A Passive Calibration Method and Device for the Backscattering Coefficient of a Radar Altimeter

Abstract

The present invention discloses a passive calibration method and device for the backscattering coefficient of a radar altimeter, relating to the technical field of microwave remote sensing, and aiming to solve the problems of low refinement degree and high cost in calibrating the backscattering coefficient of a radar altimeter in the prior art. The method includes: obtaining target observation data of a target radar altimeter in a noise monitoring mode and antenna main lobe radiation brightness temperature simulation data at the antenna aperture plane of the target radar altimeter; determining the operating system gain of the receiver in the target radar altimeter based on the target observation data and the antenna main lobe radiation brightness temperature simulation data; determining a calibration coefficient for the observed backscattering coefficient of the target radar altimeter based on the operating system gain and the measurement system gain; calibrating the backscattering coefficient of the target radar altimeter based on the calibration coefficient for the observed backscattering coefficient of the target radar altimeter; and realizing refined calibration of the backscattering coefficient at a relatively low cost.

Description

Technical Field

[0001] The present invention relates to the field of microwave remote sensing technology, and in particular to a passive calibration method and device for the backscattering coefficient of a radar altimeter. Background Art

[0002] Satellite radar altimeters are mainly used to measure the distance from the satellite to the Earth's surface. Combining this distance information with precise orbit data can determine the sea surface height in the geocentric coordinate system or relative to a reference ellipsoid, and can also simultaneously measure the significant wave height, backscattering coefficient, and sea surface wind speed at the sub-satellite point of the satellite. Among them, the sea surface wind speed is quantitatively retrieved through an empirical model based on the measured backscattering coefficient. Therefore, the backscattering coefficient of the radar altimeter needs to be accurately calibrated, and this process is very necessary and indispensable. In the prior art, for the accurate calibration of the backscattering coefficient of the radar altimeter, it is mainly achieved through the following two methods: The first is to build a dedicated ground active calibrator device and correct the errors of the entire observation system through satellite-ground synchronous calibration observations; the second is to use typical ground targets whose backscattering coefficient characteristics have been relatively accurately obtained to correct the errors of the entire observation system. However, the calibration costs of these two calibration methods are both relatively high, and they can only perform systematic bias correction, unable to distinguish which component in the radar altimeter causes the systematic bias, resulting in the inability to more finely evaluate the measurement accuracy of the backscattering coefficient of the radar altimeter and being unfavorable for the optimization of payload design.

[0003] In view of this, there is an urgent need to design a more advanced evaluation method to finely evaluate the backscattering coefficient of the radar altimeter at a lower cost, so as to solve the problems of low refinement degree and high cost in calibrating the backscattering coefficient of the radar altimeter in the prior art. Summary of the Invention

[0004] The purpose of the present invention is to provide a passive calibration method and device for the backscattering coefficient of a radar altimeter. For the calibration area of the target ground object, using the observation data of the radar altimeter in the noise monitoring mode and combining with the method of typical ground objects, the calibration coefficient of the observed backscattering coefficient of the radar altimeter is determined, and then the backscattering coefficient of the radar altimeter is calibrated, realizing that the measurement accuracy of the backscattering coefficient of the radar altimeter can be more finely evaluated, and there is no need to build expensive specific equipment, having the advantages of simplicity, feasibility, and low cost; solving the problems of low refinement degree and high cost in calibrating the backscattering coefficient of the radar altimeter in the prior art.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] In the first aspect, the present invention provides a passive calibration method for the backscattering coefficient of a radar altimeter, which may include:

[0007] Obtain the target observation data of the target radar altimeter in the noise monitoring mode and the simulated data of the radiance temperature of the main lobe of the antenna at the antenna aperture of the target radar altimeter; the target observation data is the data obtained by the target radar altimeter observing the target ground calibration area in the noise monitoring mode;

[0008] Based on the target observation data and the simulated data of the radiance temperature of the main lobe of the antenna, determine the operating system gain of the receiver in the target radar altimeter;

[0009] Based on the operating system gain and the measurement system gain of the receiver of the target radar altimeter measured on the ground before launch, determine the calibration coefficient of the observed backscattering coefficient of the target radar altimeter;

[0010] Based on the calibration coefficient of the observed backscattering coefficient of the target radar altimeter, calibrate the backscattering coefficient of the target radar altimeter.

[0011] Preferably, the determining the operating system gain of the receiver in the target radar altimeter based on the target observation data and the simulated data of the radiance temperature of the main lobe of the antenna may include:

[0012] Perform data preprocessing on the target observation data and the simulated data of the radiance temperature of the main lobe of the antenna respectively, to obtain the average output power of the receiver in the target radar altimeter and the average radiance temperature of the main lobe of the antenna at the antenna aperture of the target radar altimeter;

[0013] Based on the average output power and the average radiance temperature of the main lobe of the antenna, determine the operating system gain of the receiver in the target radar altimeter.

[0014] Preferably, the determining the operating system gain of the receiver in the target radar altimeter based on the average output power and the average radiance temperature of the main lobe of the antenna may include using the formula:

[0015] ;

[0016] Calculate the operating system gain of the receiver in the target radar altimeter; where, represents the operating system gain of the receiver in the target radar altimeter, represents the average output power, represents the average radiance temperature of the main lobe of the antenna, is the setting value of the automatic gain control (AGC) of the altimeter, is the main lobe efficiency, represents the radiation efficiency of the antenna, is the receiver signal bandwidth, and k is the Boltzmann constant.

[0017] Preferably, before obtaining the target observation data of the target radar altimeter in the noise monitoring mode and the antenna main lobe radiation brightness temperature simulation data at the antenna aperture plane of the target radar altimeter, it may include:

[0018] Using a preset surface radiation brightness temperature model to simulate and calculate the environmental parameters of the target ground calibration area, and obtaining the radiation brightness temperature simulation data on the surface of the target ground calibration area;

[0019] Using a preset atmospheric radiation transfer model to simulate and calculate the radiation brightness temperature simulation data on the surface of the target ground calibration area, and obtaining the antenna main lobe radiation brightness temperature simulation data at the antenna aperture plane of the target radar altimeter.

[0020] Preferably, before using a preset surface radiation brightness temperature model to simulate and calculate the environmental parameters of the target ground calibration area and obtaining the radiation brightness temperature simulation data on the surface of the target ground calibration area, it may include:

[0021] Construct the preset surface radiation brightness temperature model;

[0022] The construction of the preset surface radiation brightness temperature model may include:

[0023] Obtain the basic surface brightness temperature observation data of the target ground calibration area collected by a preset satellite; the preset satellite is a satellite with mature and stable operation;

[0024] Using multiple radiation emissivity models based on ground objects to simulate and calculate the environmental parameters of the target ground calibration area, and obtaining multiple surface brightness temperature simulation data; at least multiple radiation emissivity models include physical models, semi-empirical models, and empirical models;

[0025] Based on the basic surface brightness temperature observation data and multiple surface brightness temperature simulation data, determine the error accuracy of multiple radiation emissivity models, and determine the radiation emissivity model with a radiation emissivity model error accuracy less than the first preset threshold as the preset surface radiation brightness temperature model.

[0026] Preferably, after constructing the preset surface radiation brightness temperature model, it may include:

[0027] Obtain the brightness temperature observation data of an airborne microwave radiometer with the same frequency as the target radar altimeter;

[0028] Based on the brightness temperature observation data of the airborne microwave radiometer and in combination with the initial frequency of the preset surface radiation brightness temperature model, establish a first frequency scale correction coefficient between the initial frequency of the preset surface radiation brightness temperature model and the target radar altimeter frequency; the initial frequency is the operating frequency applicable to the preset surface radiation brightness temperature model itself;

[0029] Based on the first frequency scale correction coefficient, correct the surface radiation brightness temperature at the initial frequency of the preset surface radiation brightness temperature model to obtain the surface radiation brightness temperature under the operating frequency conditions of the target radar altimeter.

[0030] Preferably, before using the preset atmospheric radiative transfer model to perform simulation calculations on the simulated data of the radiation brightness temperature on the surface of the target object calibration area to obtain the simulated data of the antenna main lobe radiation brightness temperature at the antenna aperture plane of the target radar altimeter, it may include:

[0031] Construct the preset atmospheric radiative transfer model;

[0032] The constructing of the preset atmospheric radiative transfer model may include:

[0033] Obtain the station observation data of atmospheric temperature, humidity and pressure sounding;

[0034] Based on the station observation data, according to the radiation simulation strategy of preset error perturbation, simulate the error sensitivity of multiple atmospheric radiative transfer models to obtain the standard deviation of the simulation accuracy error of multiple atmospheric radiative transfer models in different atmospheric environments;

[0035] Take the atmospheric radiative transfer model with the standard deviation of the simulation accuracy error less than the second preset threshold as the preset atmospheric radiative transfer model.

[0036] Preferably, after constructing the preset atmospheric radiative transfer model, it may include:

[0037] Obtain the brightness temperature observation data of the airborne microwave radiometer with the same frequency as the target radar altimeter;

[0038] Based on the brightness temperature observation data of the airborne microwave radiometer and in combination with the initial frequency of the preset atmospheric radiative transfer model, establish a second frequency scale correction coefficient between the initial frequency of the preset atmospheric radiative transfer model and the target radar altimeter frequency;

[0039] Based on the second frequency scale correction coefficient, correct the radiation transfer process of the preset atmospheric radiation transfer model to achieve an accurate simulation of the atmospheric radiation transfer process under the operating frequency conditions of the target radar altimeter, and obtain the radiation brightness temperature of the surface radiation reaching the antenna aperture plane of the target radar altimeter after atmospheric radiation transfer.

[0040] Preferably, before obtaining the target observation data of the target radar altimeter in the noise monitoring mode and the antenna main lobe radiation brightness temperature simulation data at the antenna aperture plane of the target radar altimeter, it may include:

[0041] Determine the target ground calibration area;

[0042] The determination of the target ground calibration area may include:

[0043] Obtain historical data of the target satellite microwave radiometer observing the surface brightness temperature; the target satellite microwave radiometer is a satellite microwave radiometer that operates stably and has a working frequency close to that of the target radar altimeter;

[0044] Determine multiple limiting conditions for delineating the target ground calibration area. The multiple limiting conditions at least include that the target ground calibration area and the measurement swath of the target radar altimeter have an overlapping area, the target ground calibration area includes at least multiple ground types, the target ground calibration area has the construction conditions for the surface radiation brightness temperature models of multiple ground types, the target ground calibration area has the construction conditions for the atmospheric radiation transfer model, and the target ground calibration area covers or is close to the on-site measurement stations with the ability of operational and stable observation;

[0045] Based on the historical data and the multiple limiting conditions, determine the target ground calibration area.

[0046] In a second aspect, the present invention provides a passive calibration device for the backscattering coefficient of a radar altimeter, which may include:

[0047] A data acquisition module, which is used to acquire the target observation data of the target radar altimeter in the noise monitoring mode and the antenna main lobe radiation brightness temperature simulation data at the antenna aperture plane of the target radar altimeter; the target observation data is the data obtained by the target radar altimeter observing the target ground calibration area in the noise monitoring mode;

[0048] A system gain determination module, which is used to determine the operating system gain of the receiver in the target radar altimeter based on the target observation data and the antenna main lobe radiation brightness temperature simulation data;

[0049] A calibration coefficient determination module, which is used to determine the calibration coefficient of the observed backscattering coefficient of the target radar altimeter based on the operating system gain and the measurement system gain of the ground measurement receiver of the target radar altimeter before launch;

[0050] A backscattering coefficient calibration module, which is used to calibrate the backscattering coefficient of the target radar altimeter based on the calibration coefficient of the observed backscattering coefficient of the target radar altimeter.

[0051] Compared with the prior art, a passive calibration method for the backscattering coefficient of a radar altimeter provided by the present invention obtains the target observation data of the target radar altimeter in the noise monitoring mode and the simulated data of the radiation brightness temperature of the main lobe of the antenna at the antenna aperture of the target radar altimeter; wherein the target observation data is the data obtained by the target radar altimeter observing the target ground calibration area in the noise monitoring mode; based on the target observation data and the simulated data of the radiation brightness temperature of the main lobe of the antenna, the operating system gain of the receiver in the target radar altimeter is determined; further, based on the operating system gain and the measurement system gain of the ground measurement receiver of the target radar altimeter before launch, the calibration coefficient of the observed backscattering coefficient of the target radar altimeter is determined; finally, based on the calibration coefficient of the observed backscattering coefficient of the target radar altimeter, the backscattering coefficient of the target radar altimeter is calibrated; based on this, it can be determined that the deviation of the backscattering coefficient of the radar altimeter is mainly caused by the payload receiver of the radar altimeter, so as to more precisely evaluate the measurement accuracy of the backscattering coefficient of the radar altimeter, and the evaluation process mainly relies on simulation technology, without the need to build expensive specific equipment, which has the advantages of simplicity, feasibility and low cost; it solves the problems of low refinement degree and high cost in calibrating the backscattering coefficient of the radar altimeter in the prior art. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] The drawings described herein are used to provide a further understanding of the present invention, and constitute a part of the present invention. The schematic embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0053] Figure 1 It is a schematic diagram of the main process of a passive calibration method for the backscattering coefficient of a radar altimeter provided by the present invention;

[0054] Figure 2 It is a schematic diagram of the data flow logical relationship between the surface radiation brightness temperature and the average output power of the radar altimeter receiver in a passive calibration method for the backscattering coefficient of a radar altimeter provided by the present invention;

[0055] Figure 3Schematic diagram of the linear relationship and slope estimation between the average output power and the input bright temperature of the radar altimeter receiver in a passive calibration method for the backscattering coefficient of a radar altimeter provided by the present invention;

[0056] Figure 4 Schematic structural diagram of a passive calibration device for the backscattering coefficient of a radar altimeter provided by the present invention.

[0057] Reference numerals: 210 - Radiant bright temperature data node, 220 - Antenna main lobe radiant bright temperature data node, 230 - Radar altimeter data node. Specific embodiments

[0058] In order to clearly describe the technical solutions of the embodiments of the present invention, in the embodiments of the present invention, terms such as "first" and "second" are used to distinguish identical or similar items with basically the same functions and roles. For example, the first threshold and the second threshold are only used to distinguish different thresholds and do not limit their chronological order. Those skilled in the art can understand that terms such as "first" and "second" do not limit the quantity and execution order, and terms such as "first" and "second" do not necessarily mean different.

[0059] It should be noted that in the present invention, words such as "exemplary" or "for example" are used to represent examples, illustrations or explanations. Any embodiment or design solution described as "exemplary" or "for example" in the present invention should not be construed as being more preferred or having more advantages than other embodiments or design solutions. Rather, the use of words such as "exemplary" or "for example" is intended to present related concepts in a specific manner.

[0060] In the present invention, "at least one" means one or more, and "a plurality" means two or more. "And / or" describes the association relationship of associated objects and indicates that three relationships can exist. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone, where A and B can be singular or plural. The character " / " generally represents an "or" relationship between the previous associated objects. "At least one (item)" or similar expressions thereof refer to any combination of these items, including any combination of single item (item) or plural items (items). For example, at least one (item) of a, b or c can represent: a, b, c, the combination of a and b, the combination of a and c, the combination of b and c, or the combination of a, b and c, where a, b and c can be single or multiple.

[0061] The two commonly used methods for accurate calibration of the backscatter coefficient of the radar altimeter in the prior art require the construction of a special ground active calibrator device, and the accurate calibration of the backscatter coefficient is achieved through field tests, which requires a lot of manpower, material and financial resources; and the existing active calibrator calibration method and the typical ground object calibration method cannot distinguish which specific component causes the measurement deviation in a more detailed way, and can only correct the error of the measurement deviation of the entire system. These factors are not conducive to the optimization and upgrading of the later payload design, and it is also possible that the efficiency of improving the backscatter coefficient with higher accuracy will be lost due to insufficient refinement of the error correction. In addition, the receiver of the satellite-borne radar is a component for realizing the accurate measurement of microwave signals, and the gain deviation of the receiver itself will directly affect the measurement accuracy of the backscatter coefficient of the microwave signal of the radar. According to research, the main components on the satellite involved in the error source causing the measurement of the backscatter coefficient of the radar altimeter include the transmitter, receiver, antenna, etc.

[0062] Based on this, the present invention proposes a passive calibration method and device for the backscatter coefficient of a radar altimeter, which utilizes the observation data of the noise monitoring mode of the radar altimeter and combines the typical ground target method to realize the acquisition of the backscatter coefficient deviation of the radar altimeter, and finds that the deviation is mainly caused by the error of the receiver's own gain of the onboard payload, so that the measurement accuracy of the backscatter coefficient of the radar altimeter can be evaluated more finely, and there is no need to build expensive specific equipment, which has the advantages of simplicity and low cost; it solves the problem of low degree of refinement and high cost in the calibration of the backscatter coefficient of the radar altimeter in the prior art.

[0063] Next, the technical solution of the present invention is described in detail with reference to the accompanying drawings:

[0064] See also Figure 1 , Figure 1 The main flow diagram of the passive calibration method of the backscatter coefficient of a radar altimeter provided by the present invention is shown in FIG. The execution subject of the method is a server or terminal device equipped with the passive calibration method of the backscatter coefficient of a radar altimeter provided by the present invention; such as a calibration service platform or a mobile calibration device.

[0065] exist Figure 1 The methods may include:

[0066] Step 110: acquiring target observation data of the target radar altimeter in the noise monitoring mode and antenna main lobe radiation brightness temperature simulation data at the antenna aperture of the target radar altimeter; the target observation data is data obtained by observing the target ground object calibration area by the target radar altimeter in the noise monitoring mode.

[0067] Step 120: Determine the operating system gain of the receiver in the target radar altimeter based on the target observation data and the simulated data of the antenna main lobe radiation brightness temperature.

[0068] In Steps 110 to 120, for a pre-determined target ground calibration area, first set the target radar altimeter to the noise listening mode. At this time, the working mode of the radar altimeter is approximately the same as the observation method of a passive microwave radiometer, only detecting the radiation from the receiver, antenna loss, and the Earth's surface. Among them, the radiation response characteristics of the microwave antenna are related to its size, shape, physical temperature, and operating wavelength, and its characteristics can be accurately determined on the ground before launch. It mainly includes the main lobe efficiency, radiation efficiency, and the measurement of the brightness temperature of each specific ground surface, which can be accurately determined through the actual satellite-ground geometric relationship and ground measurement characteristics. In the present invention, the antenna radiation response can be considered accurate and error-free. Therefore, the uncertain influencing factor in the target observation data is the influence generated by the receiver. At the same time, simulation calculations are performed for different surface environment parameters in the target ground calibration area, including simulating the surface environment parameter data using a sea surface or land surface radiation brightness temperature model, and simulating the radiation brightness temperature of the sea surface or land surface using an atmospheric radiation transfer model to obtain the radiation brightness temperature at the satellite antenna aperture. Thus, based on the target observation data and the simulated data of the antenna main lobe radiation brightness temperature, the operating system gain of the receiver in the radar altimeter can be determined; there is no need to construct typical ground objects or special ground active calibration equipment to obtain data, saving the data acquisition cost.

[0069] Step 130: Determine the calibration coefficient of the observed backscattering coefficient of the target radar altimeter based on the operating system gain and the measurement system gain of the receiver measured on the ground before launch of the target radar altimeter.

[0070] Step 140: Calibrate the backscattering coefficient of the target radar altimeter based on the calibration coefficient of the observed backscattering coefficient of the target radar altimeter.

[0071] In steps 130 to 140, in the active observation mode, the radar altimeter can measure the backscattering coefficient of the surface. Compared with the passive listening mode, the set value of the automatic gain control (AGC) is different at this time, but it is known; the response characteristic of the receiver gain is the same as that in the passive listening mode. For the radar to measure the backscattering coefficient, in the radar equation used for calculating the backscattering coefficient, the receiver gain is a determined proportionality factor. Therefore, the backscattering coefficient changes proportionally with the gain of the receiver. When producing the backscattering coefficient data, the value of the receiver gain used is the measurement value on the ground before the satellite is launched; thus, when the receiver gain is estimated inaccurately, it will cause a measurement deviation in the backscattering coefficient, and passive calibration technology is required for correction. It is found that the calibration coefficient or measurement deviation of the backscattering coefficient can also be converted into the deviation of the receiver gain, that is, the calibration coefficient of the observed backscattering coefficient of the target radar altimeter can be determined by using the operating system gain and the measurement system gain of the receiver measured on the ground before the target radar altimeter is launched; finally, this calibration coefficient can be used to calibrate the backscattering coefficient of the target radar altimeter.

[0072] Based on this, a passive calibration method for the backscattering coefficient of a radar altimeter provided by the present invention establishes the correlation between the target radiation and the receiver gain in the target object by adopting the passive calibration method based on the target (typical) object, and then determines the actual operating system gain of the receiver, obtains the calculation deviation of the receiver gain, and improves the refined calibration of the backscattering coefficient; realizes the refined calibration of the backscattering coefficient at a low cost, and solves the problems of low refinement degree and high cost in calibrating the backscattering coefficient of the radar altimeter in the prior art.

[0073] Preferably, before step 110, that is, before obtaining the target observation data of the target radar altimeter in the noise listening mode and the antenna main lobe radiation brightness temperature simulation data at the antenna aperture of the target radar altimeter, it may include: determining the calibration area of the target object.

[0074] Specifically, determining the calibration area of the target object may include the following steps:

[0075] S1: Obtain the historical data of the surface brightness temperature observed by the target satellite microwave radiometer; the target satellite microwave radiometer is a satellite microwave radiometer with stable operation and a working frequency close to that of the target radar altimeter.

[0076] S2: Determine multiple constraint conditions for delineating the calibration area of the target ground object. The multiple constraint conditions at least include that there is an overlapping area between the calibration area of the target ground object and the measurement swath of the target radar altimeter, the calibration area of the target ground object includes at least multiple types of ground objects, the calibration area of the target ground object has the construction conditions for the surface radiation brightness temperature models of multiple types of ground objects, the calibration area of the target ground object has the construction conditions for the atmospheric radiation transfer model, and the calibration area of the target ground object covers or is close to the in-situ measurement stations with the ability of operational and stable observation.

[0077] S3: Determine the calibration area of the target ground object based on historical data and multiple constraint conditions.

[0078] Specifically, the deviation of the radar altimeter backscatter coefficient determined by the technical means provided by the present invention is mainly caused by the gain response error of the payload receiver. In order to ensure the calibration effect of the receiver gain response, the selected typical ground objects have relatively reliable surface radiation brightness temperature models. However, limited by the current technical development of microwave radiation and atmospheric radiation transfer models, the existing microwave radiation models do not have the same model accuracy in any geographical area of the world. Therefore, it is necessary to accurately select the geographical area of specific ground objects. Also, considering the technical characteristics of altimeter passive calibration, the selected calibration ground objects should cover various types of surfaces, including oceans, land surfaces, polar ice surfaces, etc., so that the radiation brightness temperature data set used in the subsequent calibration calculation process can cover the measurement dynamic range of the on-board receiver of the altimeter to the greatest extent. At the same time, the geographical area where the selected ground objects are distributed should consider factors such as the optimization test of radiation brightness temperature related to altimeter passive calibration, the orbit of the satellite altimeter, and the parameter acquisition conditions required for subsequent passive calibration.

[0079] Furthermore, atmospheric radiation transfer is also one of the main error sources of the passive calibration method, and there are few observation points for relevant atmospheric temperature, humidity, and pressure profile data. Therefore, in order to improve the processing accuracy of atmospheric radiation transfer, the selected geographical area should also cover or be close to atmospheric sounding stations as much as possible to obtain the in-situ profile data of measured atmospheric temperature, humidity, pressure, and wind speed, etc., and ensure the model calculation accuracy of atmospheric radiation transfer of radiation brightness temperature.

[0080] According to the above requirements, the selection criteria and principles for the calibration geographical area of typical ground objects may include the following constraint conditions:

[0081] (1) The selected geographical area must have an overlapping area with the measurement swath of the radar altimeter.

[0082] (2) The selected geographical area must include three types of ground objects, namely polar ice, ocean, and land surface. The surface types within each area should be as uniform as possible. Among them, considering that the land surface is easily affected by human life, geographical areas far from towns, such as the Amazon rainforest and the Sahara Desert, should be selected as much as possible.

[0083] (3) The selected geographical area must have the conditions for constructing mature and stable surface radiation brightness temperature models for land, ocean, polar ice, etc., and the surface environmental parameters required in the model construction stage and the calibration implementation stage should have stable and reliable acquisition conditions.

[0084] (4) The selected geographical area must have the conditions for constructing a mature and stable atmospheric radiation transfer model, and the surface environmental parameters required in the model construction stage and the calibration implementation stage should have stable and reliable acquisition conditions.

[0085] (5) The selected geographical area should preferably cover or be close to on-site measurement stations with operational and stable observation capabilities, including atmospheric sounding stations, surface environmental monitoring stations, surface radiation brightness temperature stations, etc.

[0086] Preferably, in S3, based on historical data and multiple limiting conditions, the target object calibration area is determined, which may include: First, the historical data is divided into grids to obtain the target geographical grid; based on the target geographical grid, combined with the first limiting condition, the first object calibration area is determined; the first limiting condition includes that the target object calibration area includes at least multiple object types, the target object calibration area has the conditions for constructing surface radiation brightness temperature models of multiple object types, and the target object calibration area has the conditions for constructing an atmospheric radiation transfer model; further, based on the first object calibration area, combined with the second limiting condition, the geographical grid points covered by the first object calibration area are optimized to obtain the second object calibration area; the second limiting condition includes that there is an overlapping area between the target object calibration area and the measurement swath of the target radar altimeter, and the limiting condition that the target object calibration area covers or is close to on-site measurement stations with operational and stable observation capabilities; finally, it is judged whether the stability and reliability of the surface radiation brightness temperature model constructed based on the second object calibration area meet the preset requirements. If they meet, the second object calibration area is used as the target object calibration area; if they do not meet, the first object calibration area and the second object calibration area are optimized until the stability and reliability of the obtained surface radiation brightness temperature model meet the preset convergence conditions.

[0087] Specifically, the method for selecting the calibration geographical area of typical objects can be: First, select mature and stable historical data of the observed brightness temperature of satellite microwave radiometers with relatively close frequencies, divide the data according to 30 days and 1-degree geographical grids, and select the geographical grid points covered by typical objects in combination with the selection criteria in the above (2) to (4). Then, according to the criteria in (1) and (5), the geographical grid points are combined, adjusted, and improved to determine the initial calibration area range. In the subsequent construction of the surface radiation brightness temperature model of typical objects, it is also possible to optimize and improve the initial geographical area range.

[0088] Preferably, before step 110, that is, before obtaining the target observation data of the target radar altimeter in the noise monitoring mode and the simulation data of the antenna main lobe radiation brightness temperature at the antenna aperture of the target radar altimeter, it may further include: simulating and calculating the environmental parameters of the target ground calibration area by using a preset surface radiation brightness temperature model to obtain the simulation data of the radiation brightness temperature on the surface of the target ground calibration area.

[0089] And, simulating and calculating the simulation data of the radiation brightness temperature on the surface of the target ground calibration area by using a preset atmospheric radiation transfer model to obtain the simulation data of the antenna main lobe radiation brightness temperature at the antenna aperture of the target radar altimeter.

[0090] Preferably, before simulating and calculating the environmental parameters of the target ground calibration area by using a preset surface radiation brightness temperature model to obtain the simulation data of the radiation brightness temperature on the surface of the target ground calibration area, it may include: constructing a preset surface radiation brightness temperature model.

[0091] Specifically, the surface radiation characteristics of typical ground objects such as the ocean, land surface, and polar ice surface are different and need to be studied separately. At the same time, the radiation characteristic models for typical ground objects such as the ocean, land surface, and polar ice surface have been fully developed and belong to the basic research scientific content. The technical difficulty and time cost of the calibration research for the backscattering coefficient of satellite altimeters alone are very high. The present invention will be based on the mature radiation emissivity models of typical ground objects, including physical models, semi-empirical models, and empirical models, etc., combined with the existing precisely calibrated satellite microwave radiation observation data, through sufficient error uncertainty evaluation, analyze the model accuracy and the accuracy, stability, and frequency sensitivity analysis of the supporting input surface environmental parameter errors, and construct a database of ground object radiation models and supporting data sets for passive calibration of the altimeter backscattering coefficient. Since the working frequency and bandwidth of the altimeter are generally different from the frequencies and bandwidths applicable to the existing models, it is necessary to develop a frequency correction function based on the existing surface radiation brightness temperature model based on the observation data of the same frequency of the preset satellite altimeter to accurately deduce and calculate the surface radiation brightness temperature of the preset altimeter frequency.

[0092] Preferably, constructing a preset surface radiation brightness temperature model may include: obtaining the basic surface brightness temperature observation data of the target ground calibration area collected by a preset satellite; the preset satellite is a satellite that operates stably and maturely; using multiple radiation emissivity models based on ground objects to simulate and calculate the environmental parameters of the target ground calibration area to obtain multiple surface brightness temperature simulation data; the multiple radiation emissivity models at least include physical models, semi-empirical models, and empirical models; based on the basic surface brightness temperature observation data and the multiple surface brightness temperature simulation data, determining the error accuracy of the multiple radiation emissivity models, and determining the radiation emissivity model with the error accuracy of the radiation emissivity model less than the first preset threshold as the preset surface radiation brightness temperature model.

[0093] Specifically, since multiple satellite microwave radiometers for observing environmental parameters such as sea surface temperature, sea surface salinity, atmospheric cloud liquid water, and land surface soil moisture have been launched internationally. Therefore, the radiation brightness temperature models of the ocean and land surfaces have been fully studied and developed. The construction of the radiation brightness temperature model and frequency scale correction involved in the present invention mainly includes three parts: First, there are certain deviations among various existing surface brightness temperature radiation models. Therefore, it is necessary to combine the existing mature and stable satellite microwave radiometer brightness temperature observation data, establish the deviation correction coefficients between different models based on the preselected calibration area, and then evaluate the error accuracy of different models to determine the radiation brightness temperature model that meets the requirements of the present invention. The first preset threshold can be multiple simulation error thresholds for different surface radiation brightness temperatures. For example, the simulation error of the radiation brightness temperature on the ocean surface should be less than the threshold of 2K, the simulation error of the radiation brightness temperature on land surfaces such as rainforests and polar ice should be less than the threshold of 3K, and the simulation error of the radiation brightness temperature on land surfaces such as deserts should be less than the threshold of 5K.

[0094] It should be noted that on the basis of the preselected radiation brightness temperature model, the seasonal variation characteristics and stability characteristics of the brightness temperature in different calibration areas are analyzed in detail, and combined with the requirements for the stability of the acquired calibration input environmental parameters and the numerical range of the brightness temperature change, the range of the preselected calibration area is improved, that is, the range of the calibration area initially determined in S3 is improved.

[0095] Furthermore, after constructing the preset surface radiation brightness temperature model, it may include: obtaining the brightness temperature observation data of the airborne microwave radiometer with the same frequency as the target radar altimeter; based on the brightness temperature observation data of the airborne microwave radiometer and combined with the initial frequency of the preset surface radiation brightness temperature model, establishing the first frequency scale correction coefficient between the initial frequency of the preset surface radiation brightness temperature model and the target radar altimeter frequency; the initial frequency is the working frequency applicable to the preset surface radiation brightness temperature model itself; based on the first frequency scale correction coefficient, correcting the surface radiation brightness temperature at the initial frequency of the preset surface radiation brightness temperature model to obtain the target surface radiation brightness temperature under the same frequency condition of the target radar altimeter. Thus, the environmental parameters of the target object calibration area can be simulated and calculated using the preset surface radiation brightness temperature model to obtain the radiation brightness temperature simulation data on the surface of the target object calibration area.

[0096] Furthermore, before using the preset atmospheric radiation transfer model to simulate and calculate the radiation brightness temperature simulation data on the surface of the target object calibration area to obtain the antenna main lobe radiation brightness temperature simulation data at the antenna aperture plane of the target radar altimeter, it may also include: constructing the preset atmospheric radiation transfer model.

[0097] Studies have shown that there are two effects of the atmosphere on satellite microwave radiation measurement: one is that oxygen, water vapor, cloud liquid water, etc. in the atmosphere will cause absorption attenuation and scattering of the radiation on the surface layer of the earth; the other is that the atmosphere itself will also generate microwave radiation. Therefore, it is necessary to construct an atmospheric radiation transfer model to fully simulate the influence of the upwelling radiation and downwelling radiation during the atmospheric radiation transfer process of the earth's surface radiation, and then deduce the accurate radiation brightness temperature of the earth's surface radiation at the antenna aperture plane of the spaceborne remote sensor. Considering that constructing an atmospheric radiation transfer model dedicated to a preset satellite radar altimeter is a basic scientific research content, the technical difficulty and time consumption are too long. The present invention will be based on the existing mature atmospheric radiation transfer models for microwave radiometer calibration, including physical models, semi-empirical models, and empirical models, etc., combined with the existing accurately calibrated satellite microwave radiation observation data, through sufficient error uncertainty evaluation, analyze the model accuracy and the accuracy, stability, and frequency sensitivity analysis of the supporting input atmospheric profile environmental parameter errors, and construct a database of the atmospheric radiation transfer model and the supporting dataset for passive calibration of the altimeter backscatter coefficient. Since the operating frequency and bandwidth of the altimeter are generally different from the frequencies and bandwidths applicable to the existing models, it is necessary to develop a frequency correction function based on the observed data of the same frequency as the preset satellite altimeter to accurately deduce and calculate the radiation brightness temperature of the preset altimeter frequency.

[0098] Specifically, constructing a preset atmospheric radiation transfer model may include: first, obtaining the station observation data of atmospheric temperature, humidity, and pressure sounding; second, based on the station observation data, according to the radiation simulation strategy with preset error perturbations, simulating the error sensitivity of multiple atmospheric radiation transfer models to obtain the standard deviation of the simulation accuracy errors of multiple atmospheric radiation transfer models in different atmospheric environments; finally, taking the atmospheric radiation transfer model with the standard deviation of the simulation accuracy error less than the second preset threshold as the preset atmospheric radiation transfer model.

[0099] Exemplarily, considering that there are differences in atmospheric radiation transfer under different conditions such as clear sky, cloudy, and rainfall, and the existing atmospheric radiation models may also have accuracy differences at different temperatures and different regions due to modeling accuracy differences. Therefore, for the construction of the atmospheric radiation transfer model of the present invention, first, relying on the existing atmospheric radiation transfer models, select the station observations of actual atmospheric temperature, humidity, and pressure sounding, and analyze the accuracy sensitivity of different atmospheric radiation transfer models under clear sky, cloudy, and rainfall conditions, that is, the standard deviation of the simulation accuracy error, through the radiation simulation technology with artificially increased error perturbations. The second preset threshold can be multiple simulation error thresholds for the radiation brightness temperature of the atmosphere under different environments. For example: the error sensitivity to the average upwelling radiation brightness temperature of the atmosphere should be less than the threshold of 2K, and the simulation error of the atmospheric optical thickness under clear sky should be less than the threshold of 0.02 dB.

[0100] After constructing a preset atmospheric radiative transfer model, the following steps may also be included: First, obtain the brightness temperature observation data of an airborne microwave radiometer with the same frequency as the target radar altimeter. Then, based on the brightness temperature observation data of the airborne microwave radiometer and in combination with the initial frequency of the preset atmospheric radiative transfer model, establish a second frequency scale correction coefficient between the initial frequency of the preset atmospheric radiative transfer model and the frequency of the target radar altimeter; Finally, based on the second frequency scale correction coefficient, correct the radiative transfer process of the preset atmospheric radiative transfer model to achieve an accurate simulation of the atmospheric radiative transfer process under the operating frequency conditions of the target radar altimeter, and obtain the radiative brightness temperature at the antenna aperture plane of the target radar altimeter after the surface radiative brightness temperature is radiatively transferred through the atmosphere. Thus, the radiative brightness temperature simulation data of the surface of the calibration area of the target object can be simulated and calculated using the preset atmospheric radiative transfer model to obtain the radiative brightness temperature at the antenna aperture plane of the target radar altimeter after the environmental parameters of the calibration area of the target object are transferred.

[0101] It should be noted that radar altimeters with the same frequency conditions as the target radar altimeter in the present invention on other satellites can directly use the simulation model disclosed in the present invention for simulation calculations without having to reconstruct the simulation model.

[0102] Based on this, using the brightness temperature observation data of an airborne microwave radiometer that covers the applicable frequencies of the selected existing atmospheric radiative transfer model and the preset altimeter frequency, establish a frequency scale correction coefficient between the frequency of the existing atmospheric radiative transfer model and the preset altimeter frequency to achieve an accurate simulation of the atmospheric radiative transfer under the operating frequency conditions of the preset altimeter.

[0103] Further, please refer to Figure 2 , Figure 2 which is a schematic diagram of the data flow logical relationship between the surface radiative brightness temperature and the average output power of the radar altimeter receiver in a passive calibration method for the backscattering coefficient of a radar altimeter provided by the present invention.

[0104] In Figure 2 , for a typical (target) object calibration area, that is, the surface environmental parameters, first, the surface radiative brightness temperature model in the radiative brightness temperature data node 210 can be used to simulate and calculate the environmental parameters of the target object calibration area to obtain the radiative brightness temperature simulation data of the surface of the target object calibration area; then, the atmospheric radiative transfer model in the antenna main lobe radiative brightness temperature data node 220 can be used to simulate and calculate the radiative brightness temperature simulation data of the surface of the target object calibration area to obtain the antenna main lobe radiative brightness temperature simulation data at the antenna aperture plane of the target radar altimeter; finally, the antenna main lobe radiative brightness temperature simulation data is transmitted to the radar altimeter data node 230, that is, transmitted to the radar altimeter on the satellite.

[0105] Specifically, during the calibration phase using typical ground objects, the radar altimeter operates in a noise monitoring mode. The operating mode of the altimeter is similar to the observation method of a passive microwave radiometer, detecting only the radiation from the receiver, antenna losses, and the Earth's surface. The brightness temperature of the surface radiation and the measured average power P output by the radar altimeter receiver n The data stream logical relationship between them is as Figure 2 shown. Among them, the radiation response characteristics of the microwave antenna are related to its size, shape, physical temperature, and operating wavelength. Its characteristics can be accurately determined on the ground before launch, mainly including the main lobe efficiency, radiation efficiency, and the measurement of the brightness temperature of each specific surface. It can be accurately determined through the actual satellite-ground geometric relationship and ground measurement characteristics. In the data processing of the present invention, the antenna radiation response can be considered accurate and error-free. The receiver mainly realizes the input signal that enters its front end after being radiated by the antenna, and outputs the expected average power ( ), and the characteristics directly related to the measurement mainly include the specific value of the automatic gain control setting ( ), the receiver gain ( ), and the self-thermal noise (noise equivalent temperature) of the receiver itself.

[0106] According to the microwave radiation measurement principle, after considering the self-thermal noise of the receiver, the theoretical calculation formula for the average power measured and output by the target radar altimeter receiver is as follows: is the noise equivalent temperature of the self-thermal noise of the receiver, and the available average power at the receiver input is , therefore, the average power output by the receiver is given by the following formula:

[0107] (1)

[0108] In formula (1), represents the receiver system gain of the satellite altimeter when observing typical ground objects in the passive monitoring mode (noise monitoring mode), AGC pass represents the set value of the altimeter automatic gain control AGC (directly read from the data downloaded from the altimeter), represents the main lobe efficiency, represents the radiation efficiency of the antenna, B represents the receiver signal bandwidth, k represents the Boltzmann constant (1.3806E-23 J / K), T BML represents the average brightness temperature affected by the main lobe of the antenna (antenna main lobe radiation brightness temperature), represents the average brightness temperature from the external response of the main lobe (antenna side lobe brightness temperature), represents the physical temperature of the antenna, The noise equivalent temperature representing the receiver's own thermal noise. It should be noted that Equation (1) is the basic equation for the correlation between the radiation brightness temperature at the antenna aperture and the receiver gain during typical passive calibration of ground objects. The radiation brightness temperature of the antenna main lobe is also referred to as the radiation brightness temperature input to the receiver.

[0109] When designing a microwave antenna, a key design element is to minimize the influence of the sidelobes of the microwave antenna as much as possible and enhance the radiation response of the main lobe of the antenna. Generally it is approximately 0.7 (accurately measured and estimated on the ground before launch). During the satellite's on-orbit operation, certain temperature control measures have been taken for the microwave antenna, and the variation range of its physical temperature is not large. Temperature control design has also been carried out for the receiver itself, and the variation range of its noise equivalent temperature is small.

[0110] Therefore, for Equation (1), compared with the contribution of the radiation brightness temperature of the antenna main lobe radiated from the surface the contribution of the average power of the second part is relatively small and can be ignored. Considering the linear response of the receiver to the average power measurement (the power response of general radar receivers is designed as a linear response), it can be assumed that and the relationship between them is linear. Thus, it can be seen from Equation (1) that the output power of the altimeter changes with the change of the value of the radiation brightness temperature of the altimeter antenna main lobe in different scenarios.

[0111] Therefore, in step 120, based on the target observation data and the simulation data of the radiation brightness temperature of the antenna main lobe, determining the operating system gain of the receiver in the target radar altimeter may include: respectively preprocessing the target observation data and the simulation data of the radiation brightness temperature of the antenna main lobe to obtain the average output power of the receiver in the target radar altimeter and the average radiation brightness temperature of the antenna main lobe at the antenna aperture of the target radar altimeter; determining the operating system gain of the receiver in the target radar altimeter based on the average output power and the average radiation brightness temperature of the antenna main lobe.

[0112] For example, please refer to Figure 3 Figure 3 which is a schematic diagram of the linear relationship and slope estimation between the average output power and the input brightness temperature of the radar altimeter receiver in a passive calibration method for the radar altimeter backscattering coefficient provided by the present invention.

[0113] In Figure 3 by interpolating the of two different scenarios and combining the interpolation of the corresponding average power output by the receiver, the slope of the straight line of the linear response of the power can be estimated. We can obtain the following ratio formula:

[0114] (2)​

[0115] Further, preferably, based on the average output power and the average radiance temperature of the main lobe of the antenna, determining the operating system gain of the receiver in the target radar altimeter may include using the formula:

[0116] (3)

[0117] Calculating the operating system gain of the receiver in the target radar altimeter; in Formulas (2) to (3), represents the operating system gain of the receiver in the target radar altimeter, represents the average output power, represents the average radiance temperature of the main lobe of the antenna, represents the setting value of the automatic gain control (AGC) of the altimeter, represents the main lobe efficiency, represents the radiation efficiency of the antenna, represents the receiver signal bandwidth, and k is the Boltzmann constant.

[0118] It should be noted that, is the setting value of the automatic gain control (AGC) of the altimeter, is the main lobe efficiency, represents the radiation efficiency of the antenna, is the receiver signal bandwidth. These four parameters are instrument parameters and are all known; k is the Boltzmann constant (1.3806E-23 J / K).

[0119] It has been found through research that in order to obtain the accurate calculation result of the actual system gain of the receiver on the satellite , it is only necessary to improve the estimation accuracy of the slope of the linear response line in the above figure, which can be achieved by the following two methods:

[0120] (1) Try to select as many surface scenes as possible, that is, increase more differentiated observation values, so that the estimation of the slope of the line is more accurate. This is the reason why we selected different typical ground object types in the early stage.

[0121] (2) Improve the accuracy of the surface radiance temperature model and the atmospheric radiation transfer model to obtain the average radiance temperature of the main lobe of the antenna at the antenna aperture more accurately , which is mainly ensured by constructing the surface radiance temperature model and the atmospheric radiation transfer model accurately.

[0122] Further, the calibration coefficient of the backscattering coefficient can be accurately estimated.

[0123] It should be noted that in the active observation mode, the radar altimeter can measure the backscattering coefficient of the earth's surface. Compared with the passive listening mode, the set value of the automatic gain control (AGC) is different at this time, but it is known; the response characteristic of the receiver gain is the same as that in the passive listening mode. For the radar to measure the backscattering coefficient, in the radar equation used for calculating the backscattering coefficient, the receiver gain is a definite proportionality factor. Therefore, the backscattering coefficient changes proportionally with the gain of the receiver. When generating the backscattering coefficient data, the value of the receiver gain used is the measured value on the ground before the satellite is launched. Therefore, when the receiver gain is estimated inaccurately, it will cause a measurement deviation in the backscattering coefficient, and passive calibration technology is required for correction.

[0124] Backscattering coefficient Is usually in dB units. Therefore, its measurement deviation or calibration coefficient Is defined as the measurement of the satellite to be calibrated And the actual measured value The difference between them, using the following formula:

[0125] (4)

[0126] Wherein, Represents the calibration coefficient or measurement deviation, Represents the measured value of the satellite to be calibrated, Represents The precise calibration value (true value); Can be obtained through simulation calculation or actual measurement.

[0127] Preferably, in step 130, based on the operating system gain and the measurement system gain of the receiver of the target radar altimeter measured on the ground before launch, determining the calibration coefficient of the observed backscattering coefficient of the target radar altimeter includes using the formula:

[0128] (5)

[0129] Determining the calibration coefficient of the observed backscattering coefficient of the target radar altimeter; wherein, Represents the calibration coefficient of the observed backscattering coefficient of the target radar altimeter, Represents the operating system gain of the receiver in the target radar altimeter, Represents the measurement system gain of the receiver of the target radar altimeter measured on the ground before launch.

[0130] Furthermore, the calibration coefficient of the observed backscattering coefficient of the target radar altimeter determined by formula (5) can be used to precisely calibrate the backscattering coefficient of the target radar altimeter.

[0131] In summary, the passive calibration method for the backscattering coefficient of a radar altimeter provided by the present invention achieves the following beneficial effects:

[0132] (1) The construction of the radiation characteristics model of the required typical (target) ground objects is realized. Based on the analysis of the accuracy, uncertainty, stability, and frequency sensitivity of the existing mature models in this project, a radiation model suitable for passive calibration of the backscattering coefficient of the preset radar altimeter and the construction of a database of its supporting data, as well as the construction of an atmospheric radiation transfer model and its supporting data database are established. At the same time, a frequency scale correction function based on the preset altimeter frequency is developed. This technical idea can greatly reduce the time and cost of passive calibration model research and development.

[0133] (2) The receiver gain is one of the input parameters of the radar equation for calculating the backscattering coefficient of the radar altimeter, and its value can only be determined in a ground laboratory before satellite launch. Due to the technical limitations of ground measurement and possible performance attenuation on the satellite, performance monitoring and deviation assessment after orbit are both necessary and sufficient. The passive calibration method based on typical ground objects in the present invention can establish the correlation between the radiation of typical ground object targets and the receiver gain, and then determine the actual operating system gain of the receiver, obtain the calculation deviation of the receiver gain, improve the refined calibration of the backscattering coefficient, and is also very helpful for the design optimization of subsequent satellite payloads.

[0134] Therefore, the passive calibration method for the backscattering coefficient of a radar altimeter provided by the present invention can be used to identify the observation errors caused by the receiver of the radar altimeter payload. Different from the existing "end-to-end" calibration mode for the entire observation system, it has the ability to more refinedly calibrate quantitative remote sensing payloads, and can also be used to assist in the optimization and improvement of subsequent payload designs, promoting the improvement of the measurement technology ability of remote sensing payloads; and it can obtain and correct the backscattering coefficient deviation of the radar altimeter without relying on expensive active calibrator specific equipment, with the advantages of simplicity, feasibility, and low cost. It solves the problems of low refinement degree and high cost in calibrating the backscattering coefficient of radar altimeters in the prior art.

[0135] In the second aspect, the present invention provides a passive calibration device for the backscattering coefficient of a radar altimeter. Please refer to Figure 4 , Figure 4 which is a schematic structural diagram of a passive calibration device for the backscattering coefficient of a radar altimeter provided by the present invention.

[0136] In Figure 4 , the device may include:

[0137] Data acquisition module 410 is configured to acquire target observation data of the target radar altimeter in the noise monitoring mode and antenna main lobe radiation brightness temperature simulation data at the antenna aperture plane of the target radar altimeter; the target observation data is data obtained by the target radar altimeter observing the target ground calibration area in the noise monitoring mode.

[0138] System gain determination module 420 is configured to determine the operating system gain of the receiver in the target radar altimeter based on the target observation data and the antenna main lobe radiation brightness temperature simulation data.

[0139] Calibration coefficient determination module 430 is configured to determine the calibration coefficient of the observed backscattering coefficient of the target radar altimeter based on the operating system gain and the measurement system gain of the receiver of the target radar altimeter measured on the ground before launch.

[0140] Backscattering coefficient calibration module 440 is configured to calibrate the backscattering coefficient of the target radar altimeter based on the calibration coefficient of the observed backscattering coefficient of the target radar altimeter.

[0141] Based on this, a passive calibration device for the backscattering coefficient of a radar altimeter provided by the present invention first uses the data acquisition module 410 to acquire target observation data of the target radar altimeter in the noise monitoring mode and antenna main lobe radiation brightness temperature simulation data at the antenna aperture plane of the target radar altimeter; the target observation data is data obtained by the target radar altimeter observing the target ground calibration area in the noise monitoring mode; then uses the system gain determination module 420 to determine the operating system gain of the receiver in the target radar altimeter based on the target observation data and the antenna main lobe radiation brightness temperature simulation data; further uses the calibration coefficient determination module 430 to determine the calibration coefficient of the observed backscattering coefficient of the target radar altimeter based on the operating system gain and the measurement system gain of the receiver of the target radar altimeter measured on the ground before launch, and finally uses the backscattering coefficient calibration module 440 to calibrate the backscattering coefficient of the target radar altimeter based on the calibration coefficient of the observed backscattering coefficient of the target radar altimeter; realizing refined calibration of the backscattering coefficient at a lower cost.

[0142] Although the present invention has been described in connection with various embodiments, those skilled in the art will recognize other variations of the disclosed embodiments while practicing the claimed invention, by studying the drawings, the disclosure, and the appended claims. In the claims, the word "comprising" does not exclude other elements or steps, and the indefinite article "a" or "an" does not exclude a plurality. A single processor or other unit may implement several functions recited in the claims. Certain measures are recited in mutually different dependent claims, but this does not indicate that these measures cannot be combined to advantage.

[0143] Although the invention has been described in connection with specific features and embodiments thereof, it will be apparent that various modifications and combinations can be made without departing from the spirit and scope of the invention. Accordingly, the specification and drawings are merely exemplary illustrations of the invention as defined by the appended claims, and are considered to cover any and all modifications, variations, combinations, or equivalents within the scope of the invention. Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention is also intended to include these modifications and variations.

Claims

1. A passive calibration method for backscatter coefficient of a radar altimeter, characterized in that: include: Obtaining target observation data of a target radar altimeter in a noise monitoring mode and antenna main lobe radiation brightness temperature simulation data at an antenna aperture of the target radar altimeter; The target observation data is data obtained by observing the target object calibration area by the target radar altimeter in the noise monitoring mode; Based on the target observation data and the antenna main lobe radiation brightness temperature simulation data, determining the operating system gain of the receiver in the target radar altimeter, including performing data preprocessing on the target observation data and the antenna main lobe radiation brightness temperature simulation data respectively to obtain the average output power of the receiver in the target radar altimeter and the average antenna main lobe radiation brightness temperature at the antenna aperture of the target radar altimeter; based on the average output power and the average antenna main lobe radiation brightness temperature, determining the operating system gain of the receiver in the target radar altimeter, including using the formula: ； The operating system gain of the receiver in the target radar altimeter is calculated; wherein, represents the operating system gain of the receiver in the target radar altimeter, Indicates the average output power, represents the average antenna main lobe radiation brightness temperature, is the setting value of the altimeter automatic gain control AGC, is the main lobe efficiency, The radiation efficiency of the antenna. is the receiver signal bandwidth, k is the Boltzmann constant; Determining a calibration coefficient of an observed backscatter coefficient of the target radar altimeter based on the operating system gain and a measurement system gain of a ground measurement receiver of the target radar altimeter before launch; The backscatter coefficient of the target radar altimeter is calibrated based on the calibration coefficient of the observed backscatter coefficient of the target radar altimeter.

2. The passive calibration method of the radar altimeter backscatter coefficient as claimed in claim 1, characterized in that: The step of obtaining target observation data of a target radar altimeter in a noise monitoring mode and antenna main lobe radiation brightness temperature simulation data at an antenna aperture of the target radar altimeter comprises: Using a preset surface radiation brightness temperature model to simulate and calculate the environmental parameters of the target object calibration area, and obtain radiation brightness temperature simulation data of the surface of the target object calibration area; The preset atmospheric radiation transmission model is used to simulate and calculate the radiation brightness temperature simulation data of the surface of the target object calibration area to obtain the antenna main lobe radiation brightness temperature simulation data at the antenna aperture of the target radar altimeter.

3. The passive calibration method of the radar altimeter backscatter coefficient as claimed in claim 2, characterized in that: The method of using a preset surface radiation brightness temperature model to simulate and calculate the environmental parameters of the target object calibration area to obtain radiation brightness temperature simulation data of the surface of the target object calibration area includes: Constructing the preset surface radiation brightness temperature model; The step of constructing the preset surface radiation brightness temperature model comprises: Obtaining the basic surface brightness temperature observation data of the target object calibration area collected by a preset satellite; the preset satellite is a mature and stably operating satellite; Using multiple radiation emissivity models based on ground objects, the environmental parameters of the target ground object calibration area are simulated and calculated to obtain multiple surface brightness temperature simulation data; the multiple radiation emissivity models include at least a physical model, a semi-empirical model and an empirical model; Based on the basic surface brightness temperature observation data and the plurality of surface brightness temperature simulation data, the error accuracy of the plurality of radiation emissivity models is determined, and the radiation emissivity model whose error accuracy is less than a first preset threshold is determined as the preset surface radiation brightness temperature model.

4. The passive calibration method of the backscatter coefficient of the radar altimeter as claimed in claim 3, characterized in that: The step of constructing the preset surface radiation brightness temperature model comprises: Acquiring brightness temperature observation data of an airborne microwave radiometer having the same frequency as the target radar altimeter; Based on the brightness temperature observation data of the airborne microwave radiometer and in combination with the initial frequency of the preset surface radiation brightness temperature model, a first frequency scale correction coefficient between the initial frequency of the preset surface radiation brightness temperature model and the target radar altimeter frequency is established; the initial frequency is an applicable working frequency of the preset surface radiation brightness temperature model itself; Based on the first frequency scale correction coefficient, the surface radiation brightness temperature at the initial frequency of the preset surface radiation brightness temperature model is corrected to obtain the surface radiation brightness temperature at the working frequency condition of the target radar altimeter.

5. The passive calibration method of the radar altimeter backscatter coefficient as claimed in claim 2, characterized in that: The method of using a preset atmospheric radiation transmission model to simulate and calculate the radiation brightness temperature simulation data of the surface of the target object calibration area to obtain the antenna main lobe radiation brightness temperature simulation data at the antenna aperture of the target radar altimeter includes: Constructing the preset atmospheric radiation transfer model; The step of constructing the preset atmospheric radiation transfer model comprises: Obtain station observation data of atmospheric temperature, humidity and pressure sounding; Based on the station observation data, according to the radiation simulation strategy of the preset error disturbance, the error sensitivity of multiple atmospheric radiation transfer models is simulated to obtain the standard deviation of the simulation accuracy error of the multiple atmospheric radiation transfer models under different atmospheric environments; An atmospheric radiation transfer model whose standard deviation of the simulation accuracy error is less than a second preset threshold is used as the preset atmospheric radiation transfer model.

6. The passive calibration method of the backscatter coefficient of the radar altimeter according to claim 5, characterized in that: The step of constructing the preset atmospheric radiation transfer model comprises: Acquiring brightness temperature observation data of an airborne microwave radiometer having the same frequency as the target radar altimeter; Based on the brightness temperature observation data of the airborne microwave radiometer and in combination with the initial frequency of the preset atmospheric radiation transmission model, a second frequency scale correction coefficient between the initial frequency of the preset atmospheric radiation transmission model and the target radar altimeter frequency is established; Based on the second frequency scale correction coefficient, the radiation transfer process of the preset atmospheric radiation transfer model is corrected to achieve accurate simulation of the atmospheric radiation transfer process under the working frequency conditions of the target radar altimeter, and the radiation brightness temperature of the surface radiation transmitted to the antenna aperture of the target radar altimeter through atmospheric radiation is obtained.

7. The passive calibration method of the backscatter coefficient of the radar altimeter according to claim 1, characterized in that: The step of obtaining target observation data of a target radar altimeter in a noise monitoring mode and antenna main lobe radiation brightness temperature simulation data at an antenna aperture of the target radar altimeter comprises: Determining the target object calibration area; The step of determining the target object calibration area includes: Acquire historical data of surface brightness temperature observed by a target satellite microwave radiometer; the target satellite microwave radiometer is a satellite microwave radiometer that operates stably and has an operating frequency similar to that of the target radar altimeter; Determine a plurality of restriction conditions for delimiting the target ground object calibration area, wherein the plurality of restriction conditions at least include that the target ground object calibration area and the measurement swath of the target radar altimeter have an overlapping area, the target ground object calibration area includes at least a plurality of ground object types, the target ground object calibration area has the conditions for constructing surface radiation brightness temperature models of the plurality of ground object types, the target ground object calibration area has the conditions for constructing an atmospheric radiation transmission model, and the target ground object calibration area covers or is close to an on-site measurement station with operational stable observation capability; Based on the historical data and the plurality of restriction conditions, the target object calibration area is determined.

8. A passive calibration device for backscatter coefficient of a radar altimeter, characterized in that: include: A data acquisition module, the data acquisition module is used to acquire target observation data of a target radar altimeter in a noise monitoring mode and antenna main lobe radiation brightness temperature simulation data at an antenna aperture of the target radar altimeter; the target observation data is data obtained by observing a target ground object calibration area by the target radar altimeter in a noise monitoring mode; A system gain determination module, the system gain determination module is used to determine the operating system gain of the receiver in the target radar altimeter based on the target observation data and the antenna main lobe radiation brightness temperature simulation data, including performing data preprocessing on the target observation data and the antenna main lobe radiation brightness temperature simulation data respectively to obtain the average output power of the receiver in the target radar altimeter and the average antenna main lobe radiation brightness temperature at the antenna aperture of the target radar altimeter; based on the average output power and the average antenna main lobe radiation brightness temperature, determining the operating system gain of the receiver in the target radar altimeter, including using the formula: ； The operating system gain of the receiver in the target radar altimeter is calculated; wherein, represents the operating system gain of the receiver in the target radar altimeter, Indicates the average output power, represents the average antenna main lobe radiation brightness temperature, is the setting value of the altimeter automatic gain control AGC, is the main lobe efficiency, The radiation efficiency of the antenna. is the receiver signal bandwidth, k is the Boltzmann constant; A calibration coefficient determination module, the calibration coefficient determination module is used to determine the calibration coefficient of the observed backscatter coefficient of the target radar altimeter based on the operating system gain and the measurement system gain of the ground measurement receiver of the target radar altimeter before launch; A scattering coefficient calibration module is used to calibrate the backscattering coefficient of the target radar altimeter based on the calibration coefficient of the observed backscattering coefficient of the target radar altimeter.

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