Spectral width testing method for Doppler meteorological radar

Abstract

The invention provides a spectral width test method for a Doppler meteorological radar, and the method comprises the following steps: S1, cascading 10MHz synchronization ports of three standard signal sources, adjusting the output amplitudes of the output signals of the first standard signal source and the second standard signal source to be consistent, adjusting the output frequencies to be different from the working frequencies, and adjusting the output amplitudes of the output signals of the first standard signal source and the second standard signal source to be consistent; inputting the two signals into a combiner to synthesize a radio frequency signal with frequency offset; s2, inputting a radio frequency signal into a radio frequency input port of a transceiving subsystem, inputting a clock signal generated by a third standard signal source into a clock input port of the transceiving subsystem, and completing spectrum width detection through a control processing subsystem; and S3, comparing a spectral width detection result with a theoretically calculated spectral width value. According to the spectral width test method for the Doppler weather radar, the problem that the Doppler weather radar is insufficient in test means in spectral width performance calibration and occupies hardware processing resources to cause waste can be solved.

Description

Technical Field

[0001] This invention relates to the field of meteorological detection technology, and specifically to a method for testing the spectral width of Doppler weather radar. Background Technology

[0002] Observing the movement of water droplets within the effective beam range of a radar can reflect the movement of precipitation clouds, thus providing the spectral width parameter of the observation range. The spectral width parameter is crucial in Doppler weather radar calibration, allowing for more accurate measurement of precipitation processes. However, during radar system calibration, spectral width testing typically involves generating a signal with a specific spectral width using hardware and inputting it into the radar system's input to determine the accuracy of the spectral width measurement. This method, however, places high demands on hardware resources.

[0003] Application number CN202411803101.2 discloses a weather radar velocity spectral width testing system and method. This method uses a UAV suspending a metal ball as a known target and uses radar to observe the spectral width between stationary and moving targets within the same range cell, as well as the spectral width between two moving targets. The implementation steps are as follows: Step 1: Use a UAV to suspend a metal ball and allow it to fall freely, ensuring the UAV and the metal ball are within the same range cell; Step 2: Use GPS to measure the velocity difference between the ball and the UAV as the "true value" and compare it with the spectral width measured by the radar; Step 3: After a successful first test, control a second UAV to suspend a second metal ball and fly it into the radar beam, positioned diagonally below the first UAV. Control the first UAV to raise its metal ball (moving upwards) and control the second UAV to lower its metal ball (moving downwards); Step 4: Use GPS to measure the velocity difference between the two metal balls as the "true value" and compare it with the spectral width measured by the radar. The drawback of this method is that its reliability is greatly affected by environmental factors. On the one hand, the experiment needs to be conducted under stable weather conditions with clear skies and no or light winds to minimize the interference of atmospheric disturbances on radar echo signals. On the other hand, the metal ball suspended by the UAV is easily affected by airflow during the test, resulting in unexpected swaying. This additional motion will contaminate the target's velocity spectrum, thus significantly affecting the accuracy of the spectral width test results.

[0004] Application number CN202510013140.0 discloses a weather radar velocity spectral width testing system and method. This method does not rely on external targets; instead, it utilizes components integrated within the radar system, such as a calibration source, to perform end-to-end self-testing and calibration of key parameters such as intensity, velocity, spectral width, differential reflectivity, and differential propagation phase shift of the transmit and receive links under software control. The implementation steps are as follows: Step 1: Control the calibration source to generate a continuous wave signal with a known frequency and amplitude; Step 2: After up-conversion, the signal bypasses the antenna and is directly injected into the receiver's limiter front end, then down-converted by the receiver and sent to the signal processor; Step 3: The host computer software precisely controls the intensity of the input signal through a digitally controlled attenuator, compares the measured value with the theoretical value, and statistically corrects the error. The drawback of this method is that its calibration process relies on additional hardware resources such as a built-in calibration source and noise generator to generate the test signal, which increases system complexity and cost. Furthermore, the accuracy of these internal calibration sources will drift over time, and they must be calibrated and maintained regularly using external standard instruments. Otherwise, the reliability of their calibration results cannot be guaranteed, and they may introduce imperceptible systematic errors. Summary of the Invention

[0005] The present invention addresses the shortcomings of the prior art by providing a spectral width testing method for Doppler weather radar, which can solve the problems of insufficient testing methods and wasted hardware processing resources in the spectral width performance calibration of Doppler weather radar.

[0006] This invention provides a method for testing the spectral width of a Doppler weather radar, comprising the following steps: S1. Cascade the 10MHz synchronization ports of the first, second, and third standard signal sources. After modifying the first and second standard signal sources to external trigger working mode, connect the 10MHz synchronization output of the second standard signal source to the 10MHz synchronization input port of the first standard signal source to complete the synchronization of the signal sources. Input the first transmit signal output from the first standard signal source and the second transmit signal output from the second standard signal source into a combiner to output a radio frequency signal with a wide spectrum. The first transmit signal and the second transmit signal have the same amplitude but different frequencies. S2. Input the radio frequency signal into the radio frequency input port of the transceiver subsystem, and simultaneously input the clock signal generated by the third standard signal source into the clock input port of the transceiver subsystem, and then complete the spectrum width detection through the control processing subsystem. S3. Compare the spectral width test results with the theoretically calculated spectral width value to complete the spectral width test.

[0007] In the spectral width testing method for Doppler weather radar described in this invention, as a preferred embodiment, the third standard signal source in step S1 is set to internal trigger mode.

[0008] The method for testing the spectral width of a Doppler weather radar according to the present invention, as a preferred embodiment, includes the following method for calculating the theoretical spectral width value W1 in step S3: ; Among them, v i The speed corresponding to the frequency offset of the output signal from the i-th standard signal source. S represents the average velocity corresponding to all frequency components. i V represents the intensity of the i-th frequency component, N represents the number of frequency components, v1 represents the speed corresponding to the frequency offset of the output signal from the first standard signal source, and v2 represents the speed corresponding to the frequency offset of the output signal from the second standard signal source.

[0009] The present invention provides a method for measuring the spectral width of a Doppler weather radar. As a preferred embodiment, the velocity v corresponding to the i-th frequency component... i The calculation method is as follows: ; Where λ is the operating wavelength of the radar system, f di Let be the frequency offset of the i-th input signal relative to the operating frequency.

[0010] In the spectral width testing method for Doppler weather radar described in this invention, as a preferred embodiment, the frequency of the clock signal in step S2 is 100MHz and the amplitude is 0dBm.

[0011] A system for implementing the spectral width testing method for Doppler weather radar according to the present invention includes a combiner connected to the output terminals of a first standard signal source and a second standard signal source, a waveform converter connected to the output terminal of the combiner, a transceiver subsystem connected to the output terminal of the waveform converter, a control processing subsystem connected to the output terminal of the transceiver subsystem, and signal processing terminal software connected to the control processing subsystem; the transceiver subsystem is connected to the output terminal of a third standard signal source.

[0012] The method for testing the spectral width of a Doppler weather radar described in this invention, as a preferred embodiment, uses a Ka-Ku dual-frequency precipitation radar transceiver subsystem.

[0013] In the spectral width testing method for Doppler weather radar described in this invention, the first standard signal source and the second standard signal source are preferably SMB100B.

[0014] The method for testing the spectral width of a Doppler weather radar described in this invention, as a preferred embodiment, uses an SMR30 as the third standard signal source.

[0015] The beneficial effects of this invention compared to the prior art are: (1) This invention uses a standard signal source as the input signal for generating the radar system spectral width test, which can effectively avoid the dependence of the test work on the surrounding environment of the radar station. Using a standard signal source as input can ensure the stability of the signal, reduce the introduced system error, and improve the accuracy of the measurement.

[0016] (2) This system uses off-board testing to reduce system cost and complexity, eliminating the need for additional testing hardware and reducing the hardware resource requirements of the radar system. Only the standard signal source used in the test needs to be regularly maintained to ensure its accuracy and stability, thus reducing the maintenance cost of the radar system. Attached Figure Description

[0017] Figure 1 This is a flowchart of a method for testing the spectral width of a Doppler weather radar. Figure 2 This is a schematic diagram of the system connection used to implement a method for testing the spectral width of a Doppler weather radar. Figure 3 Example 2: The signal processing terminal software outputs a Doppler spectrum for a frequency difference of 300Hz. Figure 4 The Doppler spectrum width is output by the signal processing terminal software for Example 2, where the frequency difference is 300Hz. Figure 5 Example 3: The signal processing terminal software outputs a Doppler spectrum for a frequency difference of 500Hz. Figure 6 The Doppler spectrum width is output by the signal processing terminal software for Example 3, where the frequency difference is 500Hz. Figure 7 The Doppler spectrum is output by the signal processing terminal software for Example 4, where the frequency difference is 1000Hz. Figure 8 The Doppler spectrum width is output by the signal processing terminal software for Example 4, where the frequency difference is 1000Hz. Detailed Implementation

[0018] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Example 1

[0019] like Figure 1 As shown, a method for testing the spectral width of a Doppler weather radar includes the following steps: S1. Standard signal source synchronization and input signal generation: This embodiment uses standard signal sources. The third standard signal source is set to internal trigger mode, while the first and second standard signal sources are set to external trigger mode. The 10MHz synchronous output of the third standard signal source is connected to the 10MHz synchronous input port of the second standard signal source, and vice versa, to achieve signal source synchronization. The frequencies of the first and second standard signal sources are then set to around 13.4GHz to introduce frequency offset, and the amplitudes of the output signals are adjusted to be identical using a spectrum analyzer. The transmitted signals from the first and second standard signal sources are input into a combiner to generate a wide-bandgap detection signal. The third standard signal source outputs a clock signal with a frequency of 100MHz and an amplitude of 0dBm.

[0020] S2. Use Ka-Ku dual-frequency precipitation radar to complete spectral width detection. The RF signal with a wide spectral width output from the combiner is input to the RF input port via a waveguide-coaxial converter. At the same time, the 100MHz intermediate frequency signal generated by the third standard signal source is used as the clock signal and input to the clock input port of the radar transceiver subsystem. The control and processing subsystem performs spectral width checks on the input signal and outputs the results to the signal processing terminal software.

[0021] S3. Use a standard signal source to synthesize radio frequency signal parameters and calculate the theoretical spectral width value according to the theoretical formula. Based on the signal parameters set by the standard signal sources, the output signal strengths of the first and second standard signal sources are S1=S2=0dBm, and their frequency deviations are f respectively. d1 and f d2 The corresponding v1 and v2 can be obtained from the following velocity analysis formula.

[0022] ; Where λ represents the operating wavelength of the radar system, f d This represents the frequency deviation of the input signal relative to the operating frequency, and v is the speed corresponding to the input signal.

[0023] Substituting the input signal parameters into the following spectral width calculation formula yields the theoretical value of the spectral width. The theoretical value is then compared with the measured value.

[0024] ; Where W1 is the theoretically calculated spectral width value, v i This represents the speed corresponding to the frequency offset of the output signal from the i-th standard signal source. S represents the average velocity corresponding to all frequency components. iV represents the intensity of the i-th frequency component, N represents the number of frequency components, v1 represents the speed corresponding to the frequency offset of the output signal from the first standard signal source, and v2 represents the speed corresponding to the frequency offset of the output signal from the second standard signal source.

[0025] like Figure 2 As shown, a spectral width testing system for Doppler weather radar includes a combiner connected to the output terminals of a first standard signal source and a second standard signal source, a waveform converter connected to the output terminal of the combiner, a transceiver subsystem connected to the output terminal of the waveform converter, a control processing subsystem connected to the output terminal of the transceiver subsystem, and signal processing terminal software connected to the control processing subsystem; the transceiver subsystem is connected to the output terminal of a third standard signal source. Example 2

[0026] Simulation experimental conditions: The hardware platform for the verification experiment consisted of: a Ka-Ku dual-frequency precipitation radar transceiver subsystem, a control and processing subsystem, three standard signal sources (SMB100B and SMR30), a spectrum analyzer (FSV3044), and an industrial computer.

[0027] The software platform for the verification experiment was: signal processing terminal software.

[0028] The parameters for the verification experiment were set as follows: The first standard signal source generated a continuous wave signal with a frequency offset of 1000Hz, and the second standard signal source generated a continuous wave signal with a frequency offset of 300Hz and consistent amplitude. The generated continuous wave signal was then input to the RF input port of the transceiver subsystem via a waveguide-coaxial converter.

[0029] Simulation content and result analysis: A continuous wave signal with a frequency deviation of 1000Hz was generated using a first standard signal source, and a continuous wave signal with a frequency deviation of 300Hz was generated using a second standard signal source. The combined continuous wave signal was used as input. Using the spectral width testing method of Example 1, the measured spectral width was 3.92 m / s, and the calculated theoretical spectral width was 4.38 m / s, with a measurement deviation of 0.46 m / s. The signal processing terminal software outputs the Doppler spectrum and spectral width as follows: Figures 3-4 As shown. Example 3

[0030] Simulation experimental conditions: The hardware platform for the verification experiment consisted of: a Ka-Ku dual-frequency precipitation radar transceiver subsystem, a control and processing subsystem, three standard signal sources (SMB100B and SMR30), a spectrum analyzer (FSV3044), and an industrial computer.

[0031] The software platform for the verification experiment was: signal processing terminal software.

[0032] The parameters for the verification experiment were set as follows: The first standard signal source generated a continuous wave signal with a frequency offset of 1000Hz, and the second standard signal source generated a continuous wave signal with a frequency offset of 500Hz and consistent amplitude. The generated continuous wave signal was then input to the RF input port of the transceiver subsystem via a waveguide-coaxial converter.

[0033] Simulation content and result analysis: A continuous wave signal with a frequency deviation of 1000 Hz was generated using a first standard signal source, and a continuous wave signal with a frequency deviation of 500 Hz was generated using a second standard signal source. The combined continuous wave signal was used as input. Using the spectral width test method of Example 1, the measured spectral width was 3.92 m / s, and the calculated theoretical spectral width was 4.38 m / s, with a measurement deviation of 0.46 m / s. The signal processing terminal software outputs the Doppler spectrum and spectral width as follows: Figures 5-6 As shown. Example 4

[0034] Simulation experimental conditions: The hardware platform for the verification experiment consisted of: a Ka-Ku dual-frequency precipitation radar transceiver subsystem, a control and processing subsystem, three standard signal sources (SMB100B and SMR30), a spectrum analyzer (FSV3044), and an industrial computer.

[0035] The software platform for the verification experiment was: signal processing terminal software.

[0036] The parameters for the verification experiment were set as follows: The first standard signal source generated a continuous wave signal with a frequency offset of 1000Hz, and the second standard signal source generated a continuous wave signal with a frequency offset of 1000Hz and consistent amplitude. The generated continuous wave signal was then input to the RF input port of the transceiver subsystem via a waveguide-coaxial converter.

[0037] Simulation content and result analysis: A continuous wave signal with a frequency deviation of 1000Hz was generated using a first standard signal source, and a continuous wave signal with a frequency deviation of 1000Hz was generated using a second standard signal source. The combined continuous wave signal was used as input. Using the spectral width test method of Example 1, the measured spectral width was 3.92 m / s, and the calculated theoretical spectral width was 4.38 m / s, with a measurement deviation of 0.46 m / s. The signal processing terminal software outputs the Doppler spectrum and spectral width as follows: Figures 7-8 As shown.

[0038] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A spectral width test method for Doppler weather radar, characterized by: Includes the following steps: S1. Cascade the 10MHz synchronization ports of the first, second, and third standard signal sources. Modify the first and second standard signal sources to external trigger working mode, and then connect the 10MHz synchronization output of the second standard signal source to the 10MHz synchronization input port of the first standard signal source to complete the synchronization of the signal sources. Input the first transmit signal output from the first standard signal source and the second transmit signal output from the second standard signal source into a combiner to output a radio frequency signal with a wide spectrum. The first transmit signal and the second transmit signal have the same amplitude but different frequencies. S2. Input the radio frequency signal into the radio frequency input port of the transceiver subsystem, and simultaneously input the clock signal generated by the third standard signal source into the clock input port of the transceiver subsystem, and then complete the spectrum width detection through the control processing subsystem. S3. Compare the spectral width detection result with the theoretically calculated spectral width value to complete the spectral width test.

2. The spectral width testing method for Doppler weather radar according to claim 1, characterized in that: The operating mode of the third standard signal source in step S1 is set to internal trigger.

3. The spectral width testing method for Doppler weather radar according to claim 1, characterized in that: The method for calculating the theoretical spectral width value W1 in step S3 is as follows: ； Among them, v i The speed corresponding to the frequency offset of the output signal from the i-th standard signal source. S represents the average velocity corresponding to all frequency components. i v1 represents the intensity of the i-th frequency component, N represents the number of frequency components, v1 represents the speed corresponding to the frequency offset of the output signal of the first standard signal source, and v2 represents the speed corresponding to the frequency offset of the output signal of the second standard signal source.

4. A spectral width test method for Doppler weather radar according to claim 3, characterized in that: The velocity v corresponding to the i-th frequency component i The calculation method is as follows: ； where λ is the operating wavelength of the radar system, f di is the frequency offset of the ith input signal with respect to the operating frequency.

5. The spectral width test method for Doppler weather radar according to claim 1, characterized in that: The clock signal in step S2 has a frequency of 100MHz and an amplitude of 0dBm.

6. The system for implementing the method for testing the spectral width of a Doppler weather radar according to any one of claims 1 to 5, characterized in that: It includes a combiner connected to the output terminals of the first standard signal source and the second standard signal source, a waveform converter connected to the output terminal of the combiner, a transceiver subsystem connected to the output terminal of the waveform converter, a control processing subsystem connected to the output terminal of the transceiver subsystem, and signal processing terminal software connected to the control processing subsystem. The transceiver subsystem is connected to the output terminal of the third standard signal source.

7. A spectral width test method for a Doppler weather radar according to claim 6, characterized in that: The transceiver subsystem is a Ka-Ku dual-frequency precipitation radar transceiver subsystem.

8. A spectral width test method for Doppler weather radar according to claim 6, characterized in that: The first standard signal source and the second standard signal source are both SMB100B.

9. A method for testing the spectral width of a Doppler weather radar according to claim 6, characterized in that: The third standard signal source is model SMR30.

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