Method and system for checking consistency of dual-polarization radar transmitting dual channels

Abstract

The invention relates to the technical field of dual-polarization radars, and discloses a dual-polarization radar transmitting dual-channel consistency checking method and system, and the method comprises the steps: constructing a dual-polarization radar transmitting dual-channel structure equation model and radar operation state data; determining a dual-polarization radar transmitting dual-channel consistency analysis path diagram; using a daily quantile pairing method and radar operation state data to check the significant difference of the same attribute observation variables of the two channels of the antenna; under the condition that significant difference exists, calculating a dual-channel optimal path coefficient of the same attribute observation variable by adopting a daily quantile-to-daily quantile regression method and radar operation state data; and configuring the optimal path coefficient of the two channels based on the analysis path diagram, and comparing and analyzing the consistency of the two channels on different daily quantiles. According to the method, the dynamic consistency characteristic of dual-channel influence during radar operation can be tested.

Description

Technical Field

[0001] The present invention relates to the technical field of dual-polarization radar, and in particular to a method and system for checking the consistency of dual-channel transmission of a dual-polarization radar. Background Art

[0002] Dual-polarization radars can be roughly divided into the following categories according to their application: (1) Ground surveillance and target recognition radars, which use polarization characteristics to distinguish target materials (such as metal and non-metal) or structures (vehicles, buildings), and are used in military reconnaissance, border monitoring, and autonomous driving (obstacle recognition). (2) Synthetic aperture dual-polarization radar (Dual-Pol SAR) combines synthetic aperture technology (SAR) with dual polarization to improve the ability to identify surface features. It is used in agricultural monitoring (crop classification), geological exploration (soil moisture), and disaster assessment (floods, earthquakes). Its representative systems include the European Space Agency's Sentinel-1 satellite and ALOS-2 satellite. (3) Dual-polarization weather radars, which identify precipitation types (rain, snow, hail), estimate rainfall, and analyze storm structures. Typical applications include the US NEXRAD weather radar network and China's CINRAD series radars. (4) Biological monitoring radars: Use dual-polarization information to track the migration of birds, insects, and other organisms and analyze their body size and flight patterns. (5) Ocean monitoring radar: uses dual-polarization information to observe the direction of waves, sea surface roughness, and detect oil pollution or ice floes.

[0003] Existing research on dual-polarization channel consistency mainly focuses on dual-channel calibration. Typical research contents include:

[0004] 1. Calibration Method Research Internal Calibration: Develop and use an internal calibration signal source to calibrate the channels using a known signal to ensure consistency between channels. External Calibration: Use an external standard signal source or reference antenna to calibrate and verify and adjust channel consistency.

[0005] 2. Testing and Validation Lab testing: Testing is performed in a controlled lab environment to verify the effectiveness of calibration methods and algorithms. Field testing: Testing is performed in an actual application environment to verify the performance of channel consistency under real-world conditions.

[0006] 3. Application scenario research radar system: Study the application of dual-polarization channel consistency in radar systems to ensure the accuracy of target detection and recognition.

[0007] 4. Communication Systems: Study the impact of dual-polarization channel consistency in communication systems to ensure reliable data transmission.

[0008] In addition, there are many research results on the consistency of dual-channel calibration, but the radar calibration status cannot truly reflect the dynamic consistency characteristics of the dual-channel influence when the radar is running. Summary of the Invention

[0009] The purpose of the present invention is to provide a dual-polarization radar transmission dual-channel consistency verification method and system to verify the dynamic consistency characteristics of the dual-channel influence when the radar is running, and is also suitable for expansion to multi-polarization radar systems.

[0010] In order to achieve the above purpose, the technical solutions adopted are as follows:

[0011] In a first aspect, the present invention provides a method for verifying the consistency of dual-channel transmission of a dual-polarization radar, the method comprising:

[0012] Construct a dual-channel structural equation model for dual-polarization radar transmission and radar operating status data;

[0013] Determine the dual-channel consistency analysis path diagram for dual-polarization radar transmission;

[0014] The daily quantile pairing method and radar operation status data were used to test the significant differences of the same attribute observation variables of the antenna dual channels.

[0015] When there are significant differences, the radar transmitter observation variables are used as independent variables and the antenna observation variables are used as dependent variables. The dual-channel optimal path coefficients of the same attribute observation variables are calculated using the daily quantile-to-daily quantile regression method and radar operation status data.

[0016] The dual-channel optimal path coefficient is configured based on the analysis path diagram, and the dual-channel consistency at different daily quantiles is compared and analyzed.

[0017] Furthermore, the dual-polarization radar transmitting dual-channel structural equation model includes a transmitter, a horizontal channel, a vertical channel, an antenna, a transmitter measurement unit and an antenna measurement unit; wherein, the transmitter is associated with the antenna through the horizontal channel and the vertical channel respectively, the transmitter measurement unit is used to obtain transmitter measurement indicators, and the antenna measurement unit is used to obtain antenna measurement indicators.

[0018] Furthermore, the transmitter measurement index includes two radar transmitter observation variables, namely radar transmitter observation variable one and radar transmitter observation variable two, and the antenna measurement index includes two antenna observation variables, namely antenna horizontal channel observation variable one, antenna horizontal channel observation variable two, antenna vertical channel observation variable one and antenna vertical channel observation variable two.

[0019] Furthermore, a dual-polarization radar transmission dual-channel consistency analysis path diagram is determined based on the path analysis method. The analysis path diagram is used to characterize the variable relationship (observed variables and latent variables). When the radar transmitter observation variable 1 and the radar transmitter observation variable 2 are regarded as two independent variables, the observed variable relationship represented by the analysis path diagram includes:

[0020] Difference evaluation of two independent samples of antenna horizontal channel observation variable 1 and antenna vertical channel observation variable 1;

[0021] Difference evaluation of two independent samples of antenna horizontal channel observation variable 2 and antenna vertical channel observation variable 2;

[0022] The characteristic relationship of radar transmitter observation variable 1 as the independent variable, antenna horizontal channel observation variable 1 and antenna vertical channel observation variable 1 as the dependent variables respectively;

[0023] The characteristic relationship of radar transmitter observation variable two as the independent variable, antenna horizontal channel observation variable two and antenna vertical channel observation variable two as the dependent variables respectively.

[0024] Furthermore, the daily quantile pairing method and radar operating status data were used to test the significant differences in the same attribute observation variables of the antenna dual channels, including:

[0025] Usually the observed variable x is a function of time t, let Represents the observed variable x t Daily distribution (24 hours), The daily α quantile q at time t d (α) by Given, the daily α quantile distribution is determined by the following formula:

[0026]

[0027] in, is the daily distribution function of the observed variable The inverse function of Q d (α) is the daily α quantile distribution; d is 24 hours per day, and N is the number of days.

[0028] The daily quantile pairing method is used to calculate the significant difference value of the same attribute observation variable of the antenna dual channel The specific calculation process is expressed as:

[0029]

[0030] in, is the daily α quantile paired test function of the observed variables of the antenna horizontal channel and the antenna vertical channel, is the daily α quantile distribution of the antenna horizontal channel, is the daily α quantile distribution of the antenna vertical channel.

[0031] Furthermore, when there are significant differences, the radar transmitter observation variables are used as independent variables and the antenna observation variables are used as dependent variables. The dual-channel optimal path coefficients of the same attribute observation variables are calculated using the daily quantile-to-daily quantile regression method and radar operation status data, including;

[0032] Establish a daily quantile-to-daily quantile regression model, expressed as:

[0033]

[0034] in, represents the daily α quantile distribution of the antenna observation variable; represents the daily α quantile distribution of the transmitter observation variable; λ α represents the optimal path coefficient of the daily α quantile of the horizontal channel or vertical channel; μ d (α) represents the error affected by the horizontal channel or vertical channel;

[0035] The optimal path coefficients of the daily α quantiles of the horizontal channel are estimated by the least squares method and the optimal path coefficient of the daily α quantile of the vertical channel

[0036] Furthermore, the calculation results of the optimal path coefficients of the above-mentioned different daily quantiles are configured to the analysis path diagram to achieve dual-channel consistency of comparative analysis of the same attribute observation variable.

[0037] In a second aspect, the present invention provides a dual-polarization radar transmission dual-channel consistency verification system, the system comprising:

[0038] A model and data construction module is configured to construct a dual-polarization radar transmitting dual-channel structural equation model and radar operating status data;

[0039] A path analysis module is configured to determine a dual-channel consistency analysis path diagram for dual-polarization radar transmission;

[0040] The significant difference analysis module is configured to use the daily quantile pairing method and radar operation status data to test the significant differences of the same attribute observation variables of the antenna dual channels;

[0041] The optimal path coefficient calculation module is configured to use the radar transmitter observation variable as the independent variable and the antenna observation variable as the dependent variable when there is a significant difference. It uses the daily quantile-to-daily quantile regression method and radar operation status data to calculate the dual-channel optimal path coefficient of the same attribute observation variable;

[0042] The dual-channel consistency analysis module is configured to configure the dual-channel optimal path coefficient based on the analysis path diagram, and compare and analyze the dual-channel consistency at different daily quantiles.

[0043] Furthermore, the significant difference analysis module is further configured to:

[0044] set up Represents the observed variable x t Daily distribution (24 hours), The daily α quantile q at time t d (α) by Given, the daily α quantile distribution is determined by the following formula:

[0045]

[0046] in, is the daily distribution function of the observed variable The inverse function of Q d (α) is the daily α quantile distribution; d is 24 hours per day, and N is the number of days.

[0047] The daily quantile pairing method is used to calculate the significant difference value of the same attribute observation variable of the antenna dual channel The specific calculation process is expressed as:

[0048]

[0049] in, is the daily α quantile paired test function of the observed variables of the antenna horizontal channel and the antenna vertical channel, is the daily α quantile distribution of the antenna horizontal channel, is the daily α quantile distribution of the antenna vertical channel.

[0050] Furthermore, the optimal path coefficient calculation module is further configured to:

[0051] Establish a daily quantile-to-daily quantile regression model, expressed as:

[0052]

[0053] in, represents the daily α quantile distribution of the antenna observation variable; represents the daily α quantile distribution of the transmitter observation variable; λ α represents the optimal path coefficient of the daily α quantile of the horizontal channel or vertical channel; μ d (α) represents the error affected by the horizontal channel or vertical channel;

[0054] The optimal path coefficients of the daily α quantiles of the horizontal channel are estimated by the least squares method and the optimal path coefficient of the daily α quantile of the vertical channel

[0055] The dual-channel consistency analysis module is further configured to: configure the optimal path coefficient calculation results of different daily quantiles to the analysis path diagram to achieve comparative analysis of the dual-channel consistency of the same attribute observation variable.

[0056] The beneficial effects of the present invention are:

[0057] This paper introduces the structural equation model for the first time, constructing a structural equation model for the dual-polarization radar transmit channel and a consistency test analysis path diagram. Using radar operating status data and a path analysis method, this study proposes a daily quantile pairing test and a daily quantile-to-daily quantile regression method to analyze the consistency of the dual-polarization radar transmit channels. This method intuitively reveals the dynamic consistency characteristics of the dual-channel influence during the dual-polarization radar's operating state. This method can be used to monitor the consistency of the dual-polarization radar's transmit channels in real time, allowing for timely adjustment of radar system parameters and improving the radar system's observation capabilities. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 A schematic diagram of a dual-channel transmission of a general dual-polarization radar according to the prior art is shown.

[0059] Figure 2 A flow chart of a method for checking consistency of dual-polarization radar transmission dual channels according to an embodiment of the present invention is shown.

[0060] Figure 3 A schematic diagram of a dual-polarization radar transmitting dual-channel amplitude consistency structural equation model according to an embodiment of the present invention is shown.

[0061] Figure 4 A schematic diagram of a dual-polarization radar transmitting dual-channel consistency analysis path diagram and an observed variable relationship diagram according to an embodiment of the present invention is shown.

[0062] Figure 5 The optimal path coefficient calculation result of the daily quantile-to-daily quantile regression model of a dual-polarization radar transmit peak power according to an embodiment of the present invention is shown.

[0063] Figure 6 A schematic diagram of the results of configuring the dual-channel optimal path coefficients of the analysis path diagram of the peak power transmission of a dual-polarization radar according to an embodiment of the present invention is shown.

[0064] Figure 7 A schematic diagram shows the results of configuring the dual-channel optimal path coefficient for the analysis path diagram of three daily quantiles of the average transmit power of a dual-polarization radar according to an embodiment of the present invention, where (a), (b), and (c) represent the 0.25 daily quantile, the 0.50 daily quantile, and the 0.75 daily quantile, respectively.

[0065] Figure 8The structure diagram of a dual-polarization radar transmission dual-channel consistency verification system according to an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0066] The following describes the embodiments of the present invention through specific examples. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments. The details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the following embodiments and features in the embodiments can be combined with each other unless they conflict.

[0067] The specific implementation of the present invention is further described in detail below with reference to the accompanying drawings and examples.

[0068] The embodiment of the present invention provides a method for checking the consistency of dual-polarization radar transmission dual channels. Figure 1 FIG. 1 is a schematic diagram of a dual-channel transmission of a general dual-polarization radar in the prior art.

[0069] Figure 1 In the system, the RF signal output by the transmitter is split into two equal paths by a power splitter and transmitted to the radar antenna via horizontal and vertical channel feeders, respectively. A duplexer is installed on each of the horizontal and vertical channel feeders. Simultaneously, the radar status monitoring unit and the antenna status monitoring unit measure the transmit power at the transmitter and antenna power at the antenna in real time, respectively. The radar transmitter generates RF electromagnetic waves (typically in the microwave band). The power splitter splits the output of the radar transmitter into two equal paths, which are fed into the horizontal and vertical channels, respectively. This achieves the core requirement of dual-polarization radar: simultaneous transmission of RF electromagnetic waves in two polarization directions. The power splitter ensures amplitude and phase consistency between the two signals to avoid polarization deviation. Each polarization channel (horizontal / vertical) is equipped with a duplexer. During the transmit phase, the duplexer allows the signal to pass from the transmit channel to the antenna while isolating the receive path to prevent the transmitted signal from directly entering the receiver and causing damage. During the receive phase, the duplexer directs the echo signal received by the antenna to the receiver, isolating the transmit path and preventing interference. The duplexer must have high isolation to ensure that transmission and reception processes do not interfere with each other. The horizontal channel processes horizontally polarized signals, while the vertical channel processes vertically polarized signals. The antenna radiates the two polarized signals into space and captures the echo signal reflected by the target, separating it into horizontal and vertical polarization components. The radar transmitter status monitoring unit monitors transmitter power output, frequency stability, and other parameters in real time to ensure transmitted signal quality. The antenna status monitoring unit monitors antenna power and other indicators.

[0070] See also Figure 2The dual-polarization radar transmission dual-channel consistency verification method includes the following steps S10 to S40.

[0071] S10: Construct a dual-polarization radar transmitting dual-channel structural equation model and radar operating status data;

[0072] In this embodiment, the dual-polarization radar transmit dual-channel structural equation model is a statistical analysis model based on linear regression, factor analysis and other methods for analyzing the path relationship between complex variables. Figure 3 As shown in the figure, the dual-polarization radar transmitting dual-channel structural equation model includes a structural model and a measurement model. The modeling process is driven by theoretical assumptions and can simultaneously quantify the direct and indirect causal relationships between multiple variables. Figure 3 The structure model includes a transmitter, horizontal channel, vertical channel, and antenna. Arrows indicate the path connections between the models. The amplitude consistency measurement model includes a transmitter measurement unit and an antenna measurement unit. The transmitter measurement unit is used to obtain transmitter measurement indicators, and the antenna measurement unit is used to obtain antenna measurement indicators.

[0073] In some embodiments, the transmitter measurement index includes two radar transmitter observation variables, namely radar transmitter observation variable one and radar transmitter observation variable two, and the antenna measurement index includes four antenna observation variables, namely antenna horizontal channel observation variable one, antenna horizontal channel observation variable two, antenna vertical channel observation variable one and antenna vertical channel observation variable two.

[0074] Exemplarily, radar transmitter observation variable one and radar transmitter observation variable two are respectively the transmission peak power and the transmission average power, and antenna horizontal channel observation variable one, antenna horizontal channel observation variable two, antenna vertical channel observation variable one and antenna vertical channel observation variable two are respectively the horizontal channel antenna peak power, the vertical channel antenna peak power, the horizontal channel antenna average power and the vertical channel antenna average power.

[0075] It should be noted that the number of observed variables and their corresponding indicators are merely examples and are not intended to limit the present invention. In other embodiments, other indicators may be included. The number of observed variables and their corresponding indicators may be appropriately selected based on the requirements of different radar application scenarios. For example, the observed variables of a radar transmitter primarily focus on its signal generation, power output, and operational stability. The observed variables of a radar transmitter can be reasonably combined from the following observation variables (including one or more combinations):

[0076] 1) Transmitting power: Monitor the instantaneous value, average value and fluctuation range of the transmitter output power to ensure that it meets the design requirements (such as peak power and average power).

[0077] 2) Operating frequency: Monitor the carrier frequency stability of the transmitted signal to prevent frequency drift or harmonic interference.

[0078] 3) Pulse parameters: including pulse width (directly affects distance resolution and maximum detection distance) and pulse repetition frequency (affects maximum unambiguous distance and speed measurement capability).

[0079] 4) Modulation characteristics: including linear frequency modulation slope, phase encoding accuracy, etc., to ensure that the signal waveform meets the design.

[0080] 5) Efficiency and loss parameters: including transmitter efficiency (output power / input power), heat sink temperature, and power supply voltage / current fluctuations.

[0081] 6) Fault indication parameters: including high voltage power supply status, cooling system status, over-temperature / over-current / over-voltage alarm signals.

[0082] The observation variables of the antenna focus on electromagnetic wave radiation efficiency, polarization characteristics, and mechanical state. In addition to the four observation variables listed above, the following observation variables can also be reasonably combined (the combination method includes one or any combination of them):

[0083] 1) Standing Wave Ratio: reflects the matching degree between the antenna and the feeder. A standing wave ratio > 2 may indicate a fault in the antenna or feeder.

[0084] 2) Polarization characteristics:

[0085] Polarization isolation: the amount of signal leakage between horizontal and vertical polarization channels (e.g., dual-polarization radar requires isolation > 30dB);

[0086] Cross-polarization discrimination: A measure of an antenna's ability to reject signals with undesired polarizations.

[0087] 3) Directional parameters:

[0088] Beam: 3dB beam width, affecting angular resolution;

[0089] Pointing accuracy: The deviation between the actual pointing direction of the antenna beam and the theoretical pointing direction.

[0090] 4) Gain: Monitor the antenna's radiation efficiency to ensure that the gain meets the design value (e.g., above 30dBi).

[0091] 5) Impedance matching: The degree of matching between the input impedance and the characteristic impedance of the feeder (such as 50Ω) to avoid reflection loss.

[0092] 6) Radiation efficiency: The ratio of the actual radiated power of the antenna to the input power, reflecting energy loss (such as conductor / dielectric loss).

[0093] 7) Mechanical status: antenna array flatness, drive system status (such as torque and speed of azimuth / pitch motors).

[0094] 8) Environmental adaptability: Radome’s wave transmittance, surface icing / snow conditions, and wind resistance (such as wind speed monitoring).

[0095] In some embodiments, considering that weather radars in the global severe weather monitoring service system observe and operate in a certain mode, for example, a dual-polarization S-band weather radar primarily observes in precipitation mode, which completes a standard volume scan every six minutes. The status monitoring unit generates radar operating status data every six minutes, and the operating status data is stored daily as a log text file. Therefore, the operating status log text content of the dual-polarization S-band weather radar in the study area from February 2018 to January 2019 is collected and converted into analyzable data. The aforementioned parameters in the analyzable data are extracted to construct analyzable radar operating status data.

[0096] S20: Determine the dual-channel consistency analysis path diagram for dual-polarization radar transmission.

[0097] In this embodiment, a path analysis method is used to determine the consistency analysis path diagram for dual-polarization radar transmission dual-channels. Path analysis is a specific form of structural equation modeling for processing continuous variables. Path analysis is a commonly used data mining method that focuses on direct paths between variables. This paper analyzes the variable relationships in the dual-polarization weather radar transmission dual-channel measurement model to determine the direct or indirect impact of one or more independent variables on the dependent variable. By calculating path coefficients, the dynamic and static characteristics between variables can be concisely and intuitively described and quantified, thereby understanding how the variables influence each other.

[0098] In some embodiments, a dual-polarization radar transmit dual-channel consistency analysis path diagram is determined based on a path analysis method, and the analysis path diagram is used to characterize the relationship between observation variables, such as Figure 4 As shown, when the radar transmitter observation variable 1 and the radar transmitter observation variable 2 are regarded as two independent variables, the observation variable relationship represented by the analysis path diagram includes:

[0099] Difference evaluation of two independent samples of antenna horizontal channel observation variable 1 and antenna vertical channel observation variable 1;

[0100] Difference evaluation of two independent samples of antenna horizontal channel observation variable 2 and antenna vertical channel observation variable 2;

[0101] The characteristic relationship of radar transmitter observation variable 1 as the independent variable, antenna horizontal channel observation variable 1 and antenna vertical channel observation variable 1 as the dependent variables respectively;

[0102] The average transmit power is used as the independent variable, and the antenna horizontal channel observation variable two and the antenna vertical channel observation variable two are used as the characteristic relationship of the dependent variables.

[0103] For example, when the radar transmitter observation variable 1 and the radar transmitter observation variable 2 are the transmission peak power and the transmission average power respectively, the antenna horizontal channel observation variable 1, the antenna horizontal channel observation variable 2, the antenna vertical channel observation variable 1 and the antenna vertical channel observation variable 2 are the horizontal channel antenna peak power, the vertical channel antenna peak power, the horizontal channel antenna average power and the vertical channel antenna average power respectively, assuming that the power divider performs a standard equal division on the radar transmission power and regards the transmission peak power and the transmission average power as two independent variables, there are four types of observation variable relationships in the dual-channel amplitude consistency measurement model of the dual-polarization weather radar transmission, such as Figure 4 As shown in Figure 2, the four observed variable relationships are:

[0104] (1) Difference evaluation of two independent samples of horizontal channel antenna peak power and vertical channel antenna peak power;

[0105] (2) Difference evaluation of two independent samples of horizontal channel antenna average power and vertical channel antenna average power;

[0106] (3) Characteristic relationship between transmit peak power as the independent variable, horizontal channel antenna peak power and vertical channel antenna peak power as the dependent variables;

[0107] (4) The characteristic relationship of the average transmit power as the independent variable, the average horizontal channel antenna power and the average vertical channel antenna power as the dependent variables.

[0108] S30: The daily quantile pairing method and radar operating status data are used to test the significance of the observed variables of the same attribute in the two antenna channels.

[0109] In some embodiments, based on the characteristics of the constructed radar operation status historical data stored on a daily basis, it is proposed to use the daily quantile method to study and analyze the data, which can achieve data dimensionality reduction and improve efficiency, and effectively analyze the complex relationship characteristics between variables. The daily quantile formula is as follows:

[0110] set up Represents the observed variable x t Daily distribution (24 hours), The daily α quantile q at time t d (α) is determined by P Given, the daily α quantile distribution is determined by the following formula:

[0111]

[0112] in is the daily distribution function of the observed variable The inverse function of Q d (α) is the daily α quantile distribution; d is 24 hours per day, and N is the number of days.

[0113] For example, based on the daily quantile method, this embodiment proposes using the transmit dual-channel antenna peak power and transmit dual-channel antenna average power, and using the daily quantile paired Wilcoxon test (daily quantile paired method) to test the significance of the difference in the transmit dual-channel impact on amplitude consistency. The transmit dual-channel antenna peak power and transmit dual-channel antenna average power are separately evaluated to evaluate the difference in dual-channel data.

[0114] Specifically, this embodiment proposes a daily quantile paired Wilcoxon test to evaluate the significance of the differences in the values ​​measured in the antenna measurement model: the antenna peak power amplitude and the antenna average power amplitude, respectively, where both the horizontal and vertical channels are affected. Therefore, based on the assumptions of the transmitted peak power, transmitted average power, gain and loss, the significance of the difference in antenna power amplitude (antenna peak power, antenna average power) can be calculated. It can be expressed as:

[0115]

[0116] in, is the daily α quantile paired test function of the observed variables of the antenna horizontal channel and the antenna vertical channel, is the daily α quantile distribution of the antenna horizontal channel, is the daily alpha quantile distribution of the antenna vertical channel.

[0117] S40: Determine whether there is a significant difference. If not, exit the test. If yes, proceed to step S50.

[0118] In this embodiment, the significance difference value is compared with a set threshold. Generally, a difference is considered to exist when the significance difference value is less than 0.05, a significant difference is considered to exist when the significance difference value is less than 0.01, and a highly significant difference is considered to exist when the significance difference value is less than 0.001. Therefore, when the significance difference value is less than 0.01, it is considered that there is a significant difference and step S50 is executed. Otherwise, it is considered that there is no significant difference and the current round of testing is exited.

[0119] S50: Taking radar transmitter observation variables as independent variables and antenna observation variables as dependent variables, the dual-channel optimal path coefficients of the same attribute observation variables are calculated using the daily quantile-to-daily quantile regression method and radar operation status data.

[0120] This embodiment expands on the quantile-to-quantile regression method. Based on the characteristics of the historical data of radar operation status, it proposes to use the daily quantile-to-daily quantile regression method (still a non-parametric quantile regression method) to calculate the path coefficient of the radar transmission dual-channel amplitude on the historical data, thereby performing a consistency analysis on the empirical results.

[0121] In some embodiments, calculating a dual-channel optimal path coefficient of an observation variable of the same attribute using a daily quantile-to-daily quantile regression method and radar operating status data includes:

[0122] Build a daily quantile-to-daily quantile regression model, expressed as:

[0123]

[0124] in, represents the daily α quantile distribution of the antenna observation variable; represents the daily α quantile distribution of the transmitter observation variable; λ α represents the optimal path coefficient of the daily α quantile of the horizontal channel or vertical channel; μ d (α) represents the error affected by the horizontal channel or vertical channel.

[0125] The optimal path coefficient λ of the daily quantile α affected by the horizontal channel or vertical channel is estimated by the least squares method α .

[0126] For example, the optimal path coefficient λ of the daily α quantile affected by the horizontal channel or vertical channel is estimated by the least squares method. α The steps include:

[0127] Step 1: Collect daily and Data, the number of days ranges from d=1,2,…,N.

[0128] Step 2, assuming the model is a univariate linear regression without intercept:

[0129]

[0130] in, is the error term.

[0131] Step 3: Construct the least squares objective function to minimize the residual sum of squares:

[0132]

[0133] Step 4: Calculate the path coefficient λ α :

[0134] Calculate the numerator:

[0135] Calculate the denominator:

[0136] Calculate the estimated value of the path coefficient

[0137]

[0138] like Figure 5 Figure 2 shows the calculation results of the optimal path coefficient of the daily quantile-to-daily quantile regression model of a dual-polarization radar transmit peak power. Figure 5 In the figure, the horizontal axis x is the transmitter peak power, and the vertical axis y is the antenna peak power. The upper and lower curves are the first curve and the second curve respectively. The first curve is used to describe the relationship between the horizontal channel antenna peak power and the transmitter peak power. Its linear equation is y = 0.01 + 0.33 x. The second curve is used to describe the relationship between the vertical channel antenna peak power and the transmitter peak power. Its linear equation is y = -0.01 + 0.33 x. Both the first curve and the second curve satisfy R 2 =1, indicating that the antenna peak power of the horizontal channel and the vertical channel has a strict linear relationship with the transmitter peak power, and the fitting degree is perfect (no error).

[0139] S60: Configure the optimal path coefficient of the dual-channel based on the analysis path diagram, and compare and analyze the consistency of the dual channels at different daily quantiles.

[0140] In this embodiment, please combine Figure 4 , the dual-channel optimal path coefficient can be used to characterize the relationship between the four observed variables. For example, the characteristic relationship of the transmission peak power as the independent variable, the horizontal channel antenna peak power and the vertical channel antenna peak power as the dependent variables, respectively, and the path coefficient λ of the daily quantile α that can be affected by the horizontal channel or the vertical channel α to characterize.

[0141] By comparing the optimal path coefficients of the two channels at different daily quantiles, the consistency of the two channels can be analyzed as follows:

[0142] Calculate the difference Δλ between the path coefficients of the H channel and the V channel at each daily α quantile α :

[0143]

[0144] in, and Optimal path coefficients for daily alpha quantiles representing the influence of horizontal and vertical channels.

[0145] Use paired t-test or Wilcoxon signed-rank test to verify whether the path coefficients of the horizontal channel and the vertical channel are significantly different, such as setting a threshold to determine Δλ α Whether it is within the range of the set threshold, if so, it is considered that the dual-channel consistency requirement is met, if not, it is considered that the dual-channel consistency requirement is not met.

[0146] In addition, the dual-channel consistency can also be analyzed by using the Kappa consistency coefficient, intraclass correlation coefficient (ICC), and consistency correlation coefficient (CCC) between the path coefficients of the horizontal channel and the vertical channel at different daily quantiles to determine the dual-channel consistency.

[0147] In an exemplary embodiment, Figure 6 As shown in Figure 1, it is a schematic diagram of the optimal dual-channel path coefficient configuration result for the analysis path diagram of the peak power of a dual-polarization radar. Figure 6 It can be seen that the optimal path coefficients between the transmitter and the horizontal channel and the vertical channel are both 0.5, and the optimal path coefficients between the antenna and the horizontal channel and the vertical channel are both 0.33, which indicates that Figure 6 In the results shown, both channels are consistent.

[0148] In another exemplary embodiment, Figure 7 As shown in Figure 1, a schematic diagram of the optimal dual-channel path coefficient results is shown for the analysis path diagram of the three daily quantiles of the average transmission power of a dual-polarization radar. Figure 7 (a), (b) and (c) represent the 0.25-day quantile, 0.50-day quantile and 0.75-day quantile respectively. Figure 7 It can be seen that (a) and (c) meet the requirements of dual-channel consistency, while in (b), the difference in path coefficients between the horizontal channel and the vertical channel of the antenna is 0.05. At this time, it can be compared with the above difference value of 0.05 according to the set threshold. If it is greater than the set threshold, it means that it does not meet the requirements of dual-channel consistency. If it is less than or equal to the set threshold, it means that it meets the requirements of dual-channel consistency.

[0149] The present invention also provides a dual-polarization radar transmission dual-channel consistency test system, please refer to Figure 8 , the system comprises:

[0150] The model and data construction module 801 is configured to construct a dual-polarization radar transmitting dual-channel structural equation model and radar operating status data;

[0151] A path analysis module 802 is configured to determine a dual-channel consistency analysis path diagram for transmitting a dual-polarization radar;

[0152] The significant difference analysis module 803 is configured to use the daily quantile pairing method and radar operation status data to test the significant difference of the same attribute observation variables of the antenna dual channels;

[0153] The path coefficient calculation module 804 is configured to calculate the dual-channel optimal path coefficient of the same attribute observation variable using the radar transmitter observation variable as the independent variable and the antenna observation variable as the dependent variable using the daily quantile-to-daily quantile regression method and the radar operation status data when there is a significant difference;

[0154] The dual-channel consistency analysis module 805 is configured to configure the dual-channel optimal path coefficient based on the analysis path diagram, and compare the dual-channel optimal path coefficients at different daily quantiles to analyze the dual-channel consistency.

[0155] In some embodiments, the significant difference analysis module is further configured to:

[0156] set up Represents the observed variable x t The daily distribution of The daily α quantile q at time t d (α) by Given, the daily α quantile distribution is determined by the following formula:

[0157]

[0158] in, is the daily distribution function of the observed variable The inverse function of Q d (α) is the daily α quantile distribution; d is 24 hours per day, and N is the number of days;

[0159] The daily quantile pairing method is used to calculate the significant difference value of the same attribute observation variable of the antenna dual channel The specific calculation process is expressed as:

[0160]

[0161] in, is the daily α quantile paired test function of the observed variables of the antenna horizontal channel and the antenna vertical channel, is the daily α quantile distribution of the antenna horizontal channel, is the daily alpha quantile distribution of the antenna vertical channel.

[0162] In some embodiments, the path coefficient calculation module is further configured to:

[0163] Establish a daily quantile-to-daily quantile regression model, expressed as:

[0164]

[0165] in, represents the daily α quantile distribution of the antenna observation variable; represents the daily α quantile distribution of the transmitter observation variable; λ α represents the optimal path coefficient of the daily α quantile of the horizontal channel or vertical channel; μ d (α) represents the error affected by the horizontal channel or vertical channel;

[0166] The optimal path coefficient λ of the daily α quantile affected by the horizontal channel or vertical channel is estimated by the least squares method α .

[0167] The dual-channel consistency analysis module is further configured to: configure the optimal path coefficient calculation results of different daily quantiles to the analysis path diagram to achieve comparative analysis of the dual-channel consistency of the same attribute observation variable.

[0168] It should be noted that the dual-polarization radar transmission dual-channel consistency verification system and the previously described method belong to the same technical concept, have the same technical principles and beneficial effects, and therefore will not be described in detail here.

[0169] The above embodiments are only used to illustrate the present invention, and are not intended to limit the present invention. Ordinary technicians in the relevant technical field may make various changes and modifications without departing from the spirit and scope of the present invention. Therefore, all equivalent technical solutions also fall within the scope of the present invention. The scope of patent protection of the present invention should be defined by the claims.

Claims

1. A dual-polarization radar transmission dual-channel consistency test method, characterized in that: The method comprises: Construct a dual-polarization radar transmitting dual-channel structural equation model and radar operating status data; Determine the dual-channel consistency analysis path diagram for dual-polarization radar transmission; The daily quantile pairing method and radar operation status data were used to test the significant differences of the same attribute observation variables of the antenna dual channels. When there are significant differences, the radar transmitter observation variables are used as independent variables and the antenna observation variables are used as dependent variables. The dual-channel optimal path coefficients of the same attribute observation variables are calculated using the daily quantile-to-daily quantile regression method and radar operation status data. The dual-channel optimal path coefficient is configured based on the analysis path diagram, and the dual-channel consistency at different daily quantiles is compared and analyzed.

2. The method according to claim 1, wherein The dual-polarization radar transmitting dual-channel structural equation model includes a transmitter, a horizontal channel, a vertical channel, an antenna, a transmitter measurement unit, and an antenna measurement unit; wherein the transmitter is associated with the antenna through the horizontal channel and the vertical channel respectively, the transmitter measurement unit is used to obtain transmitter measurement indicators, and the antenna measurement unit is used to obtain antenna measurement indicators.

3. The method according to claim 2, wherein The transmitter measurement index includes two radar transmitter observation variables, namely radar transmitter observation variable one and radar transmitter observation variable two; the antenna measurement index includes four antenna observation variables, namely antenna horizontal channel observation variable one, antenna horizontal channel observation variable two, antenna vertical channel observation variable one and antenna vertical channel observation variable two.

4. The method according to claim 3, wherein A dual-polarization radar transmission dual-channel consistency analysis path diagram is determined based on the path analysis method. The analysis path diagram is used to characterize the relationship between observation variables. When the radar transmitter observation variable 1 and the radar transmitter observation variable 2 are regarded as two independent variables, the observation variable relationship represented by the analysis path diagram includes: Difference evaluation of two independent samples of antenna horizontal channel observation variable 1 and antenna vertical channel observation variable 1; Difference evaluation of two independent samples of antenna horizontal channel observation variable 2 and antenna vertical channel observation variable 2; The characteristic relationship of radar transmitter observation variable 1 as the independent variable, antenna horizontal channel observation variable 1 and antenna vertical channel observation variable 1 as the dependent variables respectively; The characteristic relationship of radar transmitter observation variable two as the independent variable, antenna horizontal channel observation variable two and antenna vertical channel observation variable two as the dependent variables respectively.

5. The method according to claim 1, wherein The daily quantile pairing method and radar operating status data were used to test the significant differences of the same attribute observation variables of the antenna dual channels, including: set up Represents the observed variable x t The daily distribution of The daily α quantile q at time t d (α) by Given, the daily α quantile distribution is determined by the following formula: in, is the daily distribution function of the observed variable The inverse function of Q d (α) is the daily α quantile distribution; d is 24 hours per day, and N is the number of days; The daily quantile pairing method is used to calculate the significant difference value of the same attribute observation variable of the antenna dual channel The specific calculation process is expressed as: in, is the daily α quantile paired test function of the observed variables of the antenna horizontal channel and the antenna vertical channel, is the daily α quantile distribution of the antenna horizontal channel, is the daily alpha quantile distribution of the antenna vertical channel.

6. The method according to any one of claims 1 to 5, characterized in that When there are significant differences, the radar transmitter observation variables are used as independent variables and the antenna observation variables are used as dependent variables. The dual-channel optimal path coefficients of the same attribute observation variables are calculated using the daily quantile-to-daily quantile regression method and radar operation status data, including; Establish a daily quantile-to-daily quantile regression model, expressed as: in, represents the daily α quantile distribution of the antenna observation variable; represents the daily α quantile distribution of the transmitter observation variable; λ α represents the optimal path coefficient of the daily α quantile of the horizontal channel or vertical channel; μ d (α) represents the error affected by the horizontal channel or vertical channel; The optimal path coefficient λ of the daily α quantile affected by the horizontal channel or vertical channel is estimated by the least squares method α .

7. The method according to claim 6, wherein The calculation results of the optimal path coefficients of different daily quantiles are configured to the analysis path diagram to achieve the dual-channel consistency of the comparative analysis of the same attribute observation variable.

8. A dual-polarization radar transmission dual-channel consistency verification system, characterized in that: The system comprises: A model and data construction module is configured to construct a dual-polarization radar transmitting dual-channel structural equation model and radar operating status data; A path analysis module is configured to determine a dual-channel consistency analysis path diagram for dual-polarization radar transmission; The significant difference analysis module is configured to use the daily quantile pairing method and radar operation status data to test the significant differences of the same attribute observation variables of the antenna dual channels; The path coefficient calculation module is configured to calculate the dual-channel optimal path coefficient of the same attribute observation variable using the daily quantile-to-daily quantile regression method and radar operation status data when there is a significant difference. The radar transmitter observation variable is used as the independent variable and the antenna observation variable is used as the dependent variable. The dual-channel consistency analysis module is configured to configure the dual-channel optimal path coefficient based on the analysis path diagram, and compare the dual-channel optimal path coefficients at different daily quantiles to analyze the dual-channel consistency.

9. The system according to claim 8, wherein The significant difference analysis module is further configured to: set up Represents the observed variable x t The daily distribution of The daily α quantile q at time t d (α) by Given, the daily α quantile distribution is determined by the following formula: in, is the daily distribution function of the observed variable The inverse function of Q d (α) is the daily α quantile distribution; d is 24 hours per day, and N is the number of days. The daily quantile pairing method is used to calculate the significant difference value of the same attribute observation variable of the antenna dual channel The specific calculation process is expressed as: in, is the daily α quantile paired test function of the observed variables of the antenna horizontal channel and the antenna vertical channel, is the daily α quantile distribution of the antenna horizontal channel, is the daily alpha quantile distribution of the antenna vertical channel.

10. The system according to claim 9, wherein: The path coefficient calculation module is further configured to: Establish a daily quantile-to-daily quantile regression model, expressed as: in, represents the daily α quantile distribution of the antenna observation variable; represents the daily α quantile distribution of the transmitter observation variable; λ α represents the optimal path coefficient of the daily α quantile of the horizontal channel or vertical channel; μ d (α) represents the error affected by the horizontal channel or vertical channel; The optimal path coefficient λ of the daily α quantile affected by the horizontal channel or vertical channel is estimated by the least squares method α ; The dual-channel consistency analysis module is further configured to: configure the optimal path coefficient calculation results of different daily quantiles to the analysis path diagram to achieve comparative analysis of the dual-channel consistency of the same attribute observation variable.

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