis of the prior art, the ionosphere state modeling of the space above the soil of the country can be realized, the ionosphere parameter inversion and wide-range model reconstruction method is a byproduct of the prior short wave network, a basis can be provided for frequency selection of short wave communication and sky wave radar, ionosphere model parameters can be provided for short wave radio monitoring and positioning and sky wave radar target positioning, a reference can be provided for ionosphere environment prediction, and a large number of station building, maintenance, management and use expenses can be.
Disclosure of Invention
The invention provides a new ionosphere inversion method based on a wide-area distributed short-wave network, and based on the method, the ionosphere state parameters in a large range in the space above the territory can be obtained in real time only by adding an ionosphere inversion algorithm without adding any new equipment.
The technical problem of the invention is mainly solved by the following technical scheme:
the ionospheric parameter inversion and wide-range model reconstruction method based on the wide-area distributed short wave network is characterized by determining a wide-area distributed short wave network master station and a plurality of wide-area distributed short wave network substations, and the specific method comprises the following steps:
step 1: the method comprises the steps that a receiver of each station of a wide area distributed short wave network collects short wave cooperative communication signals synchronously transmitted in the network;
step 2: selecting a proper receiving station according to the quality of the signal received by each station;
and step 3: on the basis of a particle swarm method, the signals are operated to respectively estimate the sky wave propagation signal time delay from each transmitting station to each receiving station;
and 4, step 4: transmitting the time delay data acquired by each receiving station to a central station server;
and 5: performing a current local ionospheric parameter in a central station server based on an ionospheric model;
step 6: in a central station server, local ionosphere parameters are reconstructed into a large-range ionosphere model based on algorithms such as a neural network.
In the ionospheric parameter inversion and large-scale model reconstruction method based on the wide-area distributed short-wave network, the short-wave transceiver system in step 1 is the existing wide-area distributed short-wave network, and comprises a short-wave transmitting antenna and transmitter, a short-wave receiving antenna and receiver, an external GPS synchronization system, a central station server and an interconnected communication network among all transceiver stations.
In the ionospheric parameter inversion and wide-range model reconstruction method based on the wide-area distributed short-wave network, the signal-to-noise ratio required for the signal quality received by each station in step 2 is greater than 10dB, and it is required that a group of effective receiving stations is not less than 3, and propagation links are adjacent to each other as much as possible, and this is used as a condition for selecting a receiving station.
In the above method for ionospheric parameter inversion and wide-range model reconstruction based on wide-area distributed short-wave network, the current ionospheric parameters in step 5 include ionospheric cutoff frequency, base height, and maximum electron concentration height, wherein the ionospheric model may adopt a quasi-parabolic model, and the electron density is considered approximately as:
wherein N ise(r) is the electron concentration at r kilometers from the geocentric; n is a radical ofm＝fc 2(iii) 80.6 is the electron density maximum; f. ofcIs the critical frequency; r ismIs the maximum value N of the electron concentrationmThe height at which it is located; r isbIs the height of the bottom of the ionosphere; y ism＝rm-rbIs the ionosphere half thickness; in this model, only three parameters of the ionosphere, N, are knownm、rm、rbThe electron concentration at any height can be calculated;
under the single-layer QP model, the group path p 'of the signal with the detection frequency f and the transmission elevation angle β and the ground great circle distance D at the falling point can be accurately calculated, and the relationship between the group path p' and the ground distance D is as follows:
wherein,
F＝f/fc，
gamma is the incident angle of ray on the bottom of the ionization layer, the great circle distance D is determined because the positions of each transmitting station and each receiving station are known about the distributed short wave network, the transmitting elevation β can be obtained by an analytic method under the condition of known working frequency f, β is obtained by two values, one is a high elevation and the other is a low elevation, wherein the group path p 'corresponding to the high elevation is the high elevation ray, and the group path p' corresponding to the low elevation is the low elevation ray.
In the ionospheric parameter inversion and large-range model reconstruction method based on the wide-area distributed short-wave network, the short-wave signals are within the frequency range of 3-30 MHz.
In the ionospheric parameter inversion and large-range model reconstruction method based on the wide-area distributed short-wave network, in each receiving station in the short-wave network, a short-wave cooperative signal received by a short-wave antenna is output to a short-wave all-digital receiver and is subjected to signal acquisition; the collected data is interacted with the processing unit through the USB interface, and the sampled data is processed by the FPGA + DSP processing unit and then is networked with the central receiving station and is processed in a relevant mode.
In the ionospheric parameter inversion and large-range model reconstruction method based on the wide-area distributed short-wave network, each receiving and transmitting station in the short-wave network is synchronized based on the external GPS or the beidou receiver, the external GPS or the beidou receiver outputs pp1s signals with the accuracy within 20ns, and the synchronization signals output by the RS232 are synchronized with the processing unit.
Therefore, the invention has the following advantages: 1. the invention provides an ionosphere inversion method, which is carried out on the basis of a wide-area distributed short-wave network at present, can obtain a large-range ionosphere state parameter in real time only by adding an ionosphere inversion algorithm, does not need to add any new equipment, and is a byproduct of the existing short-wave network; 2. because the short wave networks are distributed in the whole country at present, a large number of short wave receiving and transmitting devices are arranged, and interconnection and intercommunication are realized, the ionosphere state model of the space above the soil of China can be obtained by the ionosphere parameter inversion and large-range model reconstruction method based on the wide-area distributed short wave network; 3. by utilizing the ionosphere parameter inversion and large-range model reconstruction method based on the wide-area distributed short-wave network, the method not only can provide basis for national military and civil short-wave communication, broadcasting and frequency selection of sky-wave radar, but also can provide ionosphere model parameters for short-wave radio monitoring and positioning, provide basis for maintaining air short-wave radio wave order, optimizing short-wave frequency resources, attacking illegal short-wave frequency spectrum use, and even provide ionosphere model parameters for sky-wave radar target positioning; 4. and providing a reference for wide-range ionospheric environment forecast.
Drawings
FIG. 1 is a schematic diagram of an ionospheric parameter inversion and large-scale model reconstruction method based on a wide-area distributed short-wave network;
FIG. 2 is a flow chart of a wide-area distributed short-wave network-based ionosphere parameter inversion and large-scale model reconstruction method provided by the invention;
FIG. 3 is a schematic diagram of reconstruction of a large-scale model based on ionosphere parametric inversion of a wide-area distributed short-wave network according to the present invention;
FIG. 4 is a single-node hardware block diagram of a wide-area distributed short-wave network-based ionosphere parameter inversion and wide-area model reconstruction method in the invention.
Detailed Description
The technical scheme of the invention is further specifically described by the following embodiments and the accompanying drawings.
Example (b):
fig. 1 shows a schematic diagram of an ionospheric parameter inversion and wide-range model reconstruction method based on a wide-area distributed short-wave network. Based on the existing short wave network transceiver and a large number of self-transmitting and self-receiving communication signals, the current local ionosphere parameter model is obtained based on an inversion algorithm under the assumption of an ionosphere model by obtaining the time delay of each signal in the ionosphere propagation. In the invention, each transceiver station only needs to be completely synchronous in time and can acquire signals of the same frequency at the same time, and other processing is digital signal processing at the back end through software.
Fig. 2 shows a flow chart of the ionospheric parameter inversion and wide-range model reconstruction method based on the wide-area distributed short-wave network provided by the invention. The method is realized by the following steps:
step 1: the method comprises the steps that a receiver of each station of a wide-area distributed short-wave network collects short-wave communication signals synchronously transmitted in the network;
step 2: according to the quality of signals received by each station, the signal-to-noise ratio of the signals is required to be greater than 10dB, and a proper receiving station is selected, each local ionosphere parameter inversion needs a group of effective receiving stations, the number of effective receiving stations is not less than 3, and propagation links are adjacent to each other as much as possible;
and step 3: respectively estimating the signal time delay received by each receiving station based on a particle swarm optimization method;
and 4, step 4: transmitting the time delay data obtained by each receiving station to a central station server;
and 5: and in the central station server, current ionosphere parameters such as an ionosphere cut-off frequency, a bottom height, an electron concentration maximum height and the like are inverted based on the ionosphere model. The ionosphere model can adopt a quasi-parabolic model, and the electron density is approximately considered as:
wherein N ise(r) is the electron concentration at r kilometers from the geocentric; n is a radical ofm＝fc 2(iii) 80.6 is the electron density maximum; f. ofcIs the critical frequency; r ismIs the maximum value N of the electron concentrationmThe height at which it is located; r isbIs the height of the bottom of the ionosphere; y ism＝rm-rbIs the ionosphere half thickness. In this model, only three parameters of the ionosphere, N, are knownm、rm、rbThe electron concentration at any height can be calculated.
Under the single-layer QP model, the group path p 'of the signal with the detection frequency f and the transmission elevation angle β and the ground great circle distance D at the falling point can be accurately calculated, and the relationship between the group path p' and the ground distance D is as follows:
wherein,
F＝f/fc，
the large circular distance D is determined since the positions of the transmitting and receiving stations are known for the distributed short wave network, the transmit elevation β can be analytically determined given the operating frequency f. generally, β is found to have two values, one is a high elevation and one is a low elevation, where the group path p 'for high elevation is a high elevation ray and the group path p' for low elevation is a low elevation ray.
Step 6: and in the central station server, reconstructing a large-range ionosphere model from the P local ionosphere parameters based on methods such as a neural network and the like. A schematic diagram of extensive ionospheric reconstruction is shown in figure 3.
Fig. 4 shows a hardware composition block diagram of a single receiving station of the ionospheric parameter inversion and wide-range model reconstruction method based on a wide-area distributed short-wave network. In a single receiving station, outputting a short wave cooperative signal received by a short wave antenna to a short wave full digital receiver and carrying out signal acquisition; the collected data is interacted with the processing unit (including data transmission and control command transmission) through the USB interface, and the sampled data is networked with the central receiving station and is processed in a relevant way after being processed by the FPGA + DSP processing unit. In order to obtain the time delay of the short wave signal passing through the ionosphere, time-frequency synchronization needs to be carried out on each receiving and transmitting station, therefore, each receiving station needs to be provided with a set of high-precision GPS/Beidou receiver, the external GPS or Beidou receiver outputs a pp1s signal with the precision within 20ns, and the signal is synchronized with the processing unit through a synchronization signal output by RS 232.
The invention is further explained by combining theoretical analysis:
setting ionospheric cut-off frequency, base height andthe maximum height of electron concentration is fc＝10.5MHz、rb6510km and rm6620km, the three receiving stations have a great circle distance D from the transmitting station1＝1080km、 D21740km and D32360km, the corresponding time delay tau of the radio wave group is obtained based on the ionosphere model1＝0.0038s、τ20.0060s and τ3The cut-off frequency, the base height and the maximum height of the electron concentration of the ionized layer obtained by the inversion algorithm are respectively f 0.0080sc＝10.5325MHz、rb6509.4km and rm6621.6 km. From the results, the ionosphere model parameters can be obtained by the ionosphere inversion method provided by the invention.
The specific embodiments described herein are merely illustrative of the spirit of the invention. Various modifications or additions may be made to the described embodiments or alternatives may be employed by those skilled in the art without departing from the spirit or ambit of the invention as defined in the appended claims.
Claims (7)
1. The ionospheric parameter inversion and wide-range model reconstruction method based on the wide-area distributed short wave network is characterized by determining a wide-area distributed short wave network master station and a plurality of wide-area distributed short wave network substations, and the specific method comprises the following steps:
step 1: the method comprises the steps that a receiver of each station of a wide area distributed short wave network collects short wave cooperative communication signals synchronously transmitted in the network;
step 2: selecting a proper receiving station according to the quality of the signal received by each station;
and step 3: on the basis of a particle swarm method, the signals are operated to respectively estimate the sky wave propagation signal time delay from each transmitting station to each receiving station;
and 4, step 4: transmitting the time delay data acquired by each receiving station to a central station server;
and 5: performing a current local ionospheric parameter in a central station server based on an ionospheric model;
step 6: in a central station server, local ionosphere parameters are reconstructed into a large-range ionosphere model based on algorithms such as a neural network.
2. The wide-area distributed short-wave network-based ionospheric parameter inversion and wide-range model reconstruction method according to claim 1, wherein: the short wave receiving and transmitting system in the step 1 is the existing wide area distributed short wave network, which comprises a short wave transmitting antenna and a transmitter, a short wave receiving antenna and a receiver, an external GPS synchronous system, a central station server and an interconnected communication network among all receiving and transmitting stations.
3. The wide-area distributed short-wave network-based ionospheric parameter inversion and wide-range model reconstruction method according to claim 1, wherein: the signal quality received by each station in step 2 requires that the signal-to-noise ratio is more than 10dB, and requires that a group of effective receiving stations is not less than 3, and propagation links are adjacent to each other as much as possible and are used as the condition for selecting the receiving stations.
4. The wide-area distributed short-wave network-based ionospheric parameter inversion and wide-range model reconstruction method according to claim 1, wherein: the current ionospheric parameters in step 5 include ionospheric cut-off frequency, base height, and maximum electron concentration height, wherein the ionospheric model may adopt a quasi-parabolic model, and the electron density is considered to be approximately:
wherein N ise(r) is the electron concentration at r kilometers from the geocentric; n is a radical ofm＝fc 2(iii) 80.6 is the electron density maximum; f. ofcIs the critical frequency; r ismIs the maximum value N of the electron concentrationmThe height at which it is located; r isbIs the height of the bottom of the ionosphere; y ism＝rm-rbIs the ionosphere half thickness;
under the single-layer QP model, the group path p 'of the signal with the detection frequency f and the transmission elevation angle β and the ground great circle distance D at the falling point can be accurately calculated, and the relationship between the group path p' and the ground distance D is as follows:
wherein,
gamma is the incident angle of the ray at the bottom of the ionization layer, the great circle distance D is determined because the positions of each transmitting station and each receiving station are known about the distributed short wave network, the transmitting elevation β is obtained by an analytical method under the condition of known working frequency f, and the obtained β has two values, one is a high elevation and the other is a low elevation, wherein the group path p 'corresponding to the high elevation is the high elevation ray, and the group path p' corresponding to the low elevation is the low elevation ray.
5. The wide-area distributed short-wave network-based ionospheric parameter inversion and wide-range model reconstruction method according to claim 1, wherein: the short wave signal is within the range of 3-30 MHz frequency band.
6. The wide-area distributed short-wave network-based ionospheric parameter inversion and wide-range model reconstruction method according to claim 1, wherein: in each receiving station in the short wave network, the short wave cooperation signals received by the short wave antenna are output to the short wave full digital receiver and are subjected to signal acquisition; the collected data is interacted with the processing unit through the USB interface, and the sampled data is processed by the FPGA + DSP processing unit and then is networked with the central receiving station and is processed in a relevant mode.
7. The wide-area distributed short-wave network-based ionospheric parameter inversion and wide-range model reconstruction method according to claim 1, wherein: each receiving and dispatching station in the short wave network is synchronized based on an external GPS or Beidou receiver, the external GPS or Beidou receiver outputs pp1s signals with the accuracy within 20ns, and the synchronization signals output by RS232 are synchronized with a processing unit.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109547131A (en) * | 2018-11-21 | 2019-03-29 | 河海大学 | A kind of simple and easy method for predicting extra large land short wave communication network outages |
| CN110954865A (en) * | 2019-11-05 | 2020-04-03 | 中国电波传播研究所（中国电子科技集团公司第二十二研究所） | Short wave time difference positioning method based on ionosphere information |
| CN111007489A (en) * | 2019-12-05 | 2020-04-14 | 武汉大学 | Buoy type ionized layer double-pass oblique return detection system and method |
| CN111050396A (en) * | 2019-12-24 | 2020-04-21 | 中国人民解放军32802部队 | Short wave broadcast transmitter positioning system based on ionosphere multi-station oblique measurement data fusion |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101860384A (en) * | 2010-04-23 | 2010-10-13 | 北京航空航天大学 | Ionosphere hybrid modeling method in short-wave ray tracing technique |
| CN103163533A (en) * | 2013-03-27 | 2013-06-19 | 武汉大学 | Seamless fusion expression and correction method of global navigation satellite system (GNSS) global and regional ionospheric delay |
| CN106342214B (en) * | 2011-12-12 | 2014-05-28 | 中国电子科技集团公司第二十二研究所 | A kind of ionosphere lateral scattering detection method |
| CN104360335A (en) * | 2014-11-21 | 2015-02-18 | 武汉大学 | Ionized layer parametric inversion method based on AIS target indication |
| CN106405589A (en) * | 2016-06-24 | 2017-02-15 | 西安科技大学 | Method and device for determining global ionized layer grid model |
| CN106842191A (en) * | 2017-01-13 | 2017-06-13 | 武汉工程大学 | A kind of acquisition methods of Ionospheric Parameters |
-
2018
- 2018-02-27 CN CN201810162876.4A patent/CN108414994A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101860384A (en) * | 2010-04-23 | 2010-10-13 | 北京航空航天大学 | Ionosphere hybrid modeling method in short-wave ray tracing technique |
| CN106342214B (en) * | 2011-12-12 | 2014-05-28 | 中国电子科技集团公司第二十二研究所 | A kind of ionosphere lateral scattering detection method |
| CN103163533A (en) * | 2013-03-27 | 2013-06-19 | 武汉大学 | Seamless fusion expression and correction method of global navigation satellite system (GNSS) global and regional ionospheric delay |
| CN104360335A (en) * | 2014-11-21 | 2015-02-18 | 武汉大学 | Ionized layer parametric inversion method based on AIS target indication |
| CN106405589A (en) * | 2016-06-24 | 2017-02-15 | 西安科技大学 | Method and device for determining global ionized layer grid model |
| CN106842191A (en) * | 2017-01-13 | 2017-06-13 | 武汉工程大学 | A kind of acquisition methods of Ionospheric Parameters |
Non-Patent Citations (6)
| Title |
|---|
| CHUNHUA JIANG 等: "Comparison of the Kriging and neural network methods for modeling foF2 maps over North China region", 《ADVANCES IN SPACE RESEARCH》 * |
| DE YU 等: "Ionospheric electron density profile estimation using commercial AM broadcast signals", 《JOURNAL OF ATMOSPHERIC AND SOLAR-TERRESTRIAL PHYSICS》 * |
| THOMAS A. CROFT 等: "Exact ray calculations in a quasi-parabolic ionosphere with no magnetic field", 《RADIO SCIENCE》 * |
| 总装备部电子信息基础部: "《太阳风暴对通信装备的影响与应对》", 30 September 2015, 国防工业出版社 * |
| 程黎 等: "基于粒子群优化的斜测电离图反演研究", 《中国电子科学研究院学报》 * |
| 陈洪普 等: "高频电离层传播轨迹研究", 《曲阜师范大学学报》 * |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109547131A (en) * | 2018-11-21 | 2019-03-29 | 河海大学 | A kind of simple and easy method for predicting extra large land short wave communication network outages |
| CN110954865A (en) * | 2019-11-05 | 2020-04-03 | 中国电波传播研究所（中国电子科技集团公司第二十二研究所） | Short wave time difference positioning method based on ionosphere information |
| CN111007489A (en) * | 2019-12-05 | 2020-04-14 | 武汉大学 | Buoy type ionized layer double-pass oblique return detection system and method |
| CN111007489B (en) * | 2019-12-05 | 2022-01-14 | 武汉大学 | Buoy type ionized layer double-pass oblique return detection system and method |
| CN111050396A (en) * | 2019-12-24 | 2020-04-21 | 中国人民解放军32802部队 | Short wave broadcast transmitter positioning system based on ionosphere multi-station oblique measurement data fusion |
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Application publication date: 20180817 |