Signal and data processing method for multi-base incoherent scatter radar

Abstract

The application belongs to the field of radio detection, and particularly relates to a signal and data processing method of a multi-base incoherent scatter radar, and aims to solve the problem that the conventional signal and data processing method is invalid for the multi-base incoherent scatter radar. The application comprises: dividing the detection distance range of the multi-base incoherent scatter radar beam into multiple detection distance gates, and calculating the signal autocorrelation functions of the detection distance gates; after time correction of the signals at the receiving station, determining the observation system equation constant based on the antenna gains of the transmitting station and the receiving station, the detection common height, and the radar transmitting power; fitting the signal autocorrelation functions according to the spectral ambiguity function, the plasma scattering theory power spectrum function, the observation system equation constant and the statistical error of the signal autocorrelation functions, and inversely obtaining the ionospheric parameters of the detection distance gates. The application is applied to the multi-base incoherent scatter radar, and effective ionospheric multi-parameter results are obtained.

Description

Technical Field

[0001] This application belongs to the field of radio detection, and specifically relates to a signal and data processing method for a multi-base incoherent scattering radar. Background Technology

[0002] The ionosphere, partially ionized by solar ultraviolet and X-ray radiation, lies at an altitude ranging from 60 km to 1000 km above the Earth's surface. As a transmission medium for radio waves, it is closely related to human activities, and its state directly affects communications, broadcasting, satellite navigation, and spacecraft operation. Detecting the physical parameters of the ionosphere and their spatiotemporal variations is crucial for understanding and mastering space environment information and conducting space weather research.

[0003] There are many methods for ionospheric detection. Ground-based detection uses ground equipment to transmit electromagnetic wave signals to obtain ionospheric information. Among them, incoherent scattering radar has the characteristics of high transmission power, large antenna gain, low noise and temperature, wide detection altitude range, and continuous observation time, and is considered to be the most advanced ground-based ionospheric detection equipment at present.

[0004] Multi-base incoherent scattering radar, through its separate transmit and receive design, can not only simultaneously acquire multiple ionospheric parameters but also provide the anisotropic characteristics of these parameters. However, since the target is an electron with an extremely small radius, the echo signal strength is very weak. At the same time, the volume scattering mechanism causes the signal to have random characteristics and spatiotemporal ambiguity. Therefore, signal and data processing are crucial to obtaining effective ionospheric detection results.

[0005] However, for multi-base incoherent scattering radar, due to the separate locations of the transmitting and receiving stations, the different signal transmission and reception positions lead to time deviations and changes in scattering volume. Conventional signal and data processing methods are no longer applicable, and it is impossible to obtain correct ionospheric multi-parameter results. Summary of the Invention

[0006] To address the aforementioned problems in the prior art, namely the failure of conventional signal and data processing methods due to the different geometric positions of the transmitting and receiving stations, this application proposes a signal and data processing method for multi-base incoherent scattering radar, comprising:

[0007] The detection range of the multi-base incoherent scattering radar beam is divided into multiple detection range gates, and the signal autocorrelation function of each detection range gate is constructed. The signal autocorrelation function is accumulated within the time resolution, and the statistical error of the signal autocorrelation function is calculated.

[0008] Based on the detection altitude of the transmit beam and the receive beam, the elevation angle of the transmit beam and the elevation angle of the receive beam, the time difference between the received signal between the receiving station and the transmitting station is obtained. The time difference is used to correct the signal of the receiving station.

[0009] After time correction of the signal from the receiving station, the constants of the observation system equations are determined based on the antenna gain of the transmitting and receiving stations, the height of the detection body, and the radar transmission power.

[0010] Based on the spectral ambiguity function, the power spectrum function of plasma scattering theory, and combined with the constants and statistical errors of the observation system equations, the autocorrelation function of the signal is fitted, and the ionospheric parameters of each detection range gate are obtained by inversion.

[0011] As a preferred implementation, the signal autocorrelation function of each detection range gate is constructed, including:

[0012] For any detection range gate, based on the original in-phase and quadrature signals acquired by the radar, the dot product of the time-delayed signal and the signal conjugate at different time delays is calculated, and the mean of the dot product with the same time delay is obtained as the value of that time delay. The autocorrelation function of the signal is constructed by calculating the values ​​of all time delays.

[0013] As a preferred implementation method, the process of obtaining statistical error includes:

[0014] Acquire a single frame sampling signal within the detection range, wherein the single frame sampling signal includes multiple detection range gates, and each detection range gate corresponds to a single pulse width sampling;

[0015] Within the multi-frame sampled signal included in the time resolution, the standard deviation of the autocorrelation function of the signal corresponding to all detection range gates in each frame sampled signal is obtained after incoherent accumulation and used as the statistical error.

[0016] As a preferred embodiment, obtaining the time difference of the received signal between the receiving station and the transmitting station includes:

[0017] ;

[0018] Where dt represents the time difference and c represents the speed of light. Indicates the altitude of the probe. Indicates the elevation angle of the transmitted beam. Let q represent the elevation angle of the receiving beam of the p-th receiving station, and q represent the total number of receiving stations.

[0019] As a preferred implementation, determining the constants of the observation system equations includes:

[0020] Based on the geographical locations of the transmitting and receiving stations, the antenna gain of the receiving station, and the height of the detection array, the height of the equivalent cuboid of the detection array is obtained;

[0021] Based on the relationship between the height of the equivalent cuboid and the pulse width, and combined with the height of the detection body, the antenna gain of the transmitting station, and the elevation angle of the transmitted beam, the volume of the detection body is determined.

[0022] Substituting the volume of the detection pool and the radar transmission power into the radar equations, we obtain the constants of the observation system equations at the height of the detection pool.

[0023] As a preferred implementation, the process of obtaining the height of the equivalent cuboid is as follows:

[0024] ;

[0025] Where L represents the height of the equivalent cuboid, and acos() represents the inverse cosine calculation. Let represent the antenna efficiency coefficient of the p-th receiving station. This represents the antenna gain of the p-th receiving station. Indicates the altitude of the probe. This represents the elevation angle of the receiving beam at the p-th receiving station. This represents the angle between the transmitted beam and the beam of the p-th receiving station.

[0026] As a preferred implementation method, the process of obtaining the volume of the probe body is as follows:

[0027] ;

[0028] Where V represents the volume of the probe, and L represents the height of the equivalent cuboid. Indicates the altitude of the probe. This indicates the antenna gain of the transmitting station. Indicates the elevation angle of the transmitted beam. Indicates the pulse width.

[0029] As a preferred implementation method, obtaining the observation system equation constants at the probe's common altitude includes:

[0030] ;

[0031] Where C represents the constant of the observation system equations, Indicates radar transmit power. This indicates the antenna gain of the transmitting station. Let λ represent the antenna gain of the p-th receiving station, and λ represent the radar wavelength. Indicates electron radius, This indicates the distance from the launch station to the probe community. This indicates the distance from the receiving station to the probe community. B represents the Boltzmann constant, and B represents the signal bandwidth. The angle between the transmitted beam and the beam of the p-th receiving station is represented by V, and the volume of the detection array is represented by V.

[0032] As a preferred implementation, the ionospheric parameters for each detection range gate are obtained by fitting the signal autocorrelation function and inverting it.

[0033] Construct the observation system equations:

[0034] ;

[0035] in, Let represent the autocorrelation function of the signal at the i-th detection range gate, C represent the constant of the observation system equation, A represent the spectral ambiguity function matrix of the signal, P(ω, x) represent the plasma scattering theoretical power spectrum function, ω represent the frequency sampling point vector, x=[Ne,Te,Ti,v] represent the vector composed of ionospheric parameters, Ne represent the electron density, Te represent the electron temperature, Ti represent the ion temperature, v represent the plasma line-of-sight drift velocity, and δ represent the statistical error.

[0036] The least squares fitting method is used, with the residuals of the observation system equations as the objective function. When the objective function reaches its minimum value, the fitted ionospheric parameters are obtained.

[0037] As a preferred implementation, the process of dividing the detection range gate includes:

[0038] Obtain the detection range range formed by the leading edge and trailing edge of the gate of the radar beam;

[0039] The detection range is divided into multiple detection range gates based on the sampling interval.

[0040] The beneficial effects of this invention are:

[0041] (1) By constructing the autocorrelation function of each detection range gate, multiple key parameter profiles of the ionosphere are effectively derived from the original sampled signals of the multi-base incoherent scattering radar by combining multiple data. This solves the problem of the failure of conventional signal and data processing methods due to the different geometric positions of the transmitting and receiving stations. Effective multi-parameter results of the ionosphere are obtained, which can be used for signal and data processing of phased array incoherent scattering radar systems with separate transmitting and receiving stations, and to conduct multi-parameter detection of the ionosphere at all times, all weather, and all altitudes, providing reliable data for space physics and space weather research.

[0042] (2) Multi-base phased array incoherent scattering radar provides spatial anisotropy characteristics of ionospheric parameters by separating the transmitting and receiving. The scattering volume of the detection body is affected by the geometric position of the transmitting and receiving stations. This application modifies the radar equation by calculating the volume of the detection body, so that the algorithm is not limited by the position of the radar transmitting and receiving stations, and effectively improves the applicability of signal and data processing.

[0043] (3) Compared with conventional signal and data processing methods for ionospheric detection by single-station incoherent scattering radar, this application calculates the time difference between the received signal between the radar receiving station and the transmitting station based on the height of the detection body, and completes the time correction of the receiving station. This effectively solves the problem of inaccurate distance information of the receiving station signal caused by time deviation due to the different geometric positions of the transmitting and receiving stations. Attached Figure Description

[0044] Other features, objects, and advantages of this application will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings:

[0045] Figure 1 This is a flowchart of a signal and data processing method for a multi-base incoherent scattering radar according to an embodiment of this application;

[0046] Figure 2 This is a system block diagram of a signal and data processing system for a multi-base incoherent scattering radar according to an embodiment of this application;

[0047] Figure 3 This is a schematic diagram of the structure of a computer system used to implement the methods, systems, and devices of this application. Detailed Implementation

[0048] The present application will now be described in further detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the invention. Furthermore, it should be noted that, for ease of description, only the parts relevant to the invention are shown in the accompanying drawings.

[0049] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. This application will now be described in detail with reference to the accompanying drawings and embodiments.

[0050] This application provides a signal and data processing method for multi-base incoherent scattering radar. This method divides the detection range of the multi-base incoherent scattering radar beam into multiple detection range gates and constructs the signal autocorrelation function for each detection range gate. The statistical error of the signal autocorrelation function is accumulated within the time resolution. Based on the antenna gain of the transmitting and receiving stations of the multi-base incoherent scattering radar, and the detection altitude of the transmitting and receiving beams, combined with the radar transmit power, the receiving station signal time correction is completed, and the observation system equation constants are determined. According to the spectral ambiguity function, the power spectrum function of plasma scattering theory, combined with the observation system equation constants and the statistical error of the signal autocorrelation function, the signal autocorrelation function is fitted, and the ionospheric parameters of each detection range gate are obtained by inversion. By constructing the autocorrelation function of each detection range gate, multiple key parameter profiles of the ionosphere are effectively retrieved from the raw sampled signals of the multi-base incoherent scattering radar by combining various data. This solves the problem of the failure of conventional signal and data processing methods due to the different geometric positions of the transmitting and receiving stations, and obtains effective multi-parameter results of the ionosphere. These results can be used for signal and data processing of phased array incoherent scattering radar systems with separate transmitting and receiving stations, enabling multi-parameter detection of the ionosphere at all times, all weather conditions, and all altitudes, providing reliable data for space physics and space weather research.

[0051] To more clearly explain the signal and data processing method of the multi-base incoherent scattering radar of this application, the following will be combined with... Figure 1 The steps in the embodiments of this application are described in detail.

[0052] The signal and data processing method for a multi-base incoherent scattering radar according to the first embodiment of this application includes steps S10-S40, each of which is described in detail below:

[0053] Step S10: Divide the detection range of the multi-base incoherent scattering radar beam into multiple detection range gates, and construct the signal autocorrelation function of each detection range gate. The signal autocorrelation function is accumulated within the time resolution, and the statistical error of the signal autocorrelation function is calculated.

[0054] Optionally, as an ionospheric detection device, the entire height range of the ionosphere is a target for multi-base incoherent scattering radar. However, it is not necessary to detect the entire ionosphere in every detection process. In this embodiment, the detection range consisting of the leading edge and trailing edge of the radar detection beam is first obtained. For example, if the leading edge of the gate is set to 100km and the trailing edge of the gate is set to 500km, then the defined detection range is the ionosphere from 100km to 500km.

[0055] Furthermore, the detection range is divided into multiple detection range gates based on the sampling interval.

[0056] As an example, the detection range gate can be divided using the following formula:

[0057] ;

[0058] Where N represents the number of detection range gates. Indicates the trailing edge of the gate. Indicates the leading edge of the gate, denoted by , where represents the sampling interval, and c represents the speed of light.

[0059] In this embodiment of the application, the sampling interval is determined according to the actual sampling situation, for example, it can be 10 microseconds. Correspondingly, within the detection distance range, there is one sampling point every 1.5 kilometers.

[0060] It should be noted that the detection range of a single detection range gate depends on the pulse width. For example, when the pulse width is 480 microseconds, the corresponding detection range is 72km. When radar detects the ionosphere, one pulse width corresponds to the sampling of one detection range gate. For example, when one pulse width corresponds to a detection range of 72km, there is one sampling point every 1.5km, and one detection range gate includes 48 sampling points.

[0061] It is understandable that the range of a single detection range gate corresponds to the range covered by a single pulse width. For example, at the first sampling point at 100km, the range of the first detection range gate is 100~172km, and at the second sampling point at 101.5km, the range of the second detection range gate is 101.5~173.5km. The detection range gate is gradually increased by the sampling interval.

[0062] After dividing the detection range gates, the time delay profile matrix of each gate is obtained. The rows of the time delay profile matrix represent the pulse sampling point sequence, the columns represent the conjugate sequence of the pulse sampling points, and the matrix elements are the dot product of the corresponding sampling point and its conjugate. Furthermore, the signal autocorrelation function of each detection range gate is constructed based on the time delay signal and its conjugate.

[0063] In the embodiments of this application, for any detection range gate, based on the original in-phase and quadrature signals acquired by the radar, the dot product of the time-delay signal and the signal conjugate at different time delays is calculated, and the mean of the dot product with the same time delay is obtained as the value of the time delay. The values ​​of all time delays are calculated to construct the signal autocorrelation function.

[0064] It should be noted that the original in-phase and orthogonal data are projections of the signal onto a two-dimensional orthogonal coordinate system (in-phase axis I and orthogonal axis Q). The data form is a series of complex pairs (I, Q) arranged in time order. A time delay profile matrix is ​​constructed based on the original in-phase and orthogonal data, which serves as the basis for calculating the signal autocorrelation function.

[0065] Calculating the dot product of two signal vectors (time-delayed signal and signal conjugate) at a certain time delay is essentially performing a complex correlation operation, which involves multiplying the complex numbers at corresponding points and then averaging them. This method can keenly capture the degree of similarity between two signals under different relative delays.

[0066] As an example, the signal autocorrelation function can be constructed using the following formula:

[0067] ;

[0068] in, This represents the k-th time delay value of the autocorrelation function of the signal of the i-th detection range gate. Indicates the number of sampling points.

[0069] Understandably, as the time delay k increases, the number of product terms available for summation decreases (from n terms to nk terms). If the total number of points n is used as the denominator, the estimated value will systematically decrease as k increases, resulting in bias. Therefore, using the currently valid number of terms (nk) as the denominator ensures the accuracy of the estimate.

[0070] For each detection range gate within the detection range, the above calculation is repeated according to the number of detection range gates to obtain the signal autocorrelation function of N detection range gates.

[0071] Furthermore, within a set time resolution, the autocorrelation function of the signal is incoherently accumulated to obtain the statistical error of the autocorrelation function.

[0072] It should be noted that time resolution is the time length for the accumulation of the signal autocorrelation function. The pulse repetition period determines the cycle time of each frame. The number of pulse repetition periods included in a set time resolution is the number of frames collected within that time resolution. For example, if the pulse repetition period is 10 milliseconds and the set time resolution is 10 seconds, then the signal autocorrelation function of 1000 frames of sampled signals is accumulated within that time resolution.

[0073] In this embodiment of the application, a single-frame sampling signal within the detection range is acquired, wherein the single-frame sampling signal includes multiple detection range gates; within the multi-frame sampling signal included in the time resolution, the standard deviation of the signal autocorrelation function corresponding to all detection range gates in each frame sampling signal is acquired after incoherent accumulation, and is used as the statistical error of the signal autocorrelation function.

[0074] As an example, the statistical error can be determined using the following formula:

[0075] ;

[0076] Where δ represents the statistical error. Indicates the first The autocorrelation function of the frame signal. M represents the total number of frames accumulated.

[0077] Statistical error is a quantitative result of the inherent uncertainty caused by the randomness and unpredictable fluctuations of measurement. Through the above calculation, the magnitude of the difference can be quantitatively described to ensure the accuracy of the measurement results.

[0078] Step S20: Based on the detection altitude of the transmit beam and the receive beam, the elevation angle of the transmit beam and the elevation angle of the receive beam, obtain the time difference between the received signal between the receiving station and the transmitting station, wherein the time difference is used to correct the time of the signal at the receiving station.

[0079] Optionally, time correction can be used to ensure the accuracy of the distance information corresponding to the receiving station signal and time, thereby ensuring the physical effectiveness of subsequent signal processing.

[0080] In this embodiment, the time difference between the receiving station and the transmitting station of the multi-base incoherent scattering radar is first obtained based on the detection group height, the transmit beam elevation angle and the receive beam elevation angle. Then, the time difference is subtracted from the receiving station time to complete the time correction.

[0081] As an example, the time difference can be determined using the following formula:

[0082] ;

[0083] Where dt represents the time difference and c represents the speed of light. Indicates the altitude of the probe. Indicates the elevation angle of the transmitted beam. Let q represent the elevation angle of the receiving beam of the p-th receiving station, and q represent the total number of receiving stations.

[0084] It should be noted that the detection common body height is the altitude or vertical height of the area where the radar transmit beam and receive beam intersect in the ionosphere. It is used to locate the ionospheric target being detected. By detecting the common body height, the path difference caused by the separate transmission and reception is calculated, and then the time difference is obtained as the correction amount for the receiving station. This effectively solves the problem that the time deviation caused by the different geometric positions of the transmitting and receiving stations leads to inaccurate distance information corresponding to the time of the receiving station signal.

[0085] Step S30: After time correction of the signal from the receiving station, determine the constants of the observation system equations based on the antenna gain of the transmitting and receiving stations, the altitude of the detection body, and the radar transmission power.

[0086] Optionally, time correction ensures the accuracy of the distance information corresponding to time in the constants of the observation system equations, thereby enabling the calculation of the constants of the observation system equations.

[0087] As one possible implementation, the height of the equivalent cuboid of the detection pool is obtained based on the geographical locations of the transmitting and receiving stations, the antenna gain of the receiving station, and the height of the detection pool. According to the relationship between the height of the equivalent cuboid and the pulse width, the volume of the detection pool is determined based on the height of the equivalent cuboid or the pulse width, combined with the height of the detection pool, the antenna gain of the transmitting station, and the elevation angle of the transmitted beam. The volume of the detection pool and the radar transmission power are substituted into the radar equation to obtain the constant of the observation system equation at the height of the detection pool.

[0088] Understandably, for the sake of computational simplicity, the probe community is approximated as a cuboid through the computational model, and this equivalent cuboid can be used as the model of the probe community for subsequent calculations.

[0089] As an example, the height of the equivalent cuboid can be calculated using the following formula:

[0090] ;

[0091] Where L represents the height of the equivalent cuboid, and acos() represents the inverse cosine calculation. Let represent the antenna efficiency coefficient of the p-th receiving station. This represents the antenna gain of the p-th receiving station. Indicates the altitude of the probe. This represents the elevation angle of the receiving beam at the p-th receiving station. This represents the angle between the transmitted beam and the beam of the p-th receiving station.

[0092] It should be noted that the angle between the transmitting beam and the receiving beam is determined by the geographical locations of the transmitting and receiving stations.

[0093] As an example, a horizontal coordinate system is constructed with the radar transmitting station as the origin and north, east, and zenith as the coordinate axes. The Cartesian coordinates of the detection object in this coordinate system are calculated based on the direction of the transmitted beam and the detection range. The coordinate transformation formula is as follows:

[0094] ;

[0095] Where el represents the elevation angle and az represents the azimuth angle. This indicates the distance from the launch station to the probe.

[0096] Substituting the elevation and azimuth angles of the transmitted beam detected jointly by the receiving beam of the p-th receiving station into the above formula, we obtain the Cartesian coordinates of the corresponding transmitted beam in this coordinate system. And import the Cartesian coordinates of the p-th receiving station in the above coordinate system. Calculate the angle between the transmitted beam and the beam of the p-th receiving station. The formula is:

[0097] .

[0098] Furthermore, based on the height of the obtained equivalent cuboid, the volume of the probe body is calculated.

[0099] As an example, the volume of the probe pool can be determined using the following formula:

[0100] ;

[0101] Where V represents the volume of the probe body. This indicates the antenna gain of the transmitting station. Indicates the pulse width.

[0102] After obtaining the volume of the detection pool, the volume of the detection pool and the radar transmission power are substituted into the radar equation to obtain the observation system equation constant for the height of the detection pool.

[0103] As an example, the constants of the observation system equations can be obtained using the following formula:

[0104] ;

[0105] Where C represents the constant of the observation system equations, λ represents the radar transmit power, and λ represents the radar wavelength. Indicates electron radius, This indicates the distance from the launch station to the probe community. This indicates the distance from the receiving station to the probe community. B represents the Boltzmann constant, and B represents the signal bandwidth. This represents the angle between the transmitted beam and the beam of the p-th receiving station.

[0106] The observation system equation constants are used to construct the observation system equations, which are then used to fit the signal autocorrelation function. By calculating the volume of the detection system, the radar equations are modified, making the algorithm independent of the locations of the radar transmitting and receiving stations, effectively improving the applicability of signal and data processing.

[0107] Step S40: Based on the spectral ambiguity function, the power spectrum function of plasma scattering theory, and the constants and statistical errors of the observation system equations, the autocorrelation function of the signal is fitted, and the ionospheric parameters of each detection range gate are obtained by inversion.

[0108] Optionally, the signal autocorrelation function constructed based on the time-delay dot product is calculated from the raw signal received by the radar, representing a quantification of the observed facts. The equation constructed using the spectral ambiguity function, the power spectrum function of plasma scattering theory, combined with the constants of the observation system equations and the statistical error of the signal autocorrelation function, constitutes a theoretical model. Its form is determined by the ionospheric parameters to be determined (electron density, electron temperature, ion temperature, plasma line-of-sight drift velocity, etc.). Therefore, by fitting the signal autocorrelation function to the theoretical model, the true ionospheric parameters can be obtained through inversion.

[0109] In this embodiment of the application, fitting and inversion are performed by constructing an observation system equation. As an example, the observation system equation is:

[0110] ;

[0111] in, Let represent the autocorrelation function of the signal at the i-th detection range gate, C represent the constant of the observation system equation, A represent the spectral ambiguity function matrix of the signal, P(ω, x) represent the plasma scattering theoretical power spectrum function, ω represent the frequency sampling point vector, x=[Ne,Te,Ti,v] represent the vector composed of ionospheric parameters, Ne represent the electron density, Te represent the electron temperature, Ti represent the ion temperature, v represent the plasma line-of-sight drift velocity, and δ represent the statistical error of the signal autocorrelation function.

[0112] After constructing the observation system equations, the least squares fitting method is used, with the residuals of the observation system equations as the objective function. When the objective function reaches its minimum value, the fitted ionospheric parameters are obtained.

[0113] Furthermore, each detection range gate is calculated according to the above process to obtain the profile results of the ionosphere with multiple parameters within the entire detection range.

[0114] Although the steps in the above embodiments are described in the above order, those skilled in the art will understand that in order to achieve the effect of this embodiment, different steps do not need to be executed in such order. They can be executed simultaneously (in parallel) or in reverse order. These simple changes are all within the protection scope of this application.

[0115] Please see Figure 2 The signal and data processing system of the multi-base incoherent scattering radar of the second embodiment of this application includes: a signal autocorrelation function construction module 100, a time correction module 200, an observation system equation constant determination module 300, and a fitting inversion module 400.

[0116] The signal autocorrelation function construction module 100 is used to divide the detection range of the multi-base incoherent scattering radar beam into multiple detection range gates and construct the signal autocorrelation function of each detection range gate. The signal autocorrelation function is accumulated within the time resolution and the statistical error of the signal autocorrelation function is calculated.

[0117] The time correction module 200 is used to obtain the time difference between the received signal and the transmitting station based on the detection altitude, transmit beam elevation angle and receive beam elevation angle of the transmitting beam and the receiving beam. The time difference is used to correct the signal of the receiving station.

[0118] The observation system equation constant determination module 300 is used to determine the observation system equation constants based on the antenna gain of the transmitting and receiving stations, the height of the detection body, and the radar transmission power after the signal of the receiving station is time-corrected.

[0119] The fitting and inversion module 400 is used to fit the autocorrelation function of the signal based on the spectral ambiguity function, the power spectrum function of the plasma scattering theory, and the constants and statistical errors of the observation system equations, and to invert the ionospheric parameters of each detection range gate.

[0120] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working process and related descriptions of the system described above can be found in the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0121] It should be noted that the signal and data processing system for the multi-base incoherent scattering radar provided in the above embodiments is only an example of the division of the above functional modules. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the modules or steps in the embodiments of this application can be further decomposed or combined. For example, the modules in the above embodiments can be merged into one module, or further divided into multiple sub-modules to complete all or part of the functions described above. The names of the modules and steps involved in the embodiments of this application are only for distinguishing the various modules or steps and are not considered as an improper limitation of this application.

[0122] An electronic device according to a third embodiment of this application includes:

[0123] At least one processor; and

[0124] A memory communicatively connected to at least one of the processors; wherein,

[0125] The memory stores instructions that can be executed by the processor to implement the signal and data processing method of the multi-base incoherent scattering radar described above.

[0126] A computer-readable storage medium according to a fourth embodiment of this application stores computer instructions, which are executed by the computer to implement the above-described signal and data processing method for multi-base incoherent scattering radar.

[0127] A computer program product according to the fifth embodiment of this application, when run on an electronic device, causes the electronic device to perform the above-described signal and data processing method for multi-base incoherent scattering radar.

[0128] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes and related descriptions of the electronic devices, computer-readable storage media, and computer program products described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0129] Those skilled in the art will recognize that the modules and method steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. The programs corresponding to the software modules and method steps can be placed in random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disks, removable disks, CD-ROMs, or any other form of storage medium known in the art. To clearly illustrate the interchangeability of electronic hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in electronic hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0130] The following is for reference. Figure 3 It shows a schematic diagram of the structure of a computer system for implementing the methods, systems, and devices of this application. Figure 3 The server shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of this application.

[0131] like Figure 3As shown, the computer system includes a Central Processing Unit (CPU) 301, which can perform various appropriate actions and processes based on programs stored in Read Only Memory (ROM) 302 or programs loaded from storage section 308 into Random Access Memory (RAM) 303. The RAM 303 also stores various programs and data required for system operation. The CPU 301, ROM 302, and RAM 303 are interconnected via a bus 304. An Input / Output (I / O) interface 305 is also connected to the bus 304.

[0132] The following components are connected to I / O interface 305: an input section 306 including a keyboard, mouse, etc.; an output section 307 including a cathode ray tube (CRT), liquid crystal display (LCD), and speakers, etc.; a storage section 308 including a hard disk, etc.; and a communication section 309 including a network interface card such as a LAN (Local Area Network) card and a modem, etc. The communication section 309 performs communication processing via a network such as the Internet. A drive 310 is also connected to I / O interface 305 as needed. Removable media 311, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., are installed on drive 310 as needed so that computer programs read from them can be installed into storage section 308 as needed.

[0133] Specifically, according to embodiments of this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 309, and / or installed from removable medium 311. When the computer program is executed by central processing unit (CPU) 301, it performs the functions defined in the methods of this application. It should be noted that the computer-readable medium described above in this application can be a computer-readable signal medium or a computer-readable storage medium, or any combination of the two. The computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this application, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in connection with an instruction execution system, apparatus, or device. In this application, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can also be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on a computer-readable medium can be transmitted using any suitable medium, including but not limited to: wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0134] Computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0135] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0136] The terms “first”, “second”, etc., are used to distinguish similar objects, not to describe or indicate a specific order or sequence.

[0137] The term "comprising" or any other similar term is intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus / device that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent in such process, method, article, or apparatus / device.

[0138] The technical solutions of this application have been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of this application is obviously not limited to these specific embodiments. Without departing from the principles of this application, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of this application.

Claims

1. A signal and data processing method for a multi-base incoherent scattering radar, characterized in that, include: The detection range of the multi-base incoherent scattering radar beam is divided into multiple detection range gates, and the signal autocorrelation function of each detection range gate is constructed. The signal autocorrelation function is accumulated within the time resolution, and the statistical error of the signal autocorrelation function is calculated. Based on the detection altitude, elevation angle of the transmitted beam and the elevation angle of the received beam, the time difference between the received signal between the receiving station and the transmitting station is obtained, wherein the time difference is used to perform time correction on the signal of the receiving station. After time correction of the signal at the receiving station, the constants of the observation system equations are determined based on the antenna gains of the transmitting and receiving stations, the height of the detection pool, and the radar transmission power. Based on the spectral ambiguity function, the power spectrum function of plasma scattering theory, the constants of the observation system equations, and the statistical error, the autocorrelation function of the signal is fitted, and the ionospheric parameters of each detection range gate are obtained by inversion. The determination of the constants in the observation system equations includes: Based on the geographical locations of the transmitting and receiving stations, the antenna gain of the receiving station, and the height of the detection pool, the height of the equivalent cuboid of the detection pool is obtained; Based on the relationship between the height of the equivalent cuboid and the pulse width, and combined with the height of the detection body, the antenna gain of the transmitting station, and the elevation angle of the transmitted beam, the volume of the detection body is determined. Substituting the volume of the detection pool and the radar transmission power into the radar equation, the constants of the observation system equation at the height of the detection pool are obtained.

2. The signal and data processing method for multi-base incoherent scattering radar according to claim 1, characterized in that, The construction of the signal autocorrelation function for each detection range gate includes: For any detection range gate, based on the original in-phase and quadrature signals acquired by the radar, the dot product of the time-delayed signal and the signal conjugate at different time delays is calculated, and the mean of the dot product at the same time delay is obtained as the value of that time delay. The autocorrelation function of the signal is constructed by calculating the values ​​of all time delays.

3. The signal and data processing method for multi-base incoherent scattering radar according to claim 1, characterized in that, The process of obtaining the statistical error includes: Acquire a single frame sampling signal within the detection range, wherein the single frame sampling signal includes multiple detection range gates, and each detection range gate corresponds to a sampling of a single pulse width; Within the multi-frame sampling signals included in the time resolution, the standard deviation of the autocorrelation function of the signal corresponding to all detection range gates in each frame sampling signal is obtained after incoherent accumulation, and is used as the statistical error.

4. The signal and data processing method for multi-base incoherent scattering radar according to claim 1, characterized in that, The acquisition of the time difference between the received signal and the transmitting station includes: ； Where dt represents the time difference and c represents the speed of light. Indicates the altitude of the probe. Indicates the elevation angle of the transmitted beam. Let q represent the elevation angle of the receiving beam of the p-th receiving station, and q represent the total number of receiving stations.

5. The signal and data processing method for multi-base incoherent scattering radar according to claim 1, characterized in that, The process for obtaining the height of the equivalent cuboid is as follows: ； Where L represents the height of the equivalent cuboid, and acos() represents the inverse cosine calculation. Let represent the antenna efficiency coefficient of the p-th receiving station. This represents the antenna gain of the p-th receiving station. Indicates the altitude of the probe. This represents the elevation angle of the receiving beam at the p-th receiving station. This represents the angle between the transmitted beam and the beam of the p-th receiving station.

6. The signal and data processing method for multi-base incoherent scattering radar according to claim 1, characterized in that, The process of obtaining the volume of the probe body is as follows: ； Where V represents the volume of the detection body, and L represents the height of the equivalent cuboid. Indicates the altitude of the probe. This indicates the antenna gain of the transmitting station. Indicates the elevation angle of the transmitted beam. Indicates the pulse width.

7. The signal and data processing method for multi-base incoherent scattering radar according to claim 1, characterized in that, The acquisition of the observation system equation constants at the altitude of the detection community includes: ； Where C represents the constant of the observation system equations, Indicates radar transmit power. This indicates the antenna gain of the transmitting station. Let λ represent the antenna gain of the p-th receiving station, and λ represent the radar wavelength. Indicates electron radius, This indicates the distance from the launch station to the probe community. This indicates the distance from the receiving station to the probe community. B represents the Boltzmann constant, and B represents the signal bandwidth. The angle between the transmitted beam and the beam of the p-th receiving station is represented by V, and the volume of the detection array is represented by V.

8. The signal and data processing method for multi-base incoherent scattering radar according to claim 1, characterized in that, The fitting and inversion of the signal autocorrelation function to obtain the ionospheric parameters for each detection range gate includes: Construct the observation system equations: ； in, Let represent the autocorrelation function of the signal at the i-th detection range gate, C represent the constant of the observation system equation, A represent the spectral ambiguity function matrix of the signal, P(ω, x) represent the plasma scattering theoretical power spectrum function, ω represent the frequency sampling point vector, x=[Ne,Te,Ti,v] represent the vector composed of ionospheric parameters, Ne represent the electron density, Te represent the electron temperature, Ti represent the ion temperature, v represent the plasma line-of-sight drift velocity, and δ represent the statistical error. The least squares fitting method is used, with the residual of the observation system equation as the objective function. When the objective function reaches its minimum value, the inverted ionospheric parameters are obtained.

9. The signal and data processing method for multi-base incoherent scattering radar according to claim 1, characterized in that, The process of dividing the detection range gate includes: Obtain the detection range range formed by the leading edge and trailing edge of the gate of the radar beam; The detection range is divided into multiple detection range gates based on the sampling interval.

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