Calibration method and device for compact polarimetric SAR based on active calibrator

Abstract

The application discloses a compact polarimetric SAR calibration method and device based on active calibrators and belongs to the technical field of signal processing. The method comprises the following steps: a compact polarimetric SAR system calibration model is established based on a Freeman model; the characteristic matrix of three active calibrators with different polarization characteristics is substituted into the system model, and the receiving channel imbalance, the receiving channel crosstalk, the transmitting channel crosstalk and the Faraday rotation angle are respectively analyzed and calculated; and the total electron content data of the ionosphere provided by the global navigation satellite system is used to calculate the rough Faraday rotation angle, and the phase ambiguity of the Faraday rotation angle is deambiguated. The application only needs three active calibrators, combines the analytical calculation with GNSS auxiliary deambiguity, realizes the calibration of the compact polarimetric SAR system in the CTLR mode with high precision, low equipment quantity and simplified process, and has strong anti-noise and anti-calibrator self-error capabilities.

Description

Technical Field

[0001] This invention belongs to the field of signal processing technology, specifically relating to a simplified polarization SAR calibration method and apparatus based on an active calibrator. Background Technology

[0002] Synthetic Aperture Radar (SAR) with reduced polarization is widely used in remote sensing due to its advantages such as low system complexity, small data volume, and large observation swath. Among them, the Circular Transmit and Linear Receive (CTLR) mode, which uses circular polarization for transmission and orthogonal linear polarization for reception, is one of the mainstream reduced polarization operating modes. During the operation of a CTLR SAR system, the signal undergoes various distortions during transmission, propagation, and reception, including channel amplitude / phase imbalance, inter-channel crosstalk, and Faraday rotation effects. These distortions must be corrected through calibration to ensure the accuracy of subsequent polarization information interpretation.

[0003] Existing simplified polarimetric SAR calibration methods are mainly divided into distribution-target-based calibration schemes and point-target-based calibration schemes. Distribution-target-based calibration schemes (such as homogeneous surfaces) are simple to implement and low-cost, but their calibration accuracy is limited due to the instability of natural target characteristics and modeling errors. Point-target-based calibration schemes, on the other hand, use artificial calibrators with known stable polarization characteristics (such as corner reflectors and active calibrators), achieving higher calibration accuracy. However, current point-target-based CTLR mode calibration methods still have significant limitations. For example, some existing high-precision methods typically require the deployment of four or more different types of calibrators (such as using trihedral corner reflectors and active calibrators simultaneously), resulting in high equipment deployment and transportation costs and complex operation. Furthermore, some methods employ iterative optimization algorithms when solving distortion parameters, which are cumbersome and sensitive to initial values ​​and signal-to-noise ratio, hindering rapid engineering implementation. Other schemes, while simplifying the process, fail to fully utilize the high signal-to-noise ratio advantage of active calibrators or suffer from phase ambiguity when solving for the Faraday rotation angle, affecting the final calibration accuracy and reliability.

[0004] Therefore, there is an urgent need in this field for a CTLR mode reduced polarimetric SAR calibration method that can achieve high accuracy, require fewer devices, have a simple process, and effectively handle phase ambiguity. Summary of the Invention

[0005] To address the aforementioned technical problems, this invention provides a simplified polarimetric SAR calibration method and apparatus based on active calibrators. Utilizing the high signal-to-noise ratio advantage of active calibrators and the ingenious combination of their polarization feature matrices, only three active calibrators are used to achieve unbiased estimation of distortion parameters while ignoring noise. High-precision calibration is achieved while considering noise and the calibrator's own errors, and the calculation process is analytical and the processing flow is simple.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0007] A simplified polarimetric SAR calibration method based on an active calibrator, the method comprising:

[0008] Step 1: Based on the Freeman model, analyze the error sources of the simplified polarimetric SAR system and establish a calibration model for the CTLR mode simplified polarimetric SAR system.

[0009] Step 2: Substitute the characteristic matrices of three different but known polarization characteristic matrices of active calibrators into the calibration model, and calculate the analytical solutions for receiver channel imbalance, receiver channel crosstalk, transmitter channel crosstalk, and Faraday rotation angle with phase ambiguity, respectively, while ignoring amplitude and phase coefficients and noise.

[0010] Step 3: Using the Total Electron Quantity (TEC) data of the ionosphere provided by the Global Navigation Satellite System (GNSS), calculate the estimated Faraday rotation angle of the SAR imaging area, and de-ambiguously de-ambiguously de-ambiguously de-ambiguously de-ambiguously de-ambiguously de-ambiguously de-ambiguously de-calibrate the Faraday rotation angle with phase ambiguity.

[0011] Furthermore, the calibration model established in step 1 is as follows:

[0012] The system measurement is equal to a linear transformation matrix that includes system distortion and ionospheric Faraday rotation effect, applied to the product of the real ground target scattering matrix and the emitted electric field vector, then scaled by an independent amplitude and phase coefficient, and finally the system noise is added.

[0013] Furthermore, in step 2:

[0014] The first active scaler is used to select the HV channel;

[0015] The second active scaler is used to select the VH channel;

[0016] The third active scaler is used to select four polarization channels: HH, HV, VH, and VV. The phase of the HH and HV channels is 0°, and the phase of the VH and VV channels is 180°.

[0017] Furthermore, the calculation of analytical solutions in step 2 includes:

[0018] First, the analytical expression for the crosstalk in the receiving channel is calculated using the measurement equations of the three active calibrators;

[0019] Secondly, based on the analytical solution of the received channel crosstalk, the analytical expression of the transmitted channel crosstalk is derived;

[0020] Next, using the analytical solution of transmit channel crosstalk, the analytical expression for receive channel imbalance is derived;

[0021] Then, using the analytical solution of the unbalanced receiving channel, the analytical expression of crosstalk in the other receiving channel is derived;

[0022] Finally, using all the obtained parameters, an analytical expression for the Faraday rotation angle with phase ambiguity is derived.

[0023] Furthermore, the analytical expression for the Faraday rotation angle with phase ambiguity is obtained by taking the argument of a complex expression composed of the measurements of the three active calibrators, and its range is restricted to the interval from negative π / 2 to positive π / 2.

[0024] Furthermore, in step 3, the estimated value is calculated using the Faraday rotation angle physical model based on the operating frequency of the SAR system, the geomagnetic field strength of the imaging area, the angle parameter between the radar wave propagation direction and the geomagnetic field, and the total ionospheric electron quantity (TEC) data provided by GNSS.

[0025] Furthermore, step 3, the defuzzification process includes taking the Faraday rotation angle with phase fuzziness calculated in step 2 as the base value, taking the estimated value as a reference for the phase fuzziness period, determining the integer multiple of π to be superimposed by rounding, multiplying the integer multiple by π and adding it to the base value to obtain the final unfuzzy Faraday rotation angle.

[0026] On the other hand, the present invention provides a simplified polarization SAR calibration device based on an active calibrator, comprising:

[0027] The calibration model building module is used to analyze the error sources of the simplified polarimetric SAR system based on the Freeman model and to build a calibration model of the CTLR mode simplified polarimetric SAR system.

[0028] The analytical solution calculation module is used to substitute the characteristic matrices of three different but known polarization characteristic matrices of active calibrators into the calibration model, and calculate the analytical solutions for receiver channel imbalance, receiver channel crosstalk, transmitter channel crosstalk, and Faraday rotation angle with phase ambiguity, respectively, while ignoring amplitude and phase coefficients and noise.

[0029] The phase ambiguity resolution module is used to calculate the estimated Faraday rotation angle of the SAR imaging area using the total ionospheric electron quantity (TEC) data provided by the Global Navigation Satellite System (GNSS), and to resolve the phase ambiguity of the Faraday rotation angle based on the estimated value, thereby completing the calibration.

[0030] Thirdly, the present invention provides an electronic device, comprising: one or more processors; and a memory for storing one or more programs; wherein, when the one or more programs are executed by the one or more processors, the one or more processors implement the aforementioned simplified polarization SAR calibration method based on an active calibrator.

[0031] Fourthly, the present invention provides a computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, enable the processor to implement the aforementioned simplified polarization SAR calibration method based on an active calibrator.

[0032] The beneficial effects of this invention are as follows:

[0033] Simplified equipment deployment and reduced costs: Compared to existing solutions that require the use of multiple different types of calibrators (such as a combination of corner reflectors and active calibrators), this invention only requires the deployment of three active calibrators to complete the calibration of all core parameters, which significantly reduces the number, weight and transportation and deployment complexity of field calibration equipment, and lowers implementation costs.

[0034] High calibration accuracy: By cleverly designing the combination of polarization characteristic matrices of three active calibrators, unbiased analytical estimation of key distortion parameters such as receiver channel imbalance, receiver channel crosstalk, transmitter channel crosstalk, and Faraday rotation angle can be achieved under ideal noise-free conditions. Combining ionospheric TEC data provided by GNSS for Faraday rotation angle deambiguation effectively overcomes the impact of phase ambiguity on accuracy, ensuring high overall calibration accuracy.

[0035] The algorithm is concise and efficient: the entire calibration process is based on rigorous analytical derivation, and all distortion parameters are directly calculated through closed mathematical expressions, avoiding complex iterative optimization processes. The algorithm has good determinism, high computational efficiency, and is easy to implement in engineering and process quickly.

[0036] High robustness: Simulation analysis shows that the method maintains excellent estimation performance even in the presence of noise and a certain polarization error (APN) in the calibrator itself. Under typical signal-to-noise ratio conditions, the estimation errors of each parameter can be controlled at a low level, demonstrating good environmental adaptability and practical reliability. Attached Figure Description

[0037] Figure 1 This is a flowchart of the simplified polarization SAR calibration method based on an active calibrator according to the present invention;

[0038] Figure 2 This is the estimation result of the amplitude imbalance of the receiving channel in this invention;

[0039] Figure 3 This is the estimation result of the phase imbalance of the receiving channel in this invention;

[0040] Figure 4 This invention relates to receiver channel crosstalk. The estimation results of the amplitude;

[0041] Figure 5 This invention relates to receiver channel crosstalk. Phase estimation results;

[0042] Figure 6 This invention relates to receiver channel crosstalk. The estimation results of the amplitude;

[0043] Figure 7 This invention relates to receiver channel crosstalk. Phase estimation results;

[0044] Figure 8 This invention relates to transmission channel crosstalk. The estimation results of the amplitude;

[0045] Figure 9 This invention relates to transmission channel crosstalk. Phase estimation results;

[0046] Figure 10 The present invention relates to the Faraday rotation angle with phase ambiguity. The estimation error;

[0047] Figure 11 It is the Faraday rotation angle after phase ambiguity resolution in this invention. The estimation error;

[0048] Figure 12(a) shows the crosstalk in the receiving channel under noise. estimation error;

[0049] Figure 12(b) shows the crosstalk in the receiving channel under noise. estimation error;

[0050] Figure 12(c) shows the amplitude imbalance of the receiving channel under the influence of noise. estimation error;

[0051] Figure 12(d) shows the phase imbalance of the receiving channel under noise. estimation error;

[0052] Figure 12(e) shows the crosstalk in the transmission channel under noise. estimation error;

[0053] Figure 12(f) shows the Faraday rotation angle under the influence of noise. estimation error;

[0054] Figure 13(a) shows the crosstalk in the receiving channel under the influence of the calibrator's own error. estimation error;

[0055] Figure 13(b) shows the crosstalk in the receiving channel under the influence of the calibrator's own error. estimation error;

[0056] Figure 13(c) shows the amplitude imbalance of the receiving channel under the influence of the calibrator's own error. estimation error;

[0057] Figure 13(d) shows the phase imbalance of the receiving channel under the influence of the calibrator's own error. estimation error;

[0058] Figure 13(e) shows the crosstalk in the transmit channel under the influence of the calibrator's own error. estimation error;

[0059] Figure 13(f) shows the Faraday rotation angle under the influence of the calibrator's own error. Estimation error. Detailed Implementation

[0060] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0061] like Figure 1 As shown, this invention discloses a simplified polarimetric SAR calibration method based on an active calibrator, comprising the following steps:

[0062] Step 1: Based on the Freeman model, analyze the error sources of the simplified polarimetric SAR system and establish a calibration model for the CTLR mode simplified polarimetric SAR system.

[0063] Step 2: Substitute the characteristic matrices of the three known polarization characteristic matrices of the active calibrators into the calibration model, and calculate the imbalance of the receiving channel respectively, ignoring the amplitude and phase coefficients and noise. Crosstalk in the receiving channel and Transmission channel crosstalk and Faraday rotation angle with phase ambiguity The analytical solution;

[0064] Step 3: Using the Total Electron Quantity (TEC) data of the ionosphere provided by the Global Navigation Satellite System (GNSS), calculate the estimated Faraday rotation angle of the SAR imaging area, and then adjust the Faraday rotation angle obtained in Step 2 for areas with phase ambiguity based on the estimated value. Defuzzification is performed to complete the calibration.

[0065] The specific implementation process of step 1 is as follows:

[0066] Considering the distortion of the radar transceiver system and the effects of ionosphere and noise during electromagnetic wave propagation, based on the Freeman model, the system measurement value is set to be equal to a linear transformation matrix that includes system distortion and ionospheric Faraday rotation effects. This matrix is ​​applied to the product of the actual ground target scattering matrix and the transmitted electric field vector, then scaled by an independent amplitude and phase coefficient, and finally the system noise is added. Specifically, the following CTLR mode simplified polarimetric SAR system model can be established:

[0067] ,

[0068] In the formula, and These are the measured scattering vectors received with horizontal and vertical polarization, respectively. It is related to the slant distance Angle of incidence And the amplitude and phase coefficients related to the target scattering characteristics, The phase coefficient is represented by j, which is the imaginary unit. It takes into account the effects of factors such as transmit power, transmit and receive gain, link transmission loss, target backscattering characteristics, and the phase delay of the entire link. and This refers to the crosstalk between the two receiving channels. Due to unbalanced receiving channels, Represents the Faraday rotation angle. , , and These are the components of the true scattering matrix. and These are the emitted electric field vectors for right-handed and left-handed circularly polarized waves, respectively. To prevent crosstalk between left-hand circularly polarized waves when transmitting right-hand circularly polarized waves, and These are the noise levels for the horizontal and vertical channels, respectively.

[0069] The specific implementation process of step 2 is as follows:

[0070] In this invention, a first active scaler is used to select the HV channel; a second active scaler is used to select the VH channel; and a third active scaler is used to select four polarization channels: HH, HV, VH, and VV. The HH and HV channels have a phase of 0°, and the VH and VV channels have a phase of 180°. Based on this, the characteristic matrices of the three active scalers are as follows:

[0071] ,

[0072] For ease of calculation, amplitude and phase coefficients are ignored. Substituting the characteristic matrices of the three active calibrators into the simplified polarimetric SAR system calibration model, along with the noise term, yields the measurement scattering vectors for the two channels of the corresponding calibrators:

[0073] ,

[0074] ,

[0075] ,

[0076] In the formula, , , , , and These are the measured scattering vectors received by three active calibrators with horizontal and vertical polarization, respectively.

[0077] By combining the six equations for measuring the scattering vector using the three active calibrators, analytical solutions for the five distortion parameters can be calculated:

[0078] Receive channel crosstalk The analytical solution is:

[0079] ,

[0080] Transmit channel crosstalk The analytical solution is:

[0081] ,

[0082] Receive channel imbalance The analytical solution is:

[0083] ,

[0084] Receive channel crosstalk The analytical solution is:

[0085] ,

[0086] Faraday rotation angle with phase ambiguity The analytical solution is:

[0087] ,

[0088] In the above formula This represents taking the argument of a complex number, with values ​​ranging from 1 to 2. Therefore, the Faraday rotation angle with phase ambiguity calculated using the above formula is given. The range can only be within Between, when This will result in phase ambiguity.

[0089] The specific implementation process of step 3 is as follows:

[0090] To address the Faraday rotation angle with phase ambiguity obtained in step 2... To make corrections, the local coarse Faraday rotation angle is first calculated using TEC data provided by the Global Navigation Satellite System (GNSS). :

[0091] ,

[0092] In the formula, It is a constant with a magnitude of The unit is , This indicates the operating frequency of the SAR system, in units of... , This represents magnetic flux density, and its unit is... , This represents the angle between the direction of the incident wave's normal and the direction of the Earth's magnetic field. This represents the angle between the direction of the incident wave normal and the direction perpendicularly downwards from the satellite. This indicates that the magnetic field parameters are calculated based on an altitude of 400km. This represents the total electron content of the ionosphere, measured in units of... , .

[0093] The Faraday rotation angle with phase ambiguity obtained in step 2 can be obtained by combining the following formula. Defuzzing:

[0094] ,

[0095] In the formula, This represents the Faraday rotation angle after defuzzification. The Faraday rotation angle obtained in step 2 is fuzzy. Used to round floating-point numbers to the nearest integer.

[0096] This completes the entire process of simplified polarimetric SAR calibration.

[0097] The theoretical model of this invention is verified and analyzed below based on simulation results. First, the calibration accuracy of the five distortion parameters under the condition of ignoring noise is simulated and analyzed.

[0098] Set the amplitude imbalance range of the receiving channel to... Each step The remaining distortion parameters are set as follows: , , , , Utilizing the channel imbalance from step 2 The analytical solution estimates the amplitude imbalance of the received channel and compares it with the true value. The result is as follows: Figure 2 As shown, the estimated value coincides with the true value curve, further verifying the effectiveness of the present invention.

[0099] Set the phase imbalance range of the receiving channel to... Each step The remaining distortion parameters are set as follows: , , , , Utilizing the channel imbalance from step 2 The phase estimation of the analytical solution for the receiving channel phase imbalance is compared with the true value, and the results are as follows: Figure 3 As shown, the estimated value coincides with the true value curve, further verifying the effectiveness of the present invention.

[0100] Set receive channel crosstalk The range of amplitude is Each step The remaining distortion parameters are set as follows: , , , , , Utilize step 2 to receive channel crosstalk. Analytical solution amplitude estimation of receive channel crosstalk The amplitude was compared with the true value, and the result was as follows: Figure 4 As shown, the estimated value coincides with the true value curve, further verifying the effectiveness of the present invention.

[0101] Set receive channel crosstalk Phase range is Each step The remaining distortion parameters are set as follows: , , , , , Utilize step 2 to receive channel crosstalk. Phase estimation of analytical solution for receiver channel crosstalk Phase, and compared with the true value, the result is as follows Figure 5 As shown, the estimated value coincides with the true value curve, further verifying the effectiveness of the present invention.

[0102] Set receive channel crosstalk The range of amplitude is Each step The remaining distortion parameters are set as follows: , , , , , Utilize step 2 to receive channel crosstalk. Analytical solution amplitude estimation of receive channel crosstalk The amplitude was compared with the true value, and the result was as follows: Figure 6 As shown, the estimated value coincides with the true value curve, further verifying the effectiveness of the present invention.

[0103] Set receive channel crosstalk Phase range is Each step The remaining distortion parameters are set as follows: , , , , , Utilize step 2 to receive channel crosstalk. Phase estimation of analytical solution for receiver channel crosstalk Phase, and compared with the true value, the result is as follows Figure 7 As shown, the estimated value coincides with the true value curve, further verifying the effectiveness of the present invention.

[0104] Configure transmission channel crosstalk The range of amplitude is Each step The remaining distortion parameters are set as follows: , , , , Using step 2 to transmit channel crosstalk Analytical solution amplitude estimation of transmit channel crosstalk The amplitude was compared with the true value, and the result was as follows: Figure 8 As shown, the estimated value coincides with the true value curve, further verifying the effectiveness of the present invention.

[0105] Configure transmission channel crosstalk Phase range is Each step The remaining distortion parameters are set as follows: , , , , , Using step 2 to transmit channel crosstalk Phase estimation of analytical solution for transmit channel crosstalk Phase, and compared with the true value, the result is as follows Figure 9 As shown, the estimated value coincides with the true value curve, further verifying the effectiveness of the present invention.

[0106] Set the Faraday rotation angle The range is Each step The remaining distortion parameters are set as follows: , , , , , Using the Faraday rotation angle with phase ambiguity from step 2. Analytical solution for estimating Faraday rotation angle The absolute value of the difference between the true value and the true value is taken, and the final estimated error result is as follows: Figure 10 As shown.

[0107] Set the Faraday rotation angle The range is Each step , Replace with the true value, and set the remaining distortion parameters as follows: , , , , , Using step 3, the Faraday rotation angle with phase ambiguity is determined. Defuzzify the result, subtract the true value from the fuzzy value, and take the absolute value. The final error estimate is as follows: Figure 11 As shown.

[0108] Based on the above simulation results, the CTLR mode reduced polarization SAR calibration method based on an active calibrator proposed in this invention is effective in estimating receiver channel imbalance. Crosstalk in the receiving channel and and transmission channel crosstalk Unbiased estimation can be achieved by ignoring noise. After the defuzzification method in step 3, the Faraday rotation angle is... The maximum estimation error is only .

[0109] The following is a simulation analysis of the noise immunity performance of the calibration method. Assuming the noise is Gaussian white noise, the SNR range is set to [value missing]. Each step Perform 100,000 Monte Carlo simulations, with the remaining distortion parameters set as follows: , , , , , The received channel has a large imbalance amplitude, so its phase estimation error needs to be considered in relation to SNR. The other distortion parameters have smaller amplitudes and do not require phase consideration. The variation of the estimation error of each distortion parameter with SNR is shown in Figures 12(a)-12(f). Based on the comprehensive simulation results, when SNR reaches... At that time, the estimation errors of all distortion parameters were less than or When SNR reaches At the above levels, the estimation errors of all distortion parameters are very small.

[0110] The following is a simulation analysis of the calibration method's performance against the calibrator's own error. The calibrator's own error is summarized as average polarimetric noise (APN). Let represent the characteristic matrices of the three active scalers when considering APN, as follows:

[0111] ,

[0112] Set the APN range to Each step SNR is set to Perform 100,000 Monte Carlo simulations, with the remaining distortion parameters set as follows: , , , , , The estimation errors of each distortion parameter with APN are shown in Figures 13(a)-13(f). Based on the comprehensive simulation results, only the transmit channel crosstalk is detected. The maximum value of the estimation error is Exceeded The estimation errors of the remaining distortion parameters are all smaller than or even much smaller than 1. or This demonstrates that the calibration scheme proposed in this invention has excellent resistance to APN.

[0113] Based on the analysis of all the simulation results above, this invention utilizes the high signal-to-noise ratio advantage of active calibrators and the ingenious combination of their polarization characteristic matrices to achieve unbiased estimation of distortion parameters while ignoring noise using only three active calibrators. It achieves high-precision calibration while considering noise and the calibrator's own errors, and the calculation process is analytical and the processing flow is simple.

[0114] On the other hand, the present invention provides a simplified polarization SAR calibration device based on an active calibrator, the various modules of which can implement the various steps of the aforementioned method, specifically including:

[0115] The calibration model building module is used to analyze the error sources of the simplified polarimetric SAR system based on the Freeman model and to build a calibration model for the CTLR mode simplified polarimetric SAR system with circular transmitter and line receiver.

[0116] The analytical solution calculation module is used to substitute the characteristic matrices of three different but known polarization characteristic matrices of active calibrators into the calibration model, and calculate the analytical solutions for receiver channel imbalance, receiver channel crosstalk, transmitter channel crosstalk, and Faraday rotation angle with phase ambiguity, respectively, while ignoring amplitude and phase coefficients and noise.

[0117] The phase ambiguity resolution module is used to calculate the estimated Faraday rotation angle of the SAR imaging area using the total ionospheric electron quantity (TEC) data provided by the Global Navigation Satellite System (GNSS), and to resolve the phase ambiguity of the Faraday rotation angle based on the estimated value, thereby completing the calibration.

[0118] Thirdly, the present invention provides an electronic device, comprising: one or more processors; and a memory for storing one or more programs; wherein, when the one or more programs are executed by the one or more processors, the one or more processors implement the aforementioned simplified polarization SAR calibration method based on an active calibrator.

[0119] Fourthly, the present invention provides a computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, enable the processor to implement the aforementioned simplified polarization SAR calibration method based on an active calibrator.

[0120] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A simplified polarimetric SAR calibration method based on an active calibrator, characterized in that, The method includes: Step 1: Based on the Freeman model, analyze the error sources of the simplified polarimetric SAR system and establish a calibration model for the CTLR mode simplified polarimetric SAR system. Step 2: Substitute the characteristic matrices of three different but known polarization characteristic matrices of active calibrators into the calibration model. The first active calibrator is used to select the HV channel; the second active calibrator is used to select the VH channel; and the third active calibrator is used to select four polarization channels: HH, HV, VH, and VV. The phases of the HH and HV channels are 0°, and the phases of the VH and VV channels are 180°. Ignoring amplitude and phase coefficients and noise, calculate analytical solutions for receiver channel imbalance, receiver channel crosstalk, transmitter channel crosstalk, and Faraday rotation angle with phase ambiguity, respectively. This includes: First, the crosstalk in the receiving channel is calculated using the measurement equations of the three active calibrators. The analytical solution is: ， Secondly, the transmit channel crosstalk is derived based on the analytical solution of the receive channel crosstalk. The analytical solution is: ， Next, using the analytical solution of transmit channel crosstalk, the receive channel imbalance is derived. The analytical solution is: ， Then, using the analytical solution for the imbalance of the receiving channel, the crosstalk of the other receiving channel is derived. The analytical solution is: ， Finally, using all the obtained parameters, the Faraday rotation angle with phase ambiguity is derived. The analytical solution is: expression; In the formula, , , , , and These are the measurement scattering vectors received by three active calibrators in horizontal and vertical polarization, respectively, where j represents the imaginary unit; Step 3: Using the Total Electron Quantity (TEC) data of the ionosphere provided by the Global Navigation Satellite System (GNSS), calculate the estimated Faraday rotation angle of the SAR imaging area, and de-ambiguously de-ambiguously de-ambiguously de-ambiguously de-ambiguously de-ambiguously de-ambiguously de-ambiguously de-calibrate the Faraday rotation angle with phase ambiguity.

2. The simplified polarimetric SAR calibration method based on an active calibrator according to claim 1, characterized in that, The calibration model established in step 1 is as follows: The system measurement is equal to a linear transformation matrix that includes system distortion and ionospheric Faraday rotation effect, applied to the product of the real ground target scattering matrix and the emitted electric field vector, then scaled by an independent amplitude and phase coefficient, and finally the system noise is added.

3. The simplified polarimetric SAR calibration method based on an active calibrator according to claim 1, characterized in that, The analytical expression for the Faraday rotation angle with phase ambiguity is obtained by taking the argument of a complex expression composed of the measurements of the three active calibrators, and its range is restricted to the interval from negative π / 2 to positive π / 2.

4. The simplified polarimetric SAR calibration method based on an active calibrator according to claim 1, characterized in that, In step 3, the estimated value is calculated using the Faraday rotation angle physical model based on the operating frequency of the SAR system, the geomagnetic field strength of the imaging area, the angle parameter between the radar wave propagation direction and the geomagnetic field, and the total ionospheric electron quantity (TEC) data provided by GNSS.

5. The simplified polarimetric SAR calibration method based on an active calibrator according to claim 1, characterized in that, Step 3, the defuzzification process, includes taking the Faraday rotation angle with phase fuzziness calculated in step 2 as the base value, taking the estimated value as the reference for the phase fuzziness period, determining the integer multiple of π to be superimposed by rounding, multiplying the integer multiple by π and adding it to the base value to obtain the final unfuzzy Faraday rotation angle.

6. A simplified polarization SAR calibration device based on an active calibrator, characterized in that, include: The calibration model building module is used to analyze the error sources of the simplified polarimetric SAR system based on the Freeman model and to build a calibration model of the CTLR mode simplified polarimetric SAR system. The analytical solution calculation module is used to substitute the characteristic matrices of three different but known polarization characteristic matrices of active calibrators into the calibration model. The first active calibrator is used to select the HV channel; the second active calibrator is used to select the VH channel; and the third active calibrator is used to select four polarization channels: HH, HV, VH, and VV. The phases of the HH and HV channels are 0°, and the phases of the VH and VV channels are 180°. Ignoring amplitude and phase coefficients and noise, analytical solutions are calculated for receive channel imbalance, receive channel crosstalk, transmit channel crosstalk, and Faraday rotation angles with phase ambiguity. These solutions include: First, the crosstalk in the receiving channel is calculated using the measurement equations of the three active calibrators. The analytical solution is: ， Secondly, the transmit channel crosstalk is derived based on the analytical solution of the receive channel crosstalk. The analytical solution is: ， Next, using the analytical solution of transmit channel crosstalk, the receive channel imbalance is derived. The analytical solution is: ， Then, using the analytical solution for the imbalance of the receiving channel, the crosstalk of the other receiving channel is derived. The analytical solution is: ， Finally, using all the obtained parameters, the Faraday rotation angle with phase ambiguity is derived. The analytical solution is: expression; In the formula, , , , , and These are the measurement scattering vectors received by three active calibrators in horizontal and vertical polarization, respectively, where j represents the imaginary unit; The phase ambiguity resolution module is used to calculate the estimated Faraday rotation angle of the SAR imaging area using the total ionospheric electron quantity (TEC) data provided by the Global Navigation Satellite System (GNSS), and to resolve the phase ambiguity of the Faraday rotation angle based on the estimated value, thereby completing the calibration.

7. An electronic device, characterized in that, include: One or more processors; Memory, used to store one or more programs; When one or more programs are executed by the one or more processors, the one or more processors implement the simplified polarization SAR calibration method based on an active calibrator as described in any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, It stores executable instructions that, when executed by a processor, enable the processor to implement the simplified polarization SAR calibration method based on an active calibrator as described in any one of claims 1-5.

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