Self-balancing step-by-step calibration system and method for airborne microwave radiation platform

Abstract

The invention discloses a self-balancing step-by-step calibration system and method for an airborne microwave radiation platform, the self-balancing step-by-step calibration system comprises an internal calibration and an external calibration, and the switching of calibration sources is controlled by a central processing unit. External calibration needs to be performed once before a flight task, and an external low-temperature source and an external normal-temperature source are used for calibration. When a flight task is executed, the L-band constant-temperature dual-polarization receiver collects ground brightness temperature data and carries out internal calibration at the same time. In the observation process, the radiometer switches and receives the internal cold source, the internal heat source, the vertical polarized wave of the ground soil and the horizontal polarized wave of the ground soil according to the observation process controlled by the central processing unit. And a self-balancing calibration module is designed in the central processing unit and is used for carrying out calibration processing on acquired data. And finally, the calibrated data and the combined navigation module data are packaged in the central processing unit. One path of packaged data is transmitted to a ground station through the wireless data transmission module, and the other path of packaged data is stored in an airborne SD card.

Description

Technical Field

[0001] This invention relates to a self-balancing step calibration system and method for an airborne microwave radiation platform, belonging to the field of agricultural remote sensing technology. Background Technology

[0002] In modern agriculture, soil moisture data is a key factor in ensuring the efficient operation of precision agriculture, as it comprehensively reflects the impact of other environmental parameters (such as temperature and light) on crop growth. Accurate acquisition of real-time soil moisture data can help realize intelligent decision support systems, driving agriculture towards precision agriculture.

[0003] Soil moisture detection is gradually evolving from traditional contact measurement methods to non-contact remote sensing technologies, thanks to advancements in satellite technology and aerial photography. In recent years, microwave radiometers have been widely used in agricultural production due to their all-weather operation, high sensitivity, and ability to penetrate crop foliage and obstacles. In agricultural production, microwave radiometers significantly improve efficiency and sustainability by monitoring soil moisture, assessing crop health, providing early warnings of natural disasters, and assisting in precision agriculture management. Summary of the Invention

[0004] Currently used soil moisture measurement instruments are mainly fixed-site, deeply buried soil moisture probes. These probes are inserted directly into the soil and measure the soil moisture content using principles such as electrical conductivity. They provide accurate single-point data, but are complex to set up and maintain, and have limited applicability, typically only representing an area of ​​tens of meters around the probe. This method is not ideal for large-area monitoring and requires professional personnel to operate.

[0005] Currently, most UAV-based integrated remote sensing platforms used for agricultural meteorological monitoring employ multiple microcontrollers as the central control unit to collect, package, and process different data and monitor flight status. However, because the receiver's system parameters change during observation, the results often become unstable. Furthermore, precise timing control on the microcontroller itself is difficult, making dynamic error control impossible. This compromises the efficiency, accuracy, and resolution of the airborne platform.

[0006] To address the shortcomings of existing technologies, this invention proposes a self-balancing step-by-step calibration method for airborne microwave radiation platforms. This method eliminates the influence of changes in system parameters during measurement, thereby improving the accuracy, efficiency, and resolution of current airborne microwave radiation platforms.

[0007] Compared with existing technologies, the advantages of proposing a self-balancing step-by-step calibration method for airborne microwave radiation platforms are:

[0008] 1. The central processing unit is designed based on a heterogeneous platform integrating FPGA and ARM, which enables precise timing control of the system and improves the system's integration.

[0009] 2. It achieves self-balancing step-by-step calibration, eliminating the need for offline or periodic calibration of noise voltage and removing errors caused by changes in system parameters. Attached Figure Description

[0010] Figure 1 This is the system component of the present invention.

[0011] Figure 2 This refers to the interface interconnection relationship of this invention.

[0012] Figure 3 This is a logic design diagram of the central processing unit of this invention.

[0013] Figure 4 This is the control protocol for the input source of the L-band isothermal dual-polarized receiver of the present invention.

[0014] Figure 5 This is the external calibration process of the present invention.

[0015] Figure 6 This is the process of internal calibration and observation acquisition in this invention. Detailed Implementation

[0016] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments:

[0017] 1. Based on existing L-band isothermal dual-polarized receivers and UAV hardware platforms, a self-balancing step-by-step calibration method for airborne microwave radiation platforms is proposed. This method eliminates the influence of system parameters and their variations during measurement, improving the accuracy, efficiency, and resolution of current airborne microwave radiation platforms. The hardware platform comprises a UAV platform, an L-band dual-polarized microstrip antenna, an L-band isothermal dual-polarized receiver, and a central processing unit (located inside the L-band isothermal dual-polarized receiver). The UAV platform is used for data acquisition within a predetermined observation range; the L-band dual-polarized microstrip antenna is used to receive data from the built-in cold-cooled receiver. The receiver receives horizontal and vertical polarized waves from the heat source and external hot and cold sources, as well as horizontal and vertical polarized waves from the ground soil. The L-band isothermal dual-polarization receiver converts the polarized wave data received by the antenna into voltage data and transmits it to the central processing unit for data storage and processing. The central processing unit is responsible for controlling the acquisition timing and self-balancing step-by-step calibration process of the L-band isothermal dual-polarization receiver, and is also responsible for packaging the voltage data transmitted from the L-band isothermal dual-polarization receiver, the flight status of the UAV platform, and the positioning information of the IMU+GNSS integrated navigation module according to the protocol.

[0018] 2. The design of the central processing unit according to claim 1, characterized in that: the central processing unit uses a Xilinx ZYNQ 7010 chip, a heterogeneous platform integrating an FPGA and an ARM processor. It determines the acquisition timing of the L-band isothermal dual-polarization receiver and packages and stores data according to the communication protocol. The Xilinx ZYNQ 7010 consists of a PL (FPGA) and a PS (ARM processor). The PL terminal is responsible for determining the acquisition timing of the L-band isothermal dual-polarization receiver antenna and receiving external data. The PS terminal is responsible for self-balancing calibration calculations and processing such as collecting and packaging external data. The ZYNQ 7010's PL terminal controls the single-pole four-throw RF switch of the polarization antenna by controlling the TTL level, enabling the L-band isothermal dual-polarization receiver to receive internal cold sources, internal heat sources, and external polarization waves according to the process. After receiving the polarization waves, they are converted into digital voltage values ​​through AD conversion. This data is stored in the internal BRAM and sent to the ARM for self-balancing calibration processing. Simultaneously, the PS (Physical Sensor) terminal of the ZYNQ7010 also receives flight status data from the UAV platform and positioning data from the IMU+GNSS integrated navigation module. Based on this positioning data, the PS terminal adds timestamps and spatial positioning information to the digital voltage values. Finally, the data is packetized according to the prescribed communication protocol. One packet is stored in the platform's SD card, and the other is transmitted to the ground station's host computer software via the wireless data transmission module for data imaging.

[0019] 3. A self-balancing step-by-step calibration process according to claim 2, characterized in that: a timing block diagram for self-balancing step-by-step calibration and data acquisition is determined. Self-balancing step-by-step calibration is divided into internal calibration and external calibration. Before the flight mission, an external calibration is required. An external cryogenic source (cold air) and an external ambient temperature source (ambient temperature blackbody) are set up for the external calibration process. An L-band isothermal dual-polarization receiver is used to acquire data from both the external cryogenic and ambient temperature sources at 1ms intervals, and digital integration is performed at 200ms intervals to obtain the external calibration result. The corresponding output voltage is then read and the data is stored. During the flight mission, after the L-band isothermal dual-polarization receiver enters observation mode, internal calibration needs to be performed simultaneously with the acquisition of ground brightness temperature data. An internal cryogenic source and an internal heat source are set up for the internal calibration process. Using an L-band isothermal dual-polarization receiver with a default integration time of 200ms (digital integration), an acquisition interval of 1ms, and a state switch every 1ms (controlled by TTL level), a set of data is acquired every 5ms. The data is divided into 4 sets, each digitally integrated. One such cycle is called an observation cycle (1s). Data is saved to a data file every minute, which is set as one storage cycle.

[0020] 4. The design of a self-balancing calibration method to eliminate systematic errors according to claim 1, characterized in that the principle of deriving self-balancing step-by-step calibration is derived.

[0021] By measuring the voltages of the internal cold noise source, the internal hot noise source, the external hot blackbody observation, and the external cold air observation in four states using a radiometer, the voltages are obtained. Then, by calculating the equivalent noise outputs in the four states to eliminate the influence of systematic errors, the final complete brightness temperature calibration formula is obtained.

[0022] The complete brightness temperature calibration formula eliminates the influence of system gain, input power reflection coefficient, receiver noise floor temperature, and amplifier noise temperature on the final complete brightness temperature calibration result.

[0023] The systematic error elimination analysis for the complete brightness temperature calibration formula is as follows:

[0024] Amplifier gain: In the external reference source differential ratio, the amplifier gain appears in both the numerator and denominator and is completely eliminated. To compensate for possible gain drift, an internal reference source gain ratio correction is also introduced.

[0025] Power reflection coefficient: In the differential ratio of the external reference source, the power reflection coefficient is explicitly included in both the numerator and denominator of the differential ratio, and the ratio is normalized to the external brightness temperature. The remaining power reflection coefficient is compensated through correction.

[0026] Receiver noise temperature: When the external scaling ratio is differential, the receiver noise temperature will partially cancel out. The remaining portion is explicitly eliminated through a correction term.

[0027] Amplifier noise temperature: Part of the noise is canceled out by the differential of the internal and external reference sources, and the remaining amplifier noise is explicitly compensated by the correction term.

[0028] Figure 1 The diagram illustrates the system composition of this invention. The hardware platform consists of four parts: an L-band dual-polarized microstrip antenna, an L-band temperature-controlled dual-polarized receiver, an unmanned aerial vehicle (UAV) platform, and a central processing unit (located within the L-band temperature-controlled dual-polarized receiver). Furthermore, the platform includes external auxiliary modules for integrated navigation, lithium batteries, and wireless data transmission, and comprehensively considers the impact of each unit within the system on measurement performance, exhibiting high directivity and high sensitivity.

[0029] Figure 2The diagram illustrates the interface relationships of this invention. A memory card (USB / SD) is used to store remote sensing data and connects to the central processing unit (CPU) via an RS485 interface to store the acquired information. The IMU + GNSS integrated navigation module communicates with the CPU via an RS485 interface and provides position and attitude information, enabling precise navigation and attitude control. The L-band temperature-controlled dual-polarized receiver communicates with the CPU via an RS485 interface, receiving the acquired voltage signals for subsequent calibration and observation processes. The L-band dual-polarized microstrip antenna communicates with the CPU via an RS485 interface to monitor the antenna's temperature. The lithium battery connects to the CPU via a power supply interface, providing power to the entire system. The airborne wireless data transmission module communicates with the CPU via an RS485 interface, responsible for transmitting remote sensing data from the airborne equipment to the ground equipment. The ground-based wireless data transmission module communicates with the CPU via an RS485 interface, responsible for receiving data from the airborne equipment and transmitting it to the host computer. The host computer communicates with the ground-based wireless data transmission module through the remote sensing signal interface to display and process the received remote sensing data. At the same time, the host computer can enable and control the airborne equipment through the wireless data transmission module.

[0030] Figure 3 The diagram shows the logic design of the central processing unit (CPU). The CPU is designed using the ZYNQ7010. The ZYNQ7010 consists of a PL (FPGA) and a PS (ARM processor), forming a heterogeneous platform integrating both FPGA and ARM processors. The L-band dual-polarized antenna receives both horizontal and vertical polarized signals from external targets. The analog voltage output from the L-band isothermal dual-polarized receiver enters the AD conversion module and then communicates with the PL terminal via the SPI interface (SPI0). Simultaneously, the PL terminal controls the GPIO through the radiometer control module, thereby controlling the external TTL level to switch the receiver's data source path. The data receiving module communicates with the AD acquisition chip via the SPI interface (SPI0) to receive the data acquired by the AD and identify the data source of the radiometer. After receiving one storage cycle, the receiving module sends the internal and external calibration data, along with the observed voltage data, to the self-balancing calibration module at the PS terminal for real-time calibration processing. The UAV platform, antenna temperature sensor, and IMU+GNSS integrated navigation module communicate with the PS terminal via UART1 to UART3 interfaces to acquire flight attitude, antenna temperature, and position information. The wireless data transmission module transmits data wirelessly via UART4. The SD card communicates with the PS terminal via the SPI interface (SPI1) to store the acquired remote sensing data. Finally, the calibrated data is integrated with the input data from UART1~3 and packetized. One packet is sent to the wireless data transmission module via UART4, and the other is stored on the onboard SD card via SPI1.

[0031] Figure 4 This illustrates the protocol by which the ZYNQ7010's PL pin controls the TTL level via GPIO to switch the RF single-pole quad-throw switch. When both TTL1 and TTL2 are low, the target vertical polarization signal is switched; when both TTL1 and TTL2 are high, the target horizontal polarization signal is switched; when TTL1 is low and TTL2 is high, the data received by the internal heat source is switched; when TTL1 is high and TTL2 is low, the data received by the internal cold source is switched.

[0032] Figure 5 The diagram illustrates the external calibration process. An external calibration is performed before the flight mission, using both a cryogenic external source (cold air) and a normal-temperature external source (normal-temperature blackbody). The receiver is used to collect data at a default integration time of 200ms (digital integration) and an acquisition interval of 1ms. After both the cold and hot sources have been observed, the corresponding output voltages are read and the data is stored for calculating the brightness temperature and intensity.

[0033] Figure 6 This illustrates the internal calibration and observation acquisition process. During flight missions, internal calibration is performed simultaneously with data acquisition. When the antenna is aligned with the corresponding radiation source, the target's vertical polarization signal, horizontal polarization signal, and internal cold and hot sources are switched via a switch, and the corresponding output voltages are read. Data is recorded after both cold and hot sources have been observed. After the radiometer enters observation mode, it acquires data at a default integration time of 200ms (digital integration) and an acquisition interval of 1ms. The state is switched every 1ms (controlled by TTL level), and a set of data is observed every 5ms. The data is divided into 4 groups, each digitally integrated. One such cycle is called an observation cycle (1s). A data file is saved every 60 observation cycles, or one minute.

[0034] The principle of self-balancing step-by-step calibration is derived as follows:

[0035] Effective noise temperature measured by radiometer With source temperature (i.e., the object being measured), the power reflection coefficient at the input of the radiometer Receiver noise floor temperature Amplifier noise temperature and gain The following relationship exists:

[0036] (1)

[0037] The noise equivalent output voltage of TPR and Relationship:

[0038] (2)

[0039] in Boltzmann's constant, B represents the sensitivity (in V / W) of the power detector used in the thermal power meter (TPR), and B is the measurement bandwidth. This refers to the noise temperature caused by ambient radio frequency interference (RFI).

[0040] Ignoring environmental radio frequency interference, the output noise voltage of the L-band isothermal dual-polarization receiver in four states (i.e., one switching cycle) can be expressed by formula (2) as follows:

[0041] (3)

[0042] (4)

[0043] (5)

[0044] (6)

[0045] (7)

[0046] in Noise voltage observed in external cold air. The noise voltage observed by an external thermal blackbody. The noise voltage observed for the internal cold noise source. The noise voltage observed for the internal thermal noise source. To observe the voltage in the target scene, The equivalent brightness temperature of the external cold air. The equivalent brightness temperature of an external blackbody at room temperature. The equivalent brightness temperature of the internal cold noise source. The equivalent brightness temperature of the internal thermal noise source.

[0047] The equivalent noise output voltage for one switching cycle includes four system parameters. and These parameters can be eliminated to estimate. The ratio is:

[0048] (8)

[0049] Formula (8) is the complete brightness temperature calibration formula. Where: This is for gain drift correction; This is for receiver variation compensation; This is for antenna noise variation compensation.

[0050] The system parameter elimination analysis of formula (8) is as follows:

[0051] Amplifier gain G: Differential ratio at external reference source middle, Appearing simultaneously in both the numerator and denominator, it is completely eliminated. To compensate for possible gain drift, an internal reference source gain ratio correction is also introduced: .

[0052] Power reflection coefficient The difference ratio of the external reference source middle, and Explicitly included The ratio is then normalized to the external brightness temperature. The remaining... Through correction compensate.

[0053] Receiver noise temperature External calibration ratio When using difference, This will offset part of it. The remaining part will be explicitly eliminated through the correction item: .

[0054] Amplifier noise temperature Internal and external reference sources differentially cancel out part of the difference. The remaining amplifier noise is explicitly compensated through a correction term: .

[0055] Ultimately, the brightness temperature calibration formula eliminated the system gain. Input power reflection coefficient Receiver noise floor temperature and amplifier noise temperature right The impact of the results.

Claims

1. A self-balancing step calibration system for an airborne microwave radiation platform, characterized in that: The system comprises an unmanned aerial vehicle (UAV) platform, an L-band dual-polarized microstrip antenna, an L-band isothermal dual-polarized receiver, and a central processing unit (CPU). The CPU is located inside the L-band isothermal dual-polarized receiver. The UAV platform is used to collect data within a predetermined observation range. The L-band dual-polarized microstrip antenna is used to receive horizontally and vertically polarized waves from internal and external heat sources, as well as horizontally and vertically polarized waves from the ground soil. The L-band isothermal dual-polarized receiver converts the polarized wave data received by the antenna into voltage data and transmits it to the CPU for data storage and processing. The CPU is responsible for controlling the acquisition timing and self-balancing step-by-step calibration process of the L-band isothermal dual-polarized receiver, and also for packaging the voltage data transmitted from the L-band isothermal dual-polarized receiver, the flight status of the UAV platform, and the positioning information of the IMU+GNSS integrated navigation module according to a protocol.

2. The self-balancing step calibration system for an airborne microwave radiation platform according to claim 1, characterized in that: The central processing unit uses the ZYNQ7010 chip, which is a heterogeneous platform integrating FPGA and ARM processor. It determines the acquisition timing of the L-band isothermal dual-polarization receiver and packages and stores the data according to the communication protocol. The Xilinx ZYNQ7010 is divided into a PL end and a PS end; the PL end is an FPGA; and the PS end is an ARM processor.

3. The self-balancing step calibration system for an airborne microwave radiation platform according to claim 2, characterized in that: The PL end is responsible for determining the acquisition timing of the L-band constant temperature dual polarization receiver antenna and receiving external data, while the PS end is responsible for self-balancing calibration calculation and packet processing of external data collection. The PL terminal controls the single-pole four-throw RF switch of the polarized antenna by controlling the TTL level, so that the L-band constant temperature dual-polarized receiver can receive the internal cold source, the internal heat source and the external polarized waves according to the process.

4. The self-balancing step calibration system for an airborne microwave radiation platform according to claim 3, characterized in that: After the polarized wave is received, it is converted into a digital voltage value by AD conversion, and the data is stored in the internal BRAM and sent to the ARM for self-balancing calibration. The PS terminal receives flight status data from the UAV platform and positioning data from the IMU and GNSS integrated navigation module. Based on the positioning data, the PS terminal adds timestamps and spatial positioning information to the digital voltage values, and packages the data according to the communication protocol. The packaged data is then stored in the platform's SD card and transmitted to the ground station's host computer software via the wireless data transmission module for data imaging.

5. The self-balancing step-by-step calibration method for an airborne microwave radiation platform according to any one of claims 1-4, characterized in that: The self-balancing step-by-step calibration method is divided into internal calibration and external calibration. Before the UAV performs a flight mission, it needs to perform an external calibration. The external calibration process is carried out by setting up an external low temperature source and an external normal temperature source respectively. An L-band constant temperature dual-polarization receiver was used to collect data from an external low-temperature source and an external normal temperature source at a sampling interval of 1ms. Digital integration was performed at an integration time of 200ms to obtain the external calibration result, read the corresponding output voltage, and store the data. When the UAV is performing its flight mission, the L-band isothermal dual-polarized receiver enters the observation mode and performs internal calibration while collecting ground brightness temperature data; the internal calibration process is carried out by setting up internal low temperature source and internal heat source respectively. Using an L-band constant temperature dual-polarization receiver with a default integration time of 200ms, an acquisition interval of 1ms, and a state switch controlled by TTL level after each acquisition point, a set of data is acquired every 5ms. The data is divided into 4 sets, and each set is digitally integrated. This cycle is called an observation cycle. Data is saved to a data file every 1 minute, which is set as a storage cycle.

6. The self-balancing step-by-step calibration method for an airborne microwave radiation platform according to claim 5, characterized in that: The voltages of the internal cold noise source, the internal hot noise source, the external hot blackbody observation, and the external cold air observation were obtained by measuring the radiometer in four states. Then, by calculating the equivalent noise output of the four states, the influence of system error is eliminated, and the final complete brightness temperature calibration formula is obtained. The complete brightness temperature calibration formula eliminates the influence of system gain, input power reflection coefficient, receiver noise floor temperature, and amplifier noise temperature on the final complete brightness temperature calibration result; The systematic error elimination analysis for the complete brightness temperature calibration formula is as follows: Amplifier gain: In the external reference source differential ratio, the amplifier gain appears in both the numerator and denominator and is completely eliminated; in order to compensate for possible gain drift, an internal reference source gain ratio correction is also introduced. Power reflection coefficient: In the differential ratio of the external reference source, the power reflection coefficient is explicitly included in the numerator and denominator of the differential ratio, and the ratio is normalized to the external brightness temperature; the remaining power reflection coefficient is compensated through correction. Receiver noise temperature: When the external calibration ratio is differential, the receiver noise temperature will be partially canceled out; the remaining part will be explicitly eliminated through the correction term. Amplifier noise temperature: Part of the noise is canceled out by the differential of the internal and external reference sources, and the remaining amplifier noise is explicitly compensated by the correction term.

7. The self-balancing step-by-step calibration method for an airborne microwave radiation platform according to claim 6, characterized in that: Effective noise temperature T measured by radiometer eff With source temperature T S The power reflection coefficient ρ at the input of the radiometer and the receiver's background noise temperature T. rec Amplifier noise temperature T A The gain G has the following relationship: (1) The noise equivalent output voltage of TPR and T eff Relationship: (2) Where k is the Boltzmann constant, γ is the sensitivity of the power detector used in the thermal power meter, B is the measurement bandwidth, and T RFI The noise temperature is due to environmental radio frequency interference. Ignoring environmental radio frequency interference, the output noise voltage formula (2) of the L-band isothermal dual-polarized receiver under four states, i.e., one switching cycle, is expressed as follows: (3) (4) (5) (6) (7) Where V1 is the noise voltage observed from the external cold air source, V2 is the noise voltage observed from the external hot blackbody source, V3 is the noise voltage observed from the internal cold noise source, and V4 is the noise voltage observed from the internal hot noise source. m For the voltage observed in the target scene, T R1 T is the equivalent brightness temperature of the external cold air. R2 T is the equivalent brightness temperature of an external blackbody at room temperature. C,int T is the equivalent brightness temperature of the internal cold noise source. H,int The equivalent brightness temperature of the internal thermal noise source; The equivalent noise output voltage for one switching cycle includes four system parameters ρ, T rec T A And G, eliminate these parameters to estimate T S The ratio is: (8) Formula (8) is the complete brightness temperature calibration formula; where: This is for gain drift correction; This is for receiver variation compensation; This is for antenna noise variation compensation; The system parameter elimination analysis of formula (8) is as follows: Amplifier gain G: Differential ratio at external reference source middle, Simultaneously appearing in both the numerator and denominator, it is completely eliminated; to compensate for possible gain drift, an internal reference source gain ratio correction is also introduced: ; Power reflection coefficient The difference ratio of the external reference source middle, and Explicitly included The ratio is then normalized to the external brightness temperature; the remaining values ​​are... Through correction compensate; Receiver noise temperature External calibration ratio When using difference, Part of it will be offset; the remaining part will be explicitly eliminated through the correction term: ; Amplifier noise temperature Internal and external reference sources differentially cancel out part of the difference. The remaining amplifier noise is explicitly compensated through a correction term: ; Ultimately, the brightness temperature calibration formula eliminated the system gain. Input power reflection coefficient Receiver noise floor temperature and amplifier noise temperature right The impact of the results.

Images