A satellite radar altimeter adaptive fusion calibration processing method and device

Abstract

The present application provides a method and device for adaptive fusion calibration processing of a satellite radar altimeter, the method comprising: adopting different strategies to calibrate each device in the calibration field separately; then fusing the data of each calibration device; the fusion processing comprises: removing wild value points of the calibration deviation sequence, calculating the calibration statistical characteristics of the single calibration device, the fusion calibration weight, the fusion calibration deviation estimate, the fusion calibration random error, the fusion calibration system error, and the fusion calibration accuracy, and obtaining the final fusion calibration result. The advantages of the present application are: the various parameters required for calibration can be flexibly and automatically configured; the weights are adaptively allocated according to the detection data; when the sea surface height observation of a certain calibration device is updated, only the dynamic table needs to be updated to automatically update the calibration result.

Description

Technical Field

[0001] The present application belongs to the technical field of ocean satellite altimetry, and is applicable to absolute calibration of satellite-borne radar altimeters in an offshore calibration field equipped with a variety of different sea surface height observation equipment, and specifically relates to an adaptive fusion calibration processing method and device for a satellite radar altimeter. Background Art

[0002] As one of the most important payloads of microwave remote sensing, the satellite-borne radar altimeter can measure the global sea surface height field with centimeter-level accuracy, and can also obtain information on the effective wave height (wave height) and wind speed on the sea surface. The altimeter has important value in scientific research, national defense construction, economic life and many other aspects.

[0003] As a high-precision quantitative remote sensor, the absolute calibration of satellite-borne radar altimeters is the hub of the integration of the satellite altimetry system and the key to the success of altimetry satellite missions. High-precision absolute calibration is an urgent need for these calibration studies. Altimeter calibration has the characteristics of strict indicators, high difficulty, and interdisciplinary, and requires system top-level design. If satellite radar altimeters are not absolutely calibrated, their data will be severely limited in high-precision applications such as gravity field and seabed topography inversion and global change research. In particular, the new synthetic aperture radar altimeter has a measurement error in the ocean that is half that of traditional altimeters, which puts more stringent requirements on calibration accuracy.

[0004] In the early stage after the satellite is launched, the main focus is usually on the on-orbit calibration and inspection of the onboard instruments. In order to better meet the calibration needs, a special calibration orbit is often designed with rapid re-entry as the main feature to obtain high-precision calibration coefficients in the shortest possible time, and optimize and solidify the system processing algorithm to ensure that the performance indicators of satellite remote sensing data products meet the design requirements.

[0005] There are many studies on satellite altimeter calibration at home and abroad (in fact, intensive calibration tests are carried out after each altimeter satellite is launched), but the current international calibration algorithms have the following shortcomings.

[0006] 1. Existing methods generally calibrate the sea surface height product of the altimeter directly. Different calibration methods have different processing strategies for some height measurement error items. Directly calibrating the sea surface height may bring additional calibration errors.

[0007] 2. The existing methods do not consider the advantages of multi-calibration equipment integration. Usually, each device gives a calibration result, or a simple average is made for the calibration results of different calibration devices (or an average is made based on experience);

[0008] 3. The calibration method is not automated enough. In the past, the calibration method was very specialized. If the satellite technology status changes (such as data product version updates or hardware backup) or some equipment failures in the calibration field, special processing is required again. Summary of the invention

[0009] The purpose of this application is to overcome the defects of the prior art that the calibration error is large and recalculation is required when the satellite technical status changes or part of the equipment in the calibration field fails.

[0010] In order to achieve the above objectives, the present application proposes a satellite radar altimeter adaptive fusion calibration processing method, comprising:

[0011] Using different strategies, each device in the calibration field is calibrated separately; then the data of each calibration device is integrated;

[0012] The fusion processing includes: eliminating outlier points in the calibration deviation sequence, calculating the calibration statistical characteristics of a single calibration device, fusion calibration weights, fusion calibration deviation estimates, fusion calibration random errors, fusion calibration system errors, and fusion calibration accuracy, to obtain a final fusion calibration result.

[0013] As an improvement of the above method, the method adopts different strategies to perform calibration processing on each device in the calibration field separately, including:

[0014] Step 1: Preprocess the sea surface height observation sequence of the calibration equipment;

[0015] Step 2: Perform power spectrum analysis and smoothing filtering on the sea surface height sequence;

[0016] Step 3: Calculate the sea surface height sequence along the track in the altimeter calibration area;

[0017] Step 4: Determine the satellite's overhead position and time;

[0018] Step 5: Calculate the matching error;

[0019] Step 6: Determine the sea surface height reference value of the calibration site;

[0020] Step 7: Determine the sea surface height of the altimeter to be calibrated;

[0021] Step 8: Subtract the sea surface height reference value of the calibration field from the sea surface height value of the altimeter to be calibrated to generate a sea surface height calibration deviation sequence.

[0022] As an improvement of the above method, when calculating the sea surface height sequence along the track in the altimeter calibration field area,

[0023] For tide gauge stations, the sea level height SSH is calculated according to the following formula:

[0024] SSH = orbital altitude - Ku-band distance after instrument error correction - Ku-band ionosphere correction - troposphere model correction - wet troposphere model correction - Ku-band sea state deviation correction - ocean tide correction solution based on FES model + ocean load tide

[0025] For anchoring, the sea surface height SSH is calculated according to the following formula:

[0026] SSH = orbital altitude - Ku-band distance after instrument error correction - Ku-band ionosphere correction - dry troposphere model correction - wet troposphere model correction - Ku-band sea state deviation correction

[0027] For GNSS buoys, the sea surface height SSH is calculated according to the following formula:

[0028] SSH = orbit altitude - Ku-band distance after instrument error correction - Ku-band ionosphere correction - dry troposphere model correction - wet troposphere model correction - Ku-band sea state deviation correction - solid tide correction - polar tide correction - ocean load tide.

[0029] As an improvement of the above method, the method adopts different strategies to perform calibration processing on each device in the calibration field separately, and further includes:

[0030] Step 9: Record the sea surface height calibration deviation sequence in a dynamic table, and update the dynamic table each time the deviation sequence of a single calibration device is obtained.

[0031] As an improvement of the above method, the calculation of the calibration statistical characteristics of a single calibration device includes:

[0032] The statistical characteristics of the calibration equipment, namely the calibration accuracy The calculation method is:

[0033]

[0034] Among them, N i represents the total number of valid calibration times of the i-th calibration device; σ i represents the standard deviation of the deviation sequence of the ith calibration device.

[0035] As an improvement of the above method, the calculating of fusion calibration weights includes:

[0036]

[0037] Among them, w i represents the calibration weight of the i-th calibration device; Indicates the calibration accuracy of the i-th calibration device.

[0038] As an improvement of the above method, the step of calculating the estimated value of the fusion calibration deviation includes:

[0039]

[0040] in, represents the estimated value of fusion calibration deviation; w i represents the calibration weight of the i-th calibration device; represents the average deviation of the i-th calibration device:

[0041]

[0042] Among them, N i Indicates the total number of valid calibrations of the i-th calibration device; N indicates the total number of calibrations; Bias j,i Indicates the deviation value of the jth calibration of the i-th calibration device.

[0043] As an improvement of the above method, the calculation of the fusion calibration random error includes:

[0044]

[0045] in, represents the random error of fusion calibration; Indicates the calibration accuracy of the i-th calibration device.

[0046] As an improvement of the above method, the calculation of the fusion calibration accuracy is: summing the square of the fusion calibration random error and the square of the fusion calibration system error, and then taking the square root.

[0047] As an improvement of the above method, the final fused calibration result is: fused calibration deviation estimation value±fused calibration accuracy.

[0048] The present application also provides a satellite radar altimeter adaptive fusion calibration processing device, which is implemented based on the above method, and the device includes:

[0049] An individual calibration module, used to adopt different strategies to perform calibration processing on each device in the calibration field individually; and

[0050] Fusion calibration module, used for fusion processing of data from various calibration devices;

[0051] The fusion processing includes: eliminating outlier points in the calibration deviation sequence, calculating the calibration statistical characteristics of a single calibration device, fusion calibration weights, fusion calibration deviation estimates, fusion calibration random errors, fusion calibration system errors, and fusion calibration accuracy, to obtain a final fusion calibration result.

[0052] Compared with the prior art, the advantages of this application are:

[0053] 1. At present, other similar studies mostly directly use the sea level height observation value of the satellite altimeter. All errors in the observation value have been corrected, and some errors in the calibration field are the same as the altimeter observation errors. These errors can be offset in the calibration. Correction will increase the complexity of the algorithm and introduce more errors. In the method of the present invention, the altimeter sea level height that best matches each calibration device is calculated in combination with the specific characteristics of different calibration devices. The various parameters required in the calibration can be flexibly and automatically configured. More importantly, after the parameters are flexibly configured, the calibration of the traditional mode and the synthetic aperture mode can be realized for the same synthetic aperture satellite radar altimeter at the same time, and the relative deviation between the two can be determined.

[0054] 2. In the fusion calibration, the calibration weights in the fusion are updated according to the data results of each calibration device itself to realize adaptive fusion calibration processing. In previous similar studies, either the deviations of different calibration devices are reported separately, and the user is allowed to choose a more reliable calibration result; or the results of various deviations are simply arithmetic averaged; or an empirical weight is designed according to the accuracy index given by the developer of the calibration device. The weight distribution in the present invention is completely adaptive. For example, due to sea conditions and sudden weather conditions, the GNSS buoy in the calibration device may fail or lose part of the data. The method of the present invention can automatically reduce the weight of the device in the entire calibration.

[0055] 3. Introduce a dynamic table data structure in calibration. When the sea surface height observation of a certain calibration device is updated, only the value of one column (or even a cell) in the dynamic table needs to be updated. Re-run the fusion processing software, and the calibration result of the system can be automatically updated. Calibration automation is achieved. For example, in GNSS buoy calibration, the sea surface height observation value can be quickly obtained from the broadcast ephemeris and clock difference file of the GNSS satellite (the sea surface height observation value of the tide gauge station is accurate at this time), and a preliminary sea surface height calibration result is obtained. After several days, after the GNSS satellite precise ephemeris and clock difference file is updated, the GNSS calibration result is updated, and the corresponding column in the dynamic table file is updated. The calibration processing of the tide gauge station does not need to be repeated. In previous studies, this flexibility has not been considered. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 The figure shows the function diagram of various sea surface height calibration equipment in the calibration field;

[0057] Figure 2 Shown is a single device calibration flow chart;

[0058] Figure 3 Shown is the fusion calibration flow chart. DETAILED DESCRIPTION

[0059] The technical solution of the present application is described in detail below with reference to the accompanying drawings.

[0060] The present invention proposes a satellite radar altimeter adaptive fusion calibration processing method and device, which includes two core execution steps: the first step is to use different strategies to calibrate each device in the calibration field separately; the second step is to perform fusion processing on each calibration device. The mechanism and method of measuring sea level height by different calibration devices are very different. The present invention assumes that before the calibration processing referred to in the present invention, each device in the calibration field has obtained a sea level height observation sequence (at least including a time tag sequence and a corresponding sea level height sequence), and each calibration device has been strictly tested to achieve mutual calibration (that is, when observing the sea level height in the same sea area, the relative deviation between the observation devices has been corrected).

[0061] The process of calibration processing for a single calibration device includes:

[0062] Step 1: Preprocess the sea surface height observation sequence of the calibration equipment. The preprocessing includes converting the time label into century seconds of UTC Greenwich Mean Time and removing outliers in the sea surface height observation sequence.

[0063] Step 2: Power spectrum analysis and smoothing filtering. Perform power spectrum analysis on the sea surface height sequence to obtain the best filtering parameters, and perform smoothing filtering on the sea surface height sequence.

[0064] Step 3: Calculate the sea surface height sequence along the track in the altimeter calibration field area. Set a minimum distance to the calibration field equipment, extract the altimeter measurement parameters within this range, and calculate the altimeter sea surface height sequence along the track for calibration. The altimeter sea surface height calculation method for different equipment is different.

[0065] Step 4: Determine the satellite's overpass position and time. According to the specific location of the calibration equipment, find the closest distance between the satellite's subsatellite point and the calibration equipment, and calculate the corresponding satellite's subsatellite point latitude and longitude and overpass time. Interpolate the filtered sea surface height measurement to this time.

[0066] Step 5: Calculate the matching error. Due to the perturbation of the satellite orbit, the location of the field calibration equipment is unlikely to be exactly at the sub-satellite point of the satellite, resulting in a matching error. There are two sources of matching errors: mean sea surface height difference and tidal difference. When the closest distance between the sub-satellite point and the calibration equipment is within 1 km (GNSS buoy calibration method generally meets this condition), the tidal difference can be ignored. The matching error is calculated based on high-resolution mean sea surface height model data and tidal model data.

[0067] Step 6: Determine the sea surface height reference value of the calibration field. Interpolate the sea surface height sequence of the on-site calibration equipment to the time when the satellite passes the top, and then correct the matching error to obtain the sea surface height reference value of the calibration field (one value for each comparison device and each time the satellite passes the top).

[0068] Step 7: Determine the sea surface height value of the altimeter to be calibrated. Interpolate the satellite radar altimeter sea surface height sequence to the time of passing the top to obtain the sea surface height value of the altimeter to be calibrated (one value each time the satellite passes the top).

[0069] Step 8: Generate a sea surface height calibration deviation sequence. Subtract the "sea surface height value of the calibration altimeter" obtained in step 6 from the "sea surface height value to be calibrated" obtained in step 7, and obtain a deviation value for each device and each time it passes over the top. A deviation value (which may also be an invalid value) will be generated each time it passes over the top. After completing the calibration process for a single calibration device, a sea surface height sequence can be obtained.

[0070] Step 9: Update the dynamic table. A dynamic table is prepared in advance (its data structure is shown in Table 1). When the table is initialized, all cells are set to NaN (invalid value). After the single calibration device processing is completed, a column of the dynamic table is updated.

[0071] Table 1 Dynamic table of sea surface height calibration deviation

[0072]

[0073] The adaptive fusion calibration process is as follows:

[0074] Step 1: Eliminate outlier points in the calibration deviation sequence, calculate the standard deviation of the calibration deviation sequence of each device, and treat the deviation values ​​whose absolute value is greater than several times the standard deviation (2 times, 2.5 times or 3 times can be selected according to the actual situation of the calibration field) as outlier points for elimination.

[0075] Step 2: Calculate the calibration statistical characteristics of a single calibration device. After removing the outliers in the calibration deviation sequence of each calibration device, obtain its deviation, standard deviation, number of valid calibrations (count the number of non-NaN values ​​in the column), and calibration accuracy (sequence standard deviation divided by the square root of the number of valid calibrations).

[0076] Step 3: Calculate the fusion calibration weight. According to the calibration accuracy of each calibration device, the fusion calibration weight of each calibration device is adaptively allocated.

[0077] Step 4: Calculate the estimated value of the fusion calibration deviation. According to the calibration deviation of each calibration device and the fusion calibration weight calculated in the previous step, the calibration deviations of each calibration device are weighted averaged to calculate the fusion calibration deviation.

[0078] Step 5: Calculate the random error of fusion calibration. According to the data fusion model, calculate the standard deviation of fusion calibration, which is the random error in the calibration process.

[0079] Step 6: Calculate the fusion calibration system error. The deviations of each calibration device obtained in step 2 are combined into a sequence, and the standard deviation of the sequence is calculated. This is the systematic error in the calibration process.

[0080] Step 7: Calculate the fusion calibration accuracy. Perform RSS synthesis (square root after sum of squares) of the random error obtained in step 5 and the systematic error obtained in step 6 to obtain the fusion calibration accuracy.

[0081] The final calibration result is presented in the following form:

[0082] “Fusion calibration deviation” (obtained in step 4) ± “Fusion calibration deviation” (obtained in step 7).

[0083] like Figure 1 As shown, a schematic diagram of the functions of various sea surface height calibration equipment in the calibration field is given.

[0084] Since the accuracy index of satellite radar altimeter calibration is very strict, it is recommended to adopt a general calibration scheme with multiple calibration equipment complementing each other and cross-checking. In the calibration field equipment system, each equipment has its unique and irreplaceable advantages. The construction plan of the calibration field ensures the joint work of various sea surface height calibration equipment. Tide stations and moorings work continuously throughout the calibration cycle, providing basic guarantees for joint work. When meteorological conditions and sea conditions permit, the three types of equipment, GNSS buoys, tide stations and moorings, can work together.

[0085] Tide gauge stations can serve as basic equipment for sea level height measurement and calibration at calibration sites, analyze and correct tidal information at calibration sites, and provide minimum guarantees for calibration.

[0086] GNSS buoys can be used as reference equipment for sea surface height measurement and calibration in calibration fields, providing absolute sea surface height measurement and delivering elevation references for sea surface height measurements of other equipment.

[0087] Anchoring can be used as the main equipment for sea surface height measurement and calibration at the calibration site, providing long-term continuous automatic observation of sub-satellite points.

[0088] The joint working strategy of calibration field equipment is as follows:

[0089] (1) The tide station is not located below the satellite where the altimeter has effective measurements, so indirect calibration is achieved and the tide needs to be extrapolated. Long-term synchronous observations at anchor can be used to correct the tide mismatch for the tide station.

[0090] (2) Mooring calibration requires synchronous observation of GNSS buoys to establish an elevation benchmark.

[0091] Example 1

[0092] like Figure 2 As shown in the figure, the calibration process of a single calibration device is given. The details are as follows:

[0093] Step 1: Preprocess the sea surface height observation sequence of the calibration equipment. The preprocessing includes converting its time label into century seconds of UTC Greenwich Mean Time and removing outliers in the sea surface height observation sequence.

[0094] Step 2: Power spectrum analysis and smoothing filtering. Perform power spectrum analysis on the sea surface height sequence to obtain the best filtering parameters, and perform smoothing filtering on the sea surface height sequence.

[0095] Step 3: Calculate the sea surface height sequence along the track in the altimeter calibration field area. Set a minimum distance to the calibration field equipment, extract the altimeter measurement parameters within this range, and calculate the altimeter sea surface height sequence along the track for calibration (the calculation method of the altimeter sea surface height corresponding to different equipment is different).

[0096] It should be pointed out that different calibration methods have different processing strategies for various tidal components. The simplest method is: except for the tide station (because it is not located at the sub-satellite point), try not to consider the tidal correction problem when calibrating other equipment; the tidal correction problem is considered in the altimeter.

[0097] The tide station is not located below the satellite, so its various tides (including ocean tide, ocean load tide, solid tide and extreme tide) are different from those of the altimeter and need to be calibrated. The ocean tide parameter of the altimeter product is actually the sum of the narrow ocean tide and the ocean load tide. Therefore, for the tide station, the sea surface height can be calculated according to the following formula:

[0098] SSH = altitude (orbit altitude) - range_ku (Ku band range, instrument error corrected) - iono_corr_ku (Ku band ionosphere correction) - model_dry_tropo_corr (dry troposphere model correction) - model_wet_tropo_corr (wet troposphere model correction) - sea_state_bias_ku (Ku band sea state bias correction) - ocean_tide_sol2 (ocean tide correction solution 2, based on FES model) + ocean_load_tide (ocean load tide) (1)

[0099] The ocean tide, ocean load tide, solid tide and extreme tide at anchor are the same as those of the altimeter, so no correction is required for all tides of the altimeter. For anchoring, the sea surface height can be calculated according to the following formula:

[0100] SSH = altitude (orbit altitude) - range_ku (Ku band range, instrument error correction) - iono_corr_ku (Ku band ionosphere correction) - model_dry_tropo_corr (dry troposphere model correction) - model_wet_tropo_corr (wet troposphere model correction) - sea_state_bias_ku (Ku band sea state bias correction) (2)

[0101] The situation is more complicated when calibrating GNSS buoys. In most cases (i.e., the customary practice in GNSS positioning), the load tide, solid tide, and extreme tide have all been corrected in the process of generating the absolute sea surface height. Therefore, for GNSS buoys, the sea surface height can be calculated according to the following formula:

[0102] SSH = altitude (orbit altitude) - range_ku (Ku band range, instrument error correction) - iono_corr_ku (Ku band ionosphere correction) - model_dry_tropo_corr (dry troposphere model correction) - model_wet_tropo_corr (wet troposphere model correction) - sea_state_bias_ku (Ku band sea state bias correction) - solid_earth_tide (solid tide correction) - pole_tide (pole tide correction) - ocean_load_tide (ocean load tide) (3)

[0103] If, for the purpose of calibration, you choose not to correct the load tide, solid tide and polar tide during GNSS positioning, these tides do not need to be corrected during calibration.

[0104] The preprocessing strategies for various tides are shown in the following table.

[0105] Table 2 Preprocessing strategies for various tides in altimeter products

[0106]

[0107]

[0108] Step 4: Determine the satellite's overpass position and time. Find the closest distance between the satellite's subsatellite point and the calibration equipment, and calculate the corresponding satellite's subsatellite point latitude and longitude and overpass time. Interpolate the filtered sea surface height measurement to this time.

[0109] Step 5: Calculate the matching error. Due to the perturbation of the satellite orbit, the position of the on-site calibration equipment is unlikely to be exactly at the sub-satellite point of the satellite, resulting in a matching error. There are two sources of matching errors: mean sea surface height differences and tidal differences. When the closest distance between the sub-satellite point and the calibration equipment is within 1 km (the GNSS buoy calibration method generally meets this condition), the tidal difference can be ignored. The matching error is calculated based on high-resolution mean sea surface height model data (such as the DTU21 mean sea surface model of the Technical University of Denmark) and tidal model data (such as the French FES model or the American TPXO model).

[0110] Step 6: Determine the sea surface height reference value of the calibration field. Interpolate the sea surface height sequence of the on-site calibration equipment to the time when the satellite passes the top, and then correct the matching error to obtain the sea surface height reference value of the calibration field (one value for each comparison device and each time the satellite passes the top).

[0111] Step 7: Determine the sea surface height value of the altimeter to be calibrated. Interpolate the satellite radar altimeter sea surface height sequence to the time of passing the top to obtain the sea surface height value of the altimeter to be calibrated (one value each time the satellite passes the top).

[0112] Step 8: Generate a sea surface height calibration deviation sequence. Subtract the "sea surface height value of the calibration altimeter" obtained in step 6 from the "sea surface height value to be calibrated" obtained in step 7, and obtain a deviation value for each device and each time it passes over the top. A deviation value (which may also be an invalid value) will be generated each time it passes over the top. After completing the calibration process for a single calibration device, a sea surface height sequence can be obtained.

[0113] Step 9: Update the dynamic table. A dynamic table is prepared in advance (its data structure is shown in Table 1). When the table is initialized, all cells are set to NaN (invalid value). After the single calibration device processing is completed, a column of the dynamic table is updated.

[0114] Figure 3 The flowchart for the adaptive fusion calibration process is as follows:

[0115] Step 1: Eliminate outlier points in the calibration deviation sequence, calculate the standard deviation of the calibration deviation sequence of each device, and treat the deviation values ​​whose absolute value is greater than several times the standard deviation (2 times, 2.5 times or 3 times can be selected according to the actual situation of the calibration field) as outlier points for elimination.

[0116] Step 2: Calculate the calibration statistical characteristics of a single calibration device. After removing the outliers in the calibration deviation sequence of each calibration device, obtain its deviation, standard deviation, number of valid calibrations (count the number of non-NaN values ​​in the column), and calibration accuracy (sequence standard deviation divided by the square root of the number of valid calibrations).

[0117] Let the bias value of the jth calibration of the i-th calibration device be Biasj,i , then its average deviation (Assume that the total number of effective calibration times of the device is N i ):

[0118]

[0119] Wherein, N represents the number of calibrations.

[0120] The standard deviation of the deviation series σ i for:

[0121]

[0122] The calibration accuracy of the calibration equipment is:

[0123]

[0124] Step 3: Calculate the fusion calibration weight. According to the calibration accuracy of each calibration device, adaptively allocate the fusion calibration weight of each calibration device (taking the four-grid calibration device as an example):

[0125]

[0126] Step 4: Calculate the estimated value of the fused calibration deviation. According to the calibration deviation of each calibration device calculated by formula (4) and the fused calibration weight calculated by formula (7), the calibration deviations of each calibration device are weighted averaged to calculate the fused calibration deviation:

[0127]

[0128] Step 5: Calculate the random error of fusion calibration. According to the data fusion model, calculate the standard deviation of fusion calibration, as shown in the following formula:

[0129]

[0130] This is the random error in the calibration process.

[0131] Step 6: Calculate the fusion calibration system error. The deviations of each calibration device obtained in step 2 are combined into a sequence, and the standard deviation of the sequence is calculated. This is the systematic error in the calibration process.

[0132] Step 7: Calculate the fusion calibration accuracy. Perform RSS synthesis (square root after sum of squares) of the random error obtained in step 5 and the systematic error obtained in step 6 to obtain the fusion calibration accuracy.

[0133] The final calibration result is presented in the following form:

[0134] “Fusion calibration deviation” (obtained in step 4) ± “Fusion calibration standard deviation” (obtained in step 7).

[0135] Example 2

[0136] The present application also provides a satellite radar altimeter adaptive fusion calibration processing device, which is implemented based on the above method, and the device includes:

[0137] An individual calibration module, used to adopt different strategies to perform calibration processing on each device in the calibration field individually; and

[0138] Fusion calibration module, used for fusion processing of data from various calibration devices;

[0139] The fusion processing includes: eliminating outlier points in the calibration deviation sequence, calculating the calibration statistical characteristics of a single calibration device, fusion calibration weights, fusion calibration deviation estimates, fusion calibration random errors, fusion calibration system errors, and fusion calibration accuracy, to obtain a final fusion calibration result.

[0140] The present application may also provide a computer device, comprising: at least one processor, a memory, at least one network interface and a user interface. The various components in the device are coupled together through a bus system. It is understood that the bus system is used to achieve connection and communication between these components. In addition to the data bus, the bus system also includes a power bus, a control bus and a status signal bus.

[0141] The user interface may include a display, a keyboard or a pointing device, such as a mouse, a trackball, a touch pad or a touch screen.

[0142] It is understood that the memory in the embodiments disclosed in the present application may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of RAM are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM), and direct memory bus random access memory (DRRAM). The memories described herein are intended to include, but are not limited to, these and any other suitable types of memories.

[0143] In some embodiments, the memory stores the following elements, executable modules or data structures, or a subset thereof, or an extended set thereof: an operating system and applications.

[0144] The operating system includes various system programs, such as a framework layer, a core library layer, a driver layer, etc., which are used to implement various basic services and process hardware-based tasks. The application includes various application programs, such as a media player (Media Player), a browser (Browser), etc., which are used to implement various application services. The program for implementing the method of the embodiment of the present disclosure can be included in the application.

[0145] In the above embodiment, the processor may also call a program or instruction stored in the memory, specifically, a program or instruction stored in an application program, and is used to:

[0146] Execute the steps of the above method.

[0147] The above method can be applied to a processor or implemented by a processor. The processor may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by an integrated logic circuit of hardware in the processor or an instruction in the form of software. The above processor may be a general processor, a digital signal processor (Digital Signal Processor, DSP), an application specific integrated circuit (Application Specific Integrated Circuit, ASIC), a field programmable gate array (Field Programmable Gate Array, FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The above-disclosed methods, steps and logic block diagrams can be implemented or executed. The general processor may be a microprocessor or the processor may also be any conventional processor, etc. The steps of the above-disclosed method can be directly embodied as a hardware decoding processor to execute, or the hardware and software modules in the decoding processor are combined to execute. The software module can be located in a mature storage medium in the field such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory or an electrically erasable programmable memory, a register, etc. The storage medium is located in the memory, and the processor reads the information in the memory and completes the steps of the above method in combination with its hardware.

[0148] It is understood that the embodiments described in the present application can be implemented by hardware, software, firmware, middleware, microcode or a combination thereof. For hardware implementation, the processing unit can be implemented in one or more application specific integrated circuits (ASIC), digital signal processors (DSP), digital signal processing devices (DSPD), programmable logic devices (PLD), field programmable gate arrays (FPGA), general-purpose processors, controllers, microcontrollers, microprocessors, other electronic units for performing the functions described in the present application or a combination thereof.

[0149] For software implementation, the technology of the present application can be implemented by executing the functional modules (such as procedures, functions, etc.) of the present application. The software code can be stored in a memory and executed by a processor. The memory can be implemented in the processor or outside the processor.

[0150] The present application may also provide a non-volatile storage medium for storing a computer program. When the computer program is executed by a processor, each step in the above method embodiment can be implemented.

[0151] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present application and are not intended to limit it. Although the present application is described in detail with reference to the embodiments, a person skilled in the art should understand that any modification or equivalent replacement of the technical solution of the present application does not depart from the spirit and scope of the technical solution of the present application and should be included in the scope of the claims of the present application.

Claims

1. A satellite radar altimeter adaptive fusion calibration processing method, comprising: Using different strategies, each device in the calibration field is calibrated individually; Then the data of each calibration device is fused and processed; The fusion processing includes: removing outlier points of the calibration deviation sequence, calculating the calibration statistical characteristics of a single calibration device, the fusion calibration weight, the fusion calibration deviation estimation value, the fusion calibration random error, the fusion calibration system error, and the fusion calibration accuracy, and obtaining the final fusion calibration result; The calculation of the calibration statistical characteristics of the single calibration device includes: The statistical characteristics of the calibration equipment, namely the calibration accuracy The calculation method is: Among them, N i represents the total number of valid calibration times of the i-th calibration device; σ i represents the standard deviation of the deviation sequence of the ith calibration device.

2. The satellite radar altimeter adaptive fusion calibration processing method according to claim 1, characterized in that: The different strategies are used to calibrate each device in the calibration field individually, including: Step 1: Preprocess the sea surface height observation sequence of the calibration equipment; Step 2: Perform power spectrum analysis and smoothing filtering on the sea surface height sequence; Step 3: Calculate the sea surface height sequence along the track in the altimeter calibration area; Step 4: Determine the satellite's overhead position and time; Step 5: Calculate the matching error; Step 6: Determine the sea surface height reference value of the calibration site; Step 7: Determine the sea surface height of the altimeter to be calibrated; Step 8: Subtract the sea surface height reference value of the calibration field from the sea surface height value of the altimeter to be calibrated to generate a sea surface height calibration deviation sequence.

3. The satellite radar altimeter adaptive fusion calibration processing method according to claim 2, characterized in that: When calculating the sea surface height sequence along the track in the altimeter calibration field area, For tide gauge stations, the sea level height SSH is calculated according to the following formula: SSH = orbital altitude - Ku-band distance after instrument error correction - Ku-band ionosphere correction - troposphere model correction - wet troposphere model correction - Ku-band sea state deviation correction - ocean tide correction solution based on FES model + ocean load tide For anchoring, the sea surface height SSH is calculated according to the following formula: SSH = orbital altitude - Ku-band distance after instrument error correction - Ku-band ionosphere correction - dry troposphere model correction - wet troposphere model correction - Ku-band sea state deviation correction For GNSS buoys, the sea surface height SSH is calculated according to the following formula: SSH = orbit altitude - Ku-band distance after instrument error correction - Ku-band ionosphere correction - dry troposphere model correction - wet troposphere model correction - Ku-band sea state deviation correction - solid tide correction - polar tide correction - ocean load tide.

4. The satellite radar altimeter adaptive fusion calibration processing method according to claim 2, characterized in that: The method of using different strategies to calibrate each device in the calibration field separately also includes: Step 9: Record the sea surface height calibration deviation sequence in a dynamic table, and update the dynamic table each time the deviation sequence of a single calibration device is obtained.

5. The satellite radar altimeter adaptive fusion calibration processing method according to claim 1, characterized in that: The calculating of the fusion calibration weight includes: Among them, w i represents the calibration weight of the i-th calibration device; Indicates the calibration accuracy of the i-th calibration device.

6. The satellite radar altimeter adaptive fusion calibration processing method according to claim 5, characterized in that: The calculating of the fusion calibration deviation estimate value comprises: in, represents the estimated value of fusion calibration deviation; w i represents the calibration weight of the i-th calibration device; represents the average deviation of the i-th calibration device: Among them, N i Indicates the total number of valid calibrations of the i-th calibration device; N indicates the total number of calibrations; Bias j,i Indicates the deviation value of the jth calibration of the i-th calibration device.

7. The satellite radar altimeter adaptive fusion calibration processing method according to claim 1, characterized in that: The calculating fusion calibration random error comprises: in, represents the random error of fusion calibration; Indicates the calibration accuracy of the i-th calibration device.

8. The satellite radar altimeter adaptive fusion calibration processing method according to claim 1, characterized in that: The calculation of the fusion calibration accuracy is: summing the square of the fusion calibration random error and the square of the fusion calibration system error, and then taking the square root.

9. The satellite radar altimeter adaptive fusion calibration processing method according to claim 1, characterized in that: The final fused calibration result is: fused calibration deviation estimation value±fused calibration accuracy.

10. A satellite radar altimeter adaptive fusion calibration processing device, implemented based on any method described in claims 1-9, characterized in that: The device comprises: An individual calibration module, used to adopt different strategies to perform calibration processing on each device in the calibration field individually; and Fusion calibration module, used for fusion processing of data from various calibration devices; The fusion processing includes: eliminating outlier points in the calibration deviation sequence, calculating the calibration statistical characteristics of a single calibration device, fusion calibration weights, fusion calibration deviation estimates, fusion calibration random errors, fusion calibration system errors, and fusion calibration accuracy, to obtain a final fusion calibration result.

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