Satellite-borne GNSS-R height measurement semi-physical closed-loop simulation verification system and method

Abstract

The application relates to the field of GNSS remote sensing detection, and discloses a satellite-borne GNSS-R height measurement semi-physical closed-loop simulation verification system and method. The system comprises a GNSS signal simulator, a satellite-borne GNSS-R load, a data processing module, an error correction and calculation module, an accuracy evaluation module, an error component determination module and an influence evaluation module. The GNSS signal simulator generates direct GNSS signals and reflected signals according to in-orbit observation scene data, and after response by a real satellite-borne GNSS-R load, time delay difference, environmental time delay correction parameters and geophysical correction parameters are obtained by the data processing module. The error correction and calculation module fuses the hardware time delay correction value, the environmental correction parameters and the geophysical correction parameters to calculate the height measurement value. The accuracy evaluation module determines the height measurement accuracy in combination with the height reference true value. The error component determination module decomposes two types of height measurement error components, namely, environmental and geophysical error components. The influence evaluation module analyzes the influence of multivariate disturbance on the accuracy and error components. The GNSS-R height measurement space-ground integrated closed-loop verification is realized.

Description

Technical Field

[0001] This application relates to the field of GNSS remote sensing technology, specifically to a spaceborne GNSS-R altimeter semi-physical closed-loop simulation verification system and method. Background Technology

[0002] Satellite remote sensing technology, as an important means of Earth observation, acquires physical parameters of the Earth's surface through spaceborne GNSS-R payloads and has been widely applied in fields such as weather forecasting, environmental monitoring, and disaster prevention and mitigation. With the rapid development of satellite technology, various types of spaceborne GNSS-R payloads are constantly emerging, and their performance verification has become a key link in ensuring the reliability of on-orbit applications.

[0003] Ground verification of spaceborne GNSS-R payloads primarily employs two methods: pure theoretical simulation and field tests. Pure theoretical simulation generates simulation data by constructing a virtual environment using software, while field tests involve data acquisition and analysis in real-world scenarios. These verification methods, through steps such as establishing mathematical models, generating test signals, collecting observational data, and performing data processing, enable the evaluation of the performance of spaceborne GNSS-R payloads.

[0004] However, purely theoretical simulations cannot reproduce the actual physical effects of spaceborne GNSS-R payloads during on-orbit operation, leading to discrepancies between simulation results and actual on-orbit conditions. Field tests, on the other hand, face even more objective challenges, resulting in unreliable tests and making it difficult to transfer verification results to on-orbit applications. Summary of the Invention

[0005] In view of the above problems, this application provides a spaceborne GNSS-R altimeter semi-physical closed-loop simulation verification system and method to solve the technical problems of unrealistic simulation and unreliable test in the prior art.

[0006] The first aspect of this application provides a semi-physical closed-loop simulation verification system for spaceborne GNSS-R altimeter measurement, comprising: a GNSS signal simulator for generating GNSS direct and GNSS reflected signals based on observation scene data from the on-orbit operation of the spaceborne GNSS-R payload; the spaceborne GNSS-R payload for receiving the GNSS direct and reflected signals to output observation data; a data processing module for parsing the observation data using an analytical algorithm to obtain the time delay difference, environmental time delay correction parameters, and geophysical correction parameters between the GNSS reflected and direct signals; and an error correction and calculation module for correcting the time delay difference using the environmental time delay correction parameters and a preset hardware time delay correction value to obtain a corrected time delay difference, and calculating the error based on the corrected time delay difference and the geophysical correction parameters. The system obtains the altitude measurement value of the observed object; an accuracy evaluation module is used to determine the altitude measurement accuracy of the spaceborne GNSS-R payload based on the altitude measurement value and the true altitude reference value; an error component determination module is used to determine a first altitude measurement error component based on the true environmental time delay reference value and the environmental time delay correction parameter, and to determine a second altitude measurement error component based on the true geophysical reference value and the geophysical correction parameter; the true altitude reference value, the true environmental time delay reference value, and the true geophysical reference value are all parameters determined based on the observation scene data; an impact evaluation module is used to analyze the impact on the altitude measurement accuracy, the first altitude measurement error component, and the second altitude measurement error component after adjusting at least one of the observation scene data, the direct GNSS signal, the reflected GNSS signal, the state of the spaceborne GNSS-R payload, and the analytical algorithm.

[0007] In some optional embodiments, the GNSS signal simulator is further configured to send a combined test signal with a preset time delay truth value to the spaceborne GNSS-R payload; the system further includes a hardware time delay calibration module, configured to acquire test observation data output by the spaceborne GNSS-R payload to determine the test signal time delay; and to determine the preset hardware time delay correction value based on the preset time delay truth value and the test signal time delay.

[0008] In some optional embodiments, the number of combined test signals is multiple; the hardware delay calibration module is further configured to calculate a delay threshold based on the test signal delay corresponding to the multiple combined test signals; filter the test signal delay corresponding to the multiple combined test signals based on the delay threshold to obtain the filtered test signal delay; and determine the preset hardware delay correction value based on the preset delay truth value and the filtered test signal delay.

[0009] In some optional embodiments, the hardware delay calibration module is further configured to perform an average calculation on the delay of the test signals corresponding to multiple combined test signals to obtain an average delay value; and calculate a delay threshold based on the average delay value.

[0010] In some optional embodiments, the hardware delay calibration module is further configured to traverse the test signal delays corresponding to the plurality of combined test signals; if the traversed test signal delay is greater than the delay threshold, the traversed test signal delay is filtered out to obtain the filtered test signal delay.

[0011] In some optional embodiments, the data processing module is further configured to preprocess the observation data to obtain preprocessed observation data; wherein the preprocessing includes at least one of data timestamp alignment, attitude data correction, and spatial information calculation; perform signal enhancement processing on the preprocessed observation data to obtain enhanced observation data; and parse the enhanced observation data based on an analytical algorithm to obtain the time delay difference between the GNSS reflected signal and the GNSS direct signal, environmental time delay correction parameters, and geophysical correction parameters.

[0012] In some optional embodiments, the enhanced observation data includes the reflected signal power waveform, observation time, location, and environmental parameters; the data processing module is further configured to analyze the reflected signal power waveform based on an analytical algorithm to obtain the time delay difference between the GNSS reflected signal and the GNSS direct signal; and to calculate environmental time delay correction parameters and geophysical correction parameters based on the observation time, location, and environmental parameters.

[0013] In some optional embodiments, the accuracy assessment module is further configured to calculate the difference between the measured altitude value and the true altitude reference value; and determine the altitude measurement accuracy of the spaceborne GNSS-R payload based on the difference.

[0014] In some optional embodiments, the observation scene data includes a first environmental parameter of the observed object and a second environmental parameter of the signal propagation path; the GNSS signal simulator is further configured to determine the signal receiving power of the spaceborne GNSS-R payload based on the first environmental parameter and the signal propagation data; determine the signal receiving delay of the spaceborne GNSS-R payload based on the second environmental parameter and the signal propagation data; and generate GNSS direct signal and GNSS reflected signal based on the signal receiving delay and the signal receiving power.

[0015] In some optional embodiments, the observation scene data includes spatiotemporal parameters of the observed object; the system further includes: a height reference truth value module, used to determine a reference simulation value and a correction amount from the simulation model and the correction model respectively based on the spatiotemporal parameters; and to correct the reference simulation value based on the correction amount to obtain the height reference truth value.

[0016] The second aspect of this application provides a semi-physical closed-loop simulation verification method for spaceborne GNSS-R altimeter measurement, comprising: generating GNSS direct signal and GNSS reflected signal based on observation scene data during the on-orbit operation of the spaceborne GNSS-R payload; transmitting the GNSS direct signal and the GNSS reflected signal to the spaceborne GNSS-R payload and acquiring the observation data output by the spaceborne GNSS-R payload; parsing the observation data based on an analytical algorithm to obtain the time delay difference between the GNSS reflected signal and the GNSS direct signal, environmental time delay correction parameters, and geophysical correction parameters; correcting the time delay difference using the environmental time delay correction parameters and a preset hardware time delay correction value to obtain a corrected time delay difference; and based on the corrected time delay difference and the geophysical... The altitude measurement value of the observed object is obtained by calculating the correction parameters; the altitude measurement accuracy of the spaceborne GNSS-R payload is determined based on the altitude measurement value and the true altitude reference value; a first altitude measurement error component is determined based on the true environmental time delay reference value and the environmental time delay correction parameters, and a second altitude measurement error component is determined based on the true geophysical reference value and the geophysical correction parameters; the true altitude reference value, the true environmental time delay reference value, and the true geophysical reference value are all parameters determined based on the observation scene data; after adjusting at least one of the observation scene data, the GNSS direct signal, the GNSS reflected signal, the GNSS-R payload state, and the analytical algorithm, the impact on the altitude measurement accuracy, the first altitude measurement error component, and the second altitude measurement error component is analyzed.

[0017] In some optional embodiments, the method further includes: sending a combined test signal with a preset time delay truth value to the spaceborne GNSS-R payload, and acquiring test observation data output by the spaceborne GNSS-R payload to determine the test signal time delay; and determining the preset hardware time delay correction value based on the preset time delay truth value and the test signal time delay.

[0018] In some optional embodiments, the number of combined test signals is multiple; determining the preset hardware delay correction value based on the preset delay truth value and the test signal delay includes: calculating a delay threshold based on the test signal delays corresponding to the multiple combined test signals; filtering the test signal delays corresponding to the multiple combined test signals based on the delay threshold to obtain filtered test signal delays; and determining the preset hardware delay correction value based on the preset delay truth value and the filtered test signal delays.

[0019] In some optional embodiments, the delay threshold is calculated based on the test signal delays corresponding to multiple combined test signals, including: averaging the test signal delays corresponding to multiple combined test signals to obtain an average delay value; and calculating the delay threshold based on the average delay value.

[0020] In some optional embodiments, the test signal delays corresponding to the plurality of combined test signals are filtered based on the delay threshold to obtain the filtered test signal delays, including: traversing the test signal delays corresponding to the plurality of combined test signals; if the traversed test signal delay is greater than the delay threshold, the traversed test signal delay is filtered out to obtain the filtered test signal delays.

[0021] In some optional embodiments, the observation data is analyzed based on an analytical algorithm to obtain the time delay difference, environmental time delay correction parameters, and geophysical correction parameters between the GNSS reflected signal and the GNSS direct signal. This includes: preprocessing the observation data to obtain preprocessed observation data; wherein the preprocessing includes at least one of data timestamp alignment, attitude data correction, and spatial information calculation; performing signal enhancement processing on the preprocessed observation data to obtain enhanced observation data; and analyzing the enhanced observation data based on an analytical algorithm to obtain the time delay difference, environmental time delay correction parameters, and geophysical correction parameters between the GNSS reflected signal and the GNSS direct signal.

[0022] In some optional embodiments, the enhanced observation data includes the reflected signal power waveform, observation time, location, and environmental parameters; the enhanced observation data is analyzed based on an analytical algorithm to obtain the time delay difference between the GNSS reflected signal and the GNSS direct signal, environmental time delay correction parameters, and geophysical correction parameters, including: analyzing the reflected signal power waveform based on a waveform analysis algorithm to obtain the time delay difference between the GNSS reflected signal and the GNSS direct signal; and calculating the environmental time delay correction parameters and geophysical correction parameters based on the observation time, location, and environmental parameters.

[0023] In some optional embodiments, determining the altimetry accuracy of the spaceborne GNSS-R payload based on the measured altitude value and the true altitude reference value includes: calculating the difference between the measured altitude value and the true altitude reference value; and determining the altimetry accuracy of the spaceborne GNSS-R payload based on the difference.

[0024] In some optional embodiments, the observation scene data includes a first environmental parameter of the observed object and a second environmental parameter of the signal propagation path; generating GNSS direct signal and GNSS reflected signal based on the observation scene data of the spaceborne GNSS-R payload during its on-orbit operation includes: determining the signal receiving power of the spaceborne GNSS-R payload based on the first environmental parameter and the signal propagation data; determining the signal receiving delay of the spaceborne GNSS-R payload based on the second environmental parameter and the signal propagation data; and generating GNSS direct signal and GNSS reflected signal based on the signal receiving delay and the signal receiving power.

[0025] In some optional embodiments, the observation scene data includes spatiotemporal parameters of the observed object; the method further includes: determining a baseline simulation value and a correction amount from the simulation model and the correction model respectively based on the spatiotemporal parameters; and correcting the baseline simulation value based on the correction amount to obtain the true value of the height baseline.

[0026] This application achieves end-to-end verification of a spaceborne GNSS-R payload. Through a complete process of "generating direct and reflected signals → GNSS-R payload in-loop testing → data processing → error correction and calculation → accuracy assessment → error component determination → impact assessment," a test closed loop is constructed that is isomorphic to the spaceborne GNSS-R payload during in-orbit operation. Specifically, direct and reflected signals are generated based on observation scenario data from the spaceborne GNSS-R payload during in-orbit operation, making the direct and reflected signals more closely resemble the in-orbit operating scenario and improving their realism. The direct and reflected signals are then sent to a real spaceborne GNSS-R payload, ensuring that the observation data output by the spaceborne GNSS-R payload reflects the physical effects generated by the actual hardware during in-orbit operation. This application corrects for time delay errors by introducing a preset hardware time delay correction value, eliminating the influence of inherent systematic errors of the actual hardware on the observation data. Based on the corrected time delay difference and the geophysical correction parameters obtained through analysis, the altitude measurement value of the observed object is calculated, thereby improving the accuracy of the altitude measurement value. This application also introduces a true altitude reference value, which is combined with the measured altitude value for analysis to accurately determine the altimetry accuracy of the spaceborne GNSS-R payload. This application can also determine the first altimetry error component corresponding to the environmental delay correction parameters, and the second altimetry error component corresponding to the geophysical correction parameters. After adjusting at least one of the following: observation scene data, GNSS direct signal, GNSS reflected signal, GNSS-R payload state, and analytical algorithm, the impact on the altimetry accuracy of the spaceborne GNSS-R, the first altimetry error component, and the second altimetry error component is analyzed. This allows for high-fidelity, repeatable, and low-cost verification testing, providing reliable technical support for scheme optimization, hardware debugging, and performance evaluation.

[0027] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application. Attached Figure Description

[0028] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application. It is obvious that the drawings described below are merely some embodiments of this application, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort.

[0029] Figure 1 This is a schematic flowchart illustrating an exemplary embodiment of a spaceborne GNSS-R altimeter semi-physical closed-loop simulation verification method.

[0030] Figure 2 This is a flowchart illustrating a method for determining a preset hardware latency correction value, as shown in an exemplary embodiment of this application.

[0031] Figure 3 Based on Figure 2 The exemplary embodiment shown illustrates a flowchart of another method for determining a preset hardware latency correction value.

[0032] Figure 4 This is a schematic diagram of the structure of a spaceborne GNSS-R altimeter semi-physical closed-loop simulation verification system, as illustrated in an exemplary embodiment of this application.

[0033] Figure 5 Based on Figure 4 The illustrated embodiment shows a schematic diagram of another spaceborne GNSS-R altimeter semi-physical closed-loop simulation verification system.

[0034] Figure 6 This is the calibration result of the hardware delay difference at frequency B1 of the spaceborne GNSS-R altimeter semi-physical closed-loop simulation verification system of this application.

[0035] Figure 7 This is a comparison chart of the sea surface height output by the spaceborne GNSS-R altimeter semi-physical closed-loop simulation verification system of this application and the true value of the simulation input.

[0036] Figure 8 This is a comparison chart of the true values ​​of the ionospheric TEC calculated using the dual-frequency direct and reflected signals of GNSS dual-frequency altimetry in this application and the simulation input. Detailed Implementation

[0037] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numerals in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of systems and methods consistent with some aspects of this application as detailed in the appended claims.

[0038] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.

[0039] The flowcharts shown in the accompanying drawings are merely illustrative and do not necessarily include all content and operations / steps, nor do they necessarily have to be performed in the described order. For example, some operations / steps can be broken down, while others can be combined or partially combined; therefore, the actual execution order may change depending on the specific circumstances.

[0040] In this application, "multiple" refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. The character " / " generally indicates that the preceding and following related objects have an "or" relationship.

[0041] Ground verification of spaceborne GNSS-R payloads primarily employs two methods: pure theoretical simulation and field tests. Pure theoretical simulation generates simulation data by constructing a virtual environment using software, while field tests involve data acquisition and analysis in real-world scenarios. These verification methods, through steps such as establishing mathematical models, generating test signals, collecting observational data, and performing data processing, enable the evaluation of the performance of spaceborne GNSS-R payloads.

[0042] However, purely theoretical simulations lack hardware involvement and cannot reproduce the actual physical effects of spaceborne GNSS-R payloads during on-orbit operation, leading to discrepancies between simulation results and actual on-orbit conditions. Field tests, on the other hand, face even more objective problems, resulting in unreliable tests and making it difficult to transfer verification results to on-orbit applications.

[0043] To address this issue, one aspect of this application provides a semi-physical closed-loop simulation verification method for spaceborne GNSS-R altimeter measurement, thereby resolving the technical problems of unrealistic simulations and unreliable experiments in existing technologies. Please refer to the details below. Figure 1 , Figure 1 This is a schematic flowchart illustrating an exemplary embodiment of a spaceborne GNSS-R altimeter semi-physical closed-loop simulation verification method. The method includes at least steps S110 to S170, which are described in detail below:

[0044] S110 generates GNSS direct and GNSS reflected signals based on observation scene data from the on-orbit operation of the spaceborne GNSS-R payload.

[0045] A spaceborne GNSS-R payload refers to an observation device and / or equipment carried on an in-orbit satellite, capable of receiving and processing space navigation signals. Its hardware includes a direct / reflected dual-channel RF receiving front-end, a high-speed ADC sampling module, an FPGA real-time signal processing unit, and data storage and downlink interfaces. A spaceborne GNSS-R payload can observe objects in space. Specifically, it obtains the attribute values ​​of the observed object based on the received signals and inverses these signals, thus achieving attribute observation of the observed object. For example, a GNSS-R (Global Navigation Satellite System Reflectometry) interferometer can receive direct signals from a space signal source and the reflected signals after the direct signals are reflected by the sea surface (the observed object), and inversely calculate the sea surface height based on the direct and reflected signals.

[0046] The observation scene data is a spatiotemporal collection of data characterizing the relative motion relationship between the spaceborne GNSS-R payload and the space signal source, the signal propagation path characteristics, and the target reflection characteristics. It includes, but is not limited to, the first on-orbit operation data of the spaceborne GNSS-R payload (e.g., the ephemeris of the mission satellite carrying the spaceborne GNSS-R payload), the second on-orbit operation data of the space signal source (e.g., the ephemeris of the signal transmitting satellite), attitude parameters, timestamp sequences, space signal source ephemeris, latitude and longitude and altitude of the specular reflection point (i.e., the observed object, such as the sea surface), atmospheric temperature, humidity and pressure and ionospheric TEC along the signal propagation path, incident angle, and azimuth angle.

[0047] GNSS direct signal refers to the original navigation signal transmitted by a GNSS satellite, which is received by the onboard GNSS-R payload after free propagation in space. GNSS reflected signal refers to the scattered signal received by the onboard GNSS-R payload after the same GNSS signal is specularly reflected by the observed object (e.g., the sea surface). There is a measurable time delay difference between the two at the time of reception. This time delay difference is a function of the satellite-sea distance and is the basic observation for inverting the altitude of the observed object.

[0048] In some embodiments, the observation scene data includes a first environmental parameter of the observed object and a second environmental parameter of the signal propagation path; based on the observation scene data of the onboard GNSS-R payload during its on-orbit operation, GNSS direct signal and GNSS reflected signal are generated, including S111 to S113:

[0049] S111 determines the signal receiving power of the spaceborne GNSS-R payload based on the first environmental parameters and signal propagation data.

[0050] The first environmental parameter is a set of environmental parameters characterizing the physical state and surface characteristics of the observed object, including but not limited to sea surface wind speed, significant wave height, sea surface temperature, sea surface salinity, sea surface dielectric constant, and sea surface roughness spectrum parameters; the signal propagation data is a set of data characterizing the propagation path characteristics of GNSS direct and reflected signals in space, including but not limited to the spatial location information of the observed object, atmospheric temperature, humidity, pressure and ionospheric TEC along the signal propagation path, the path difference between the direct path and the reflected path, antenna installation geometry, incident angle, elevation angle, signal polarization, and carrier frequency.

[0051] Based on the first environmental parameters and signal propagation data, the signal receiving power of the spaceborne GNSS-R payload is determined, including: based on the sea surface wind speed and significant wave height in the first environmental parameters, combined with the radar equation and the Kirchhoff Approximation (KA) scattering model, the backscattering coefficient of the GNSS reflected signal at the specular reflection point is calculated; then, based on the antenna gain of the spaceborne GNSS-R payload, the propagation distance of the direct and reflected signals, the signal frequency, and the polarization, the power value of the reflected signal reaching the receiver's RF front end is inferred; the receiving power of the direct signal mainly depends on the satellite's transmit power, free space path loss, and receiving antenna gain. The influence of the first environmental parameters can be ignored in its calculation process, but it needs to maintain a consistent relative relationship with the reflected signal power.

[0052] For example, in the BeiDou / GNSS-R interferometric altimetry verification scenario, after acquiring the LEO satellite orbital parameters and BDS satellite ephemeris, the system calculates in real time the spatial location information of the mirror reflection point at a certain moment as 121.5°E, 30.2°N, and altitude. 12m; the wind speed (6.2m / s), significant wave height (1.8m), and sea surface dielectric constant (75) at this latitude and longitude were extracted from ECMWF sea surface products; based on these, the radar equations and KA model were substituted to calculate the received power of the L-band reflected signal on the spaceborne GNSS-R payload to be approximately 142dBm.

[0053] S112 determines the signal reception delay of the spaceborne GNSS-R payload based on the second environmental parameters and signal propagation data.

[0054] The second environmental parameter is environmental data characterizing the signal propagation path. It is a set of parameters characterizing the physical properties of the transmission medium in the propagation space, including but not limited to atmospheric temperature profile, atmospheric humidity profile, atmospheric pressure profile, total electron content of the ionosphere, and ionospheric height profile. The signal propagation data includes the propagation path of GNSS direct and reflected signals, spatial coordinates of the reflection point, propagation distance, geometric elevation angle, and Doppler shift.

[0055] Based on the second environmental parameters and signal propagation data, the signal reception delay of the spaceborne GNSS-R payload was determined, including: calculating the tropospheric slant path delay using a ray tracing algorithm based on the tropospheric three-dimensional profile data in the second environmental parameters; and calculating the tropospheric TEC distribution delay using I=40.3×TEC / f, combined with the signal frequency and penetration angle. 2 The formula calculates the ionospheric group delay; where I represents the ionospheric group delay, TEC represents the total electron content along the signal propagation path, and f represents the signal frequency. The vacuum geometric propagation delay (calculated from the spatial coordinates of the satellite, reflection point, and receiver) is then superimposed to obtain the total propagation delay of both the direct and reflected signals. The reflected signal delay comprises three parts: the direct path segment (satellite → reflection point), the reflection segment (phase center shift at the reflection point), and the reflection path segment (reflection point → receiver), and each segment is modulated by the second environmental parameter at the corresponding location.

[0056] For example, in the BeiDou / GNSS-R interferometric altimetry verification scenario, the spaceborne GNSS-R payload is located in a low Earth orbit (altitude approximately 500 km), and the space signal source is the BDS-3 MEO satellite; the second environmental data is obtained from the ECMWF atmospheric three-dimensional profile (37 layers, 1hPa–1000hPa) and the JPL-GIM ionospheric TEC grid (5°×2.5°, 450 km altitude); the signal propagation data solution yields a direct path length of 20342 km for the simulated source signal and a reflection path length of 20343.8 km for the simulated reflected signal; after Snell refraction path integration calculation, the tropospheric delay contribution is 2.1 ns, the ionospheric delay contribution is 5.7 ns, and after superimposing the vacuum geometric delay, the final determination of the direct signal reception delay is 20.4124 μs, and the reflection signal reception delay is 21.8670 μs.

[0057] S113 generates GNSS direct signal and GNSS reflected signal based on signal reception delay and signal reception power.

[0058] Signal reception delay is a key parameter used to control the timing generator inside the GNSS signal simulator, which determines the relative offset of direct and reflected signals on the time axis; signal reception power is a key parameter used to configure the gain and carrier-to-noise ratio of the GNSS signal simulator's RF output channel, which determines the signal-to-noise ratio level and dynamic range of the signal in the amplitude domain.

[0059] The process involves generating GNSS direct and reflected signals based on signal reception delay and power. This includes: using the calculated delay value as the initial phase offset and the power value as the signal amplitude scaling factor, and injecting them into the digital waveform synthesis module of the GNSS signal simulator. This module generates baseband I / Q signals with true code phase, carrier phase, Doppler shift, noise spectral density, and power spectral density based on standard navigation signal structures such as GPS C / A code, BDS B1I / B3I code, and Galileo E1 / E5a. These signals are then digitally up-converted and DAC-converted to output radio frequency-grade GNSS direct and reflected signals. The two signals strictly satisfy the calculated delay difference relationship in the time domain and the calculated power ratio relationship in the power domain.

[0060] This embodiment structures the observation scene data into a first environmental parameter and a second environmental parameter, allowing the GNSS signal simulator to independently calculate the signal reception power and delay based on both parameters, thus avoiding physical distortion caused by traditional single-system parameters. Since the signal reception power is driven by the first environmental parameter, it can realistically reflect the energy attenuation characteristics of reflected signals under different sea states. Since the signal reception delay is driven by the second environmental parameter, it can accurately reproduce the spatiotemporal disturbance effects of the atmosphere and ionosphere on the propagation path. As the final signal is generated by the combined constraints of the two parameters, it significantly improves the physical fidelity and scene adaptability of GNSS direct and reflected signals in the hardware-in-the-loop simulation, providing a quantifiable, traceable, and reproducible technical foundation for the credibility verification of spaceborne GNSS-R payloads.

[0061] The S120 transmits direct and reflected GNSS signals to the onboard GNSS-R payload and acquires the observation data output by the onboard GNSS-R payload.

[0062] Observational data refers to the raw processed data output by the spaceborne GNSS-R payload after receiving direct and reflected GNSS signals, processed through its entire on-orbit signal chain (including antennas, filters, amplifiers, mixers, ADCs, digital downconverters, correlators, etc.). Its format is completely consistent with the on-orbit measured data, including I / Q quadrature sampling data streams, acquisition timestamps, spaceborne GNSS-R payload operating status parameters, and auxiliary navigation information. For example, direct and reflected signals can be directly connected to the RF input port of the spaceborne GNSS-R payload via a low-loss RF cable (insertion loss less than 0.5 dB), allowing the signal to bypass the antenna radiation stage, avoiding anechoic chamber reflection interference, and ensuring the purity of the input signal. Another example is radiating direct and reflected signals through a transmitting antenna in a microwave anechoic chamber, which are then received by the original antenna of the spaceborne GNSS-R payload, reproducing the actual electromagnetic coupling process. This embodiment involves deploying a programmable attenuator and phase adjuster between the GNSS signal simulator and the spaceborne GNSS-R payload to dynamically adjust the signal power and phase relationship, simulating reception conditions under different orbital altitudes and signal-to-noise ratios. This embodiment completes the injection of direct and reflected signals and the acquisition of observation data based on any example method, ensuring that the acquired data fully reflects the inherent hardware characteristics of the spaceborne GNSS-R payload.

[0063] S130 analyzes the observation data using an analytical algorithm to obtain the time delay difference between the GNSS reflected signal and the GNSS direct signal, as well as the environmental time delay correction parameters and the geophysical correction parameters.

[0064] The analytical algorithm is a set of modular processing logics used to jointly extract time delay difference and correction parameters from raw observation data. Its input is observation data and its output is a set of three key parameters: time delay difference, environmental delay correction parameters, and geophysical correction parameters.

[0065] Here is an example of the S130 parsing method: At least one preprocessing operation is performed on the observation data, including data timestamp alignment, attitude data correction, and spatial information calculation, to eliminate macroscopic systematic deviations in the original observation data caused by multi-source asynchronous acquisition, platform attitude disturbances, and inconsistencies in the spatial coordinate system; signal enhancement processing is then performed on the preprocessed observation data to improve its signal-to-noise ratio and waveform structure discernibility; based on the analytical algorithm, inherent systematic error compensation is performed on the enhanced observation data to form corrected observation data with time consistency, attitude stability, spatial geometric accuracy, and high signal-to-noise ratio, ensuring the robustness and effectiveness of the parsing process.

[0066] In some embodiments, the data processing module is further configured to preprocess the observation data to obtain preprocessed observation data; wherein, the preprocessing includes at least one of data timestamp alignment, attitude data correction, and spatial information calculation; perform signal enhancement processing on the preprocessed observation data to obtain enhanced observation data; and analyze the enhanced observation data based on an analytical algorithm to obtain the time delay difference between the GNSS reflected signal and the GNSS direct signal, environmental time delay correction parameters, and geophysical correction parameters, including S131 to S133:

[0067] S131 Preprocesses the observation data to obtain preprocessed observation data; wherein, the preprocessing includes at least one of data timestamp alignment, attitude data correction, and spatial information calculation.

[0068] Data timestamp alignment refers to resampling or interpolating observation data from different sensors or acquisition channels based on a unified time reference (such as Coordinated Universal Time UTC or the absolute timestamp after synchronization with the local clock of the spaceborne GNSS-R payload). This ensures that the data from each source have a strict correspondence in the time dimension, which can be used to eliminate time offset errors caused by multi-source asynchronous acquisition, thereby ensuring the timing consistency of direct and reflected signal waveform comparison in subsequent data processing. Its function is to provide input data with time consistency for subsequent signal enhancement and analysis, avoiding false time delay differences introduced by time misalignment.

[0069] Attitude data correction refers to the compensation of signal phase shifts and geometric projection deviations caused by platform attitude disturbances in the original observation data based on the attitude angles (pitch angle, roll angle, yaw angle) and their rate of change acquired in real time during the on-orbit operation of the spaceborne GNSS-R payload. It can be based on attitude quaternions or direction cosine matrices to perform rotation mapping on the coordinates of the original sampling points or the signal phase. Its function is to eliminate the influence of payload attitude drift on the positioning accuracy of the mirror reflection point, ensure the geometric accuracy of the propagation path calculation of the reflected signal, and thus support the subsequent signal reception delay and power modeling based on the propagation path.

[0070] Spatial information calculation refers to the precise ground-based calculation, coordinate system transformation, and geometric error compensation of parameters related to spatial geometry in the original observation data (such as the position of the specular reflection point, the position of the GNSS satellite, the position of the spaceborne GNSS-R payload, the signal angle of arrival, and the estimated propagation distance) based on the spatial position (three-dimensional coordinates) of the spaceborne GNSS-R payload, the precise ephemeris of the GNSS satellite, the antenna installation matrix, and the phase center offset. For example, it involves transforming the observation data from the sensor coordinate system to the geocentric coordinate system or the geocentric inertial coordinate system, and correcting the systematic time delay deviation caused by the physical installation of the antenna.

[0071] S132 performs signal enhancement processing on the preprocessed observation data to obtain enhanced observation data.

[0072] Signal enhancement processing refers to strengthening the information components related to the attributes of the observed object in the observed data by improving the signal-to-noise ratio or enhancing the discernibility of the signal structure. For example, incoherent accumulation, adaptive filtering, wavelet denoising, matched filtering, or waveform averaging methods are used to statistically or deterministically enhance the original signal. Its function is to suppress the influence of thermal noise, quantization noise, and electromagnetic interference on the relevant power waveform, highlight the relative time delay characteristics between direct and reflected signals, and provide data input with sufficient signal-to-noise ratio and clear waveform structure for subsequent accurate analysis based on analytical algorithms, avoiding the distortion of analytical parameter fitting under low signal-to-noise ratio.

[0073] S133 uses an analytical algorithm to analyze the enhanced observation data and obtains the time delay difference between the GNSS reflected signal and the GNSS direct signal, environmental time delay correction parameters, and geophysical correction parameters.

[0074] The enhanced observation data includes the reflected signal power waveform, observation time, location, and environmental parameters. Based on analytical algorithms, the enhanced observation data is analyzed to obtain the time delay difference between the GNSS reflected signal and the GNSS direct signal, environmental time delay correction parameters, and geophysical correction parameters. This includes: analyzing the reflected signal power waveform using analytical algorithms to obtain the time delay difference between the GNSS reflected signal and the GNSS direct signal; and calculating the environmental time delay correction parameters and geophysical correction parameters based on the observation time, location, and environmental parameters.

[0075] Among them, the time delay difference is the time difference between the reflected and direct signals reaching the phase center of the receiver antenna, and is the sum of the time delay value corresponding to the specular reflection point on the relevant power waveform and the open-loop tracking value of the time delay difference; the environmental time delay correction parameter is a numerical parameter used to compensate for the additional time delay of the signal in the propagation medium caused by the atmosphere and ionosphere, including but not limited to tropospheric dry delay, wet delay, and ionospheric delay; the geophysical correction parameter is a numerical parameter used to correct the height shift of the reflection point caused by geophysical processes such as ocean tides, solid earth tides, polar tides, dynamic atmospheric pressure, and sea state deviations.

[0076] For example, the least squares fitting method can be used to treat the environmental time delay correction parameters and geophysical correction parameters as variables to be estimated. The observation results of test signals with multiple known time delay values ​​can be used as constraints to iteratively optimize the parameters and apply them to the observation data. Alternatively, the environmental time delay correction parameters and geophysical correction parameters can be embedded into the kernel of the relevant power waveform re-tracking algorithm to synchronously correct the time delay deviation between channels during the waveform matching process and directly output the analytical results.

[0077] This embodiment ensures strict consistency of observation data in the time and spatial domains by sequentially performing data timestamp alignment, attitude data correction, and spatial information calculation. Signal enhancement processing significantly improves the detectability and stability of specular reflection features in the relevant power waveform. Furthermore, based on analytical algorithms, the enhanced observation data is jointly analyzed. While ensuring the physical interpretability of each parameter, the time delay difference, environmental time delay correction parameters, and geophysical correction parameters are output simultaneously. This provides a high-quality, traceable, and reproducible data foundation for subsequent hardware time delay correction, separation of environmental and physical errors, altitude measurement calculation, and accuracy assessment, effectively solving the technical problem of low analytical accuracy caused by poor quality of the original observation data.

[0078] S140 uses environmental time delay correction parameters and preset hardware time delay correction values ​​to correct the time delay difference, obtains the corrected time delay difference, and calculates the height measurement value of the observed object based on the corrected time delay difference and geophysical correction parameters.

[0079] The preset hardware delay correction value is a numerical parameter used to compensate for the fixed signal propagation delay introduced by the signal simulator, radio frequency transmission link and the front-end circuit of the onboard GNSS-R payload. Its physical meaning is the average value of the systematic deviation between the test signal delay and the corresponding preset delay true value. This value is determined by the hardware delay calibration module in calibration mode based on the observation scenario data of the onboard GNSS-R payload during operation in orbit. Depending on the connection of the simulation system, the typical hardware delay correction value can reach the meter level.

[0080] The correction time delay difference is the pure geometric time delay difference after eliminating the influence of environment and hardware, and it is the core input for altitude inversion; the geophysical correction parameters are used to correct the dynamic fluctuations of the reflector reference surface to ensure the consistency of the altitude calculation reference.

[0081] The time delay difference is corrected using environmental time delay correction parameters and preset hardware time delay correction values ​​to generate a corrected time delay difference. The height measurement value of the observed object is then calculated based on the corrected time delay difference and geophysical correction parameters. This process includes: firstly, subtracting the original time delay difference using the hardware time delay correction value, and then performing a second subtraction correction by superimposing atmospheric / ionospheric environmental time delay correction parameters to obtain the corrected time delay difference; subsequently, substituting this corrected time delay difference into the star-sea geometric model (including the reference ellipsoid, the incident angle of the reflected signal, and the constant of the speed of light), and dynamically correcting the height reference of the reflecting surface in combination with geophysical correction parameters, finally calculating the height measurement value of the observed object (e.g., the sea surface).

[0082] For example, take the original delay difference of the above output (e.g., 1.234567 ms), subtract the hardware delay correction value (e.g., the delay corresponding to 0.003 mm ≈ 0.01 ns), and then subtract the tropospheric wet delay (e.g., 0.12 ns) and the ionospheric TEC delay (e.g., 0.89 ns) to obtain the corrected delay difference (e.g., 1.233468 ms); substitute this value into the formula h = c × Δt / 2sinθ + h ref +δh phys Where c is the speed of light, θ is the incident angle of the reflected signal, and h ref For the reference ellipsoid height, δh phys The sum of geophysical correction parameters (including ocean tides, solid tides, polar tides, and DAC) is used to finally calculate the sea surface height measurement (e.g., 12.345 m).

[0083] S150 determines the altitude measurement accuracy of the spaceborne GNSS-R payload based on the measured altitude value and the true altitude reference value.

[0084] The true altitude reference value is a parameter determined based on the observation scenario data of the onboard GNSS-R payload during its operation in orbit. It is the standard value of the target physical quantity obtained by independent high-precision measurement during the verification process. For example, the true sea surface altitude data calculated by the onboard propagation environment simulation subsystem is based on the DTU21 mean sea surface height model superimposed with multi-source geophysical models such as GOT tides, IERS polar tides, Munk-Cartwright solid tides, and CLS-MOG2D-G dynamic atmospheric corrections. It has both long-term stability and short-term dynamic response capability.

[0085] Altitude measurement accuracy is a quantitative indicator of the consistency between the altitude measurement value output by the spaceborne GNSS-R payload and the true altitude reference value. It is a comprehensive metric used to characterize the degree of closeness between the observation result and the true value. Its characterization forms include, but are not limited to, root mean square error, standard deviation, mean absolute error, and systematic bias.

[0086] For example, the difference between the measured altitude value and the true altitude reference value is calculated; the altitude measurement accuracy of the spaceborne GNSS-R payload is determined based on the difference.

[0087] For example, calculate the point-by-point difference sequence between the measured height and the true height reference value; calculate the mean, standard deviation and root mean square error of the difference sequence; and determine whether the load meets the height measurement accuracy requirements based on a preset threshold (e.g., RMSE ≤ 20 cm).

[0088] For example, the calculated 24-hour continuous sea surface height measurement sequence (time resolution of 5 Hz) is compared point by point with the corresponding time period height reference true value sequence (same time resolution) output by the spaceborne propagation environment simulation subsystem, and the difference sequence is calculated. The mean of this sequence is 0.8 cm, the standard deviation is 14.2 cm, and the root mean square error is 14.3 cm. The RMSE is lower than the 20 cm threshold, indicating that the height measurement accuracy of the spaceborne GNSS-R payload meets the standard.

[0089] The origin of the altitude reference true value is illustrated here: the observation scene data of the spaceborne GNSS-R payload during on-orbit operation includes the spatiotemporal parameters of the observed object; based on the spatiotemporal parameters of the observed object, the reference simulation value and correction amount are determined from the simulation model and the correction model respectively; the reference simulation value is corrected based on the correction amount to obtain the altitude reference true value.

[0090] Spatiotemporal parameters are a set of parameters that characterize the spatial location and temporal state of the observed object at a specific moment, including but not limited to geographic coordinates (e.g., longitude, latitude, altitude), motion state (e.g., velocity, acceleration, attitude angle), and timestamps (e.g., UTC time or GPS week seconds).

[0091] The simulation model is a high-fidelity numerical model based on multiphysics coupling modeling, used to output the theoretical observables (i.e., baseline simulation values) of the observed object under given spatiotemporal parameter inputs; its modeling basis includes atmospheric refraction law, ionospheric refraction model, sea surface wind and wave spectrum model, Earth tide model and radar scattering geometry model.

[0092] The correction model is a pre-built systematic error compensation model used to characterize the modeling deviation of the simulation model from the real physical process under different spatiotemporal conditions. Its data sources include historical field measurement comparison results, laboratory calibration data, orbiter on-orbit verification data, and error analytical expressions derived from known physical mechanisms.

[0093] The baseline simulation value is the initial theoretical value directly output by the simulation model after inputting the spatiotemporal parameters of the observed object, such as the simulated value of sea surface height, the simulated value of signal propagation delay, or the simulated value of reflected power. The correction is the deviation compensation term output by the correction model under the same set of spatiotemporal parameters, used to correct the baseline simulation value, such as the correction of sea surface height, the correction of delay deviation, or the correction of power attenuation.

[0094] For example, taking global sea level measurement as an application scenario, for a specific spatiotemporal point (latitude 35.2°N, longitude 121.8°E, time June 1, 2024, 08:00 UTC), the DTU21 mean sea level height model is first called, combined with the GOT tidal model and the Munk solid tide model, to calculate the baseline simulation value (e.g., 23.47 cm) after superimposing static and quasi-static components; then, the CLS-MOG2D-G dynamic atmospheric correction model and the JPL-GIM ionospheric model are called to extract high-frequency disturbance terms at the same spatiotemporal point to obtain the correction amount (e.g., ). (1.23 cm); the baseline simulation value and the correction amount are directly added to obtain the true altitude baseline value of 22.24 cm; this value is written into the baseline database of the accuracy evaluation module and compared with the altitude measurement value obtained by the spaceborne GNSS-R payload in subsequent steps to quantify the altitude measurement accuracy.

[0095] This embodiment achieves multi-source fusion generation of the true altitude reference value by synchronously inputting the spatiotemporal parameters of the observed object into the simulation model and the correction model, respectively obtaining the baseline simulation value and the correction amount, and then numerically correcting the baseline simulation value based on the correction amount. This mechanism not only ensures the physical interpretability and long-term consistency of the true value, but also enhances its response capability to local dynamic disturbances. On this basis, the generated true altitude reference value can serve as a unified reference standard for the accuracy evaluation module, supporting the objective, quantitative, and reproducible evaluation of altitude measurement accuracy, the first altitude measurement error component, and the second altitude measurement error component, thereby providing a solid and reliable technical basis for the on-orbit performance verification of the spaceborne GNSS-R payload.

[0096] S160 determines the first altimetry error component based on the true value of the environmental time delay reference and the environmental time delay correction parameters, and determines the second altimetry error component based on the true value of the geophysical reference and the geophysical correction parameters.

[0097] Among them, the environmental time delay reference true value and the geophysical reference true value are both parameters determined based on the observation scenario data.

[0098] The environmental time delay reference true value is, for example, the atmospheric / ionospheric time delay true value output by the ECMWF / JPL-GIM model, and the geophysical reference true value is, for example, the geophysical correction true value jointly output by GOT / IERS / Munk-Cartwright / CLS-MOG2D-G. Both are high-confidence reference quantities provided by the spaceborne propagation environment simulation subsystem. The first altimeter error component is, for example, the altitude error caused by the environmental correction residual, reflecting the deviation between the environmental parameter modeling and the actual measurement. The second altimeter error component is, for example, the altitude error caused by the insufficient accuracy of the geophysical model, reflecting the completeness of the physical mechanism modeling.

[0099] The first altimetry error component is determined based on the true environmental time delay reference value and the environmental time delay correction parameter, and the second altimetry error component is determined based on the true geophysical reference value and the geophysical correction parameter. This includes: subtracting the environmental time delay correction parameter from the true environmental time delay reference value and substituting it into the geometric model to convert it into an equivalent height error, which is the first altimetry error component; and subtracting the geophysical correction parameter from the true geophysical reference value and directly using it as the second altimetry error component. The two components together constitute the structured analytical result of the total altimetry error.

[0100] For example, the difference between the above output tropospheric wet delay correction value (e.g., 2.34 ns) and the ECMWF model true value (e.g., 2.41 ns) is taken as... 0.07 ns), converted to height error ( 0.01 cm); take the difference between the TEC correction value (e.g., 12.5 TECU) and the JPL-GIM true value (e.g., 12.8 TECU). 0.3 TECU), converted to height error ( 0.4 cm); the two are combined to form the first height measurement error component ( 0.41 cm); take the difference between the above-output ocean tide correction value (e.g., 0.215 m) and the true GOT value (e.g., 0.218 m). 0.003 m), as the second altimeter error component ( (0.3 cm); This separation result indicates that the current error mainly originates from the physical correction process.

[0101] S170 analyzes the impact on altimetry accuracy, the first altimetry error component, and the second altimetry error component after adjusting at least one of the following: observation scene data, GNSS direct signal, GNSS reflected signal, GNSS-R payload status, and analytical algorithm.

[0102] This application can adjust one or more parameters among the observation scene data, GNSS direct signal, GNSS reflected signal, GNSS-R load status, and analytical algorithm, and then re-execute the above S110 to S160 to obtain the updated altimetry accuracy, the updated first altimetry error component, and the updated second altimetry error component. These are then compared and analyzed with the original altimetry accuracy, the first altimetry error component, and the second altimetry error component, thereby determining the impact of the relevant parameter adjustments on the altimetry accuracy, the first altimetry error component, and the second altimetry error component.

[0103] Adjustments include modifying the atmospheric temperature and humidity profile, increasing sea surface wind speed disturbance, changing the signal-to-noise ratio of reflected signals, adjusting GNSS-R receiver signal processing parameters, and replacing relevant power waveform re-tracking algorithms to simulate different on-orbit operating conditions or system configuration changes. Analyses include comparing the trends in altitude measurement accuracy before and after adjustments, changes in the proportion of error component contributions, and the sensitivity ranking of key parameters to identify system weaknesses and optimization directions.

[0104] Figure 1 The illustrated embodiment realizes semi-physical closed-loop simulation verification of spaceborne GNSS-R altimetry. Through a complete process of "generating direct and reflected signals → GNSS-R payload in-loop testing → data processing → error correction and calculation → accuracy evaluation → error component determination → impact assessment," a test closed loop is constructed that is isomorphic to the spaceborne GNSS-R payload during on-orbit operation. Specifically, direct and reflected signals are generated based on the observation scenario data of the spaceborne GNSS-R payload during on-orbit operation, making the direct and reflected signals more closely resemble the on-orbit operating scenario and improving their realism. The direct and reflected signals are sent to the actual spaceborne GNSS-R payload so that the observation data output by the spaceborne GNSS-R payload can reflect the physical effects generated by the actual hardware during on-orbit operation. This embodiment corrects for time delay errors by introducing a preset hardware time delay correction value, eliminating the influence of the inherent systematic errors of the actual hardware on the observation data. Based on the corrected time delay difference and the geophysical correction parameters obtained through analysis, the altitude measurement value of the observed object is calculated, thereby improving the accuracy of the altitude measurement value of the observed object. This embodiment also introduces a true altitude reference value, which is combined with the measured altitude value for analysis to accurately determine the altimetry accuracy of the spaceborne GNSS-R payload. This application can also determine the first altimetry error component corresponding to the environmental delay correction parameters, and the second altimetry error component corresponding to the geophysical correction parameters. After adjusting at least one of the following: observation scene data, GNSS direct signal, GNSS reflected signal, GNSS-R payload state, and analytical algorithm, the impact on altimetry accuracy, the first altimetry error component, and the second altimetry error component is analyzed. This allows for high-fidelity, repeatable, and low-cost verification testing, providing reliable technical support for scheme optimization, hardware debugging, and performance evaluation.

[0105] In another exemplary embodiment of this application, the origin of the preset hardware latency correction value is described in detail; please refer to [link to relevant documentation]. Figure 2 , Figure 2 This is a flowchart illustrating an exemplary embodiment of this application, showing a method for determining a preset hardware latency correction value. The determination method includes at least steps S210 to S220, which are described in detail below:

[0106] S210 sends a combined test signal with a preset time delay truth value to the onboard GNSS-R payload and acquires the test observation data output by the onboard GNSS-R payload to determine the test signal time delay.

[0107] The preset delay true value is a signal propagation delay reference value that is artificially set during the test signal generation stage and has a known accurate value. Its physical meaning is the theoretical transmission time of the test signal from the transmitter through the hardware link (including GNSS signal simulator, radio frequency cable, satellite GNSS-R payload front end, etc.) to the input end of the satellite GNSS-R payload signal processing unit. This value does not contain any unknown system errors and can be understood as a standard value without any inherent hardware errors.

[0108] The combined test signal is used for hardware error calibration. Its form can be a single-frequency continuous wave, a pseudo-random code modulated signal, or a narrow pulse signal, and its time-domain characteristics must meet the requirement of accurately measuring the start and arrival times. Each combined test signal includes at least one GNSS direct test signal and one GNSS reflection test signal.

[0109] Test observation data is the raw observation data output by the spaceborne GNSS-R payload after responding to the combined test signal. Its data structure includes at least timestamp information and signal arrival event markers. The time when the signal is received is recorded by the high-precision clock inside the spaceborne GNSS-R payload.

[0110] The test signal delay is the time difference between the GNSS direct test signal and the GNSS reflection test signal within the combined test signal obtained by actual measurement of the spaceborne GNSS-R payload.

[0111] S220 determines the preset hardware delay correction value based on the preset delay truth value and the test signal delay.

[0112] For example, the preset delay truth value is subtracted from the test signal delay, and the preset hardware delay correction value is determined based on the difference; the difference can be directly used as the preset hardware delay correction value, or corresponding mathematical calculations can be performed based on the difference, and the calculation result can be used as the preset hardware delay correction value.

[0113] Figure 2 The embodiment shown in the figure inputs a combination of test signals with preset delay truth values ​​to the onboard GNSS-R payload, obtains the delay of the test signal output by the payload, and determines the preset hardware delay correction value based on the deviation between the two. This achieves traceable, repeatable, and high-precision calibration of the fixed delay of the hardware link. This parameter is a key component of the preset hardware delay correction value, thereby improving the accuracy of delay difference correction.

[0114] In another exemplary embodiment of this application, the origin of the preset hardware latency correction value is described in detail; please refer to [link to relevant documentation]. Figure 3 , Figure 3 Based on Figure 2 The exemplary embodiment shown illustrates a flowchart of another method for determining a preset hardware latency correction value. This determination method, as in... Figure 2 The S220 shown includes at least S310 to S330; the number of combined test signals is multiple, as detailed below:

[0115] S310 calculates the delay threshold based on the delay of the test signals corresponding to multiple combined test signals.

[0116] The test signal delay corresponding to multiple combined test signals refers to a set of measured delay values ​​obtained by the data processing module after continuously inputting several sets of combined test signals with preset true delay values ​​to the spaceborne GNSS-R payload in hardware delay calibration mode, and then analyzing each set of test observation data. The delay threshold is a statistical criterion boundary value used to distinguish between normal measurement deviations and abnormal disturbances. Its function is to exclude test signal delays that significantly deviate from the true hardware delay due to accidental factors such as transient electromagnetic interference, sampling jitter, or the nonlinear response of the spaceborne GNSS-R payload front end.

[0117] For example, the delays of the test signals corresponding to multiple combined test signals are averaged to obtain an average delay value; a delay threshold is then calculated based on the average delay value. The averaging operation can be an arithmetic average, where the delays of all N test signals are summed and then divided by N to obtain a single scalar value, i.e., the average delay value. Here, the average delay value can be directly used as the delay threshold; alternatively, a fixed bias can be added to the average delay value to obtain the delay threshold; or the average delay value can be multiplied by a preset scaling factor to obtain the delay threshold.

[0118] For example, in hardware delay calibration mode, six sets of combined test signals with preset true delay values ​​of 0.5 ns, 1.0 ns, 1.5 ns, 2.0 ns, 2.5 ns, and 3.0 ns are continuously input to the spaceborne GNSS-R payload. The data processing module performs relevant power waveform analysis on each set of test observation data to obtain six measured delay values ​​for the test signals, which are 0.52 ns, 1.03 ns, 1.49 ns, 2.01 ns, 2.54 ns, and 2.98 ns, respectively. The arithmetic mean of these six measured values ​​is then calculated to obtain an average delay of 1.93 ns.

[0119] The S320 filters the test signal delays corresponding to multiple combined test signals based on a delay threshold, and obtains the filtered test signal delays.

[0120] The filtering method is a filtering operation performed on the delay of all test signals based on the delay threshold. Only test signals whose delay is less than or equal to the delay threshold are retained. This operation does not change the original data of the test signals, but only reduces the number of test signals and improves their quality. The delay of the filtered test signals is the set of signals retained after removing abnormal outliers. Its distribution is closer to the true statistical characteristics of the inherent system error of the spaceborne GNSS-R payload, rather than a mixed distribution superimposed with transient disturbances.

[0121] For example, the test signal delays corresponding to multiple combined test signals are traversed; if the traversed test signal delay is greater than a delay threshold, the traversed test signal delay is filtered out to obtain the filtered test signal delay. Here, traversal can refer to the operation process of sequentially accessing and reading the test signal delay value corresponding to each combined test signal in a preset order, used to establish a systematic checking mechanism for the delay of all test signals, ensuring that subsequent judgment logic covers all collected samples.

[0122] The S330 determines the preset hardware delay correction value based on the preset delay truth value and the delay of the filtered test signal.

[0123] The preset true delay value is the theoretical signal propagation delay value precisely configured by the GNSS signal simulator when generating the test signal. It represents the hardware link delay that the test signal needs to experience from the injection point to the output of the onboard GNSS-R payload under ideal, undisturbed conditions. The hardware delay correction value here is specifically represented as the total hardware link delay deviation, which is equal to the difference between the preset true delay value and the statistical average of the delay of the filtered test signal. This parameter is used to systematically offset the signal delay term in the actual observation data and is a component of the preset hardware delay correction value.

[0124] For example, in a hardware delay calibration task, a total of 12 sets of combined test signals were injected, corresponding to 12 test signal delay values ​​calculated as follows: 2.8 ns, 3.1 ns, 2.9 ns, 3.3 ns, 3.0 ns, 2.7 ns, 3.2 ns, 3.4 ns, 2.6 ns, 3.5 ns, 8.9 ns, and 3.1 ns. The average delay value determined in Example 14 is 3.3 ns, and the preset deviation coefficient is 1.5, from which the delay threshold is calculated to be 4.95 ns. Traversing these 12 delay values, it is found that the 11th value, 8.9 ns, is greater than 4.95 ns, so it is filtered out. The remaining 11 delay values ​​are entered into the subsequent correction value calculation, and the final hardware delay correction value is determined to be 3.05 ns, which significantly reduces the impact of abnormal disturbances compared to the 3.42 ns before filtering.

[0125] In another exemplary embodiment of this application, a system for performing the above-described methods is described by way of example; please refer to [link / reference]. Figure 4 , Figure 4 This is a schematic diagram illustrating the structure of a spaceborne GNSS-R altimeter semi-physical closed-loop simulation verification system according to an exemplary embodiment of this application. System 400 includes:

[0126] The GNSS signal simulator 410 is used to generate GNSS direct and GNSS reflected signals based on observation scene data from the on-orbit operation of the spaceborne GNSS-R payload.

[0127] The spaceborne GNSS-R payload 420 is used to receive direct GNSS signals and reflected GNSS signals to output observation data.

[0128] The data processing module 430 is used to analyze the observation data based on the analytical algorithm to obtain the time delay difference between the GNSS reflected signal and the GNSS direct signal, the environmental time delay correction parameters, and the geophysical correction parameters.

[0129] The error correction and calculation module 440 is used to correct the time delay difference using environmental time delay correction parameters and preset hardware time delay correction values, obtain the corrected time delay difference, and calculate the height measurement value of the observed object based on the corrected time delay difference and geophysical correction parameters.

[0130] The accuracy assessment module 450 is used to determine the altitude measurement accuracy of the spaceborne GNSS-R payload based on the measured altitude value and the true altitude reference value.

[0131] The error component determination module 460 is used to determine the first altimetry error component based on the environmental time delay reference true value and the environmental time delay correction parameter, and to determine the second altimetry error component based on the geophysical reference true value and the geophysical correction parameter; the altitude reference true value, the environmental time delay reference true value and the geophysical reference true value are all parameters determined based on the observation scene data.

[0132] The impact assessment module 470 is used to analyze the impact on altimetry accuracy, the first altimetry error component, and the second altimetry error component after adjusting at least one of the following: observation scene data, GNSS direct signal, GNSS reflected signal, GNSS-R payload status, and analytical algorithm.

[0133] This system achieves end-to-end verification of the spaceborne GNSS-R payload. Through a complete process of "direct and reflected signal generation → GNSS-R payload in-loop testing → data processing → error correction and calculation → accuracy assessment → error component determination → impact assessment," it constructs a test closed loop isomorphic to the spaceborne GNSS-R payload during in-orbit operation. Specifically, it generates direct and reflected signals based on observation scenario data from the spaceborne GNSS-R payload's in-orbit operation, making these signals more closely resemble the in-orbit operating scenario and improving their realism. The direct and reflected signals are then sent to the actual spaceborne GNSS-R payload, ensuring that the observation data output by the payload reflects the physical effects generated by the actual hardware during in-orbit operation. This system corrects for time delay errors by introducing a preset hardware time delay correction value, eliminating the influence of inherent system errors of the actual hardware on the observation data. Based on the corrected time delay difference and the geophysical correction parameters obtained through analysis, it calculates the altitude measurement value of the observed object, thereby improving the accuracy of the altitude measurement value. This application also introduces a true altitude reference value, which is combined with the measured altitude value for analysis to accurately determine the altimetry accuracy of the spaceborne GNSS-R payload. This system can also determine the first altimetry error component corresponding to the environmental delay correction parameters, and the second altimetry error component corresponding to the geophysical correction parameters. After adjusting at least one of the following: observation scene data, GNSS direct signal, GNSS reflected signal, GNSS-R payload state, and analytical algorithm, the impact on altimetry accuracy, the first altimetry error component, and the second altimetry error component is analyzed. This allows for high-fidelity, repeatable, and low-cost verification testing, providing reliable technical support for scheme optimization, hardware debugging, and performance evaluation.

[0134] In another exemplary embodiment, the GNSS signal simulator is further configured to send a combined test signal with a preset time delay truth value to the spaceborne GNSS-R payload; the system also includes a hardware time delay calibration module, configured to acquire test observation data output by the spaceborne GNSS-R payload to determine the test signal time delay; and to determine a preset hardware time delay correction value based on the preset time delay truth value and the test signal time delay.

[0135] In another exemplary embodiment, the number of combined test signals is multiple; the hardware delay calibration module is further configured to calculate a delay threshold based on the test signal delay corresponding to the multiple combined test signals; filter the test signal delay corresponding to the multiple combined test signals based on the delay threshold to obtain the filtered test signal delay; and determine a preset hardware delay correction value based on the preset delay truth value and the filtered test signal delay.

[0136] In another exemplary embodiment, the hardware delay calibration module is further configured to perform an averaging operation on the delays of the test signals corresponding to multiple combined test signals to obtain an average delay value; and to calculate a delay threshold based on the average delay value.

[0137] In another exemplary embodiment, the hardware delay calibration module is further configured to traverse the test signal delays corresponding to multiple combined test signals; if the traversed test signal delays are greater than the delay threshold, the traversed test signal delays are filtered out to obtain the filtered test signal delays.

[0138] In another exemplary embodiment, the data processing module is further configured to preprocess the observation data to obtain preprocessed observation data; wherein the preprocessing includes at least one of data timestamp alignment, attitude data correction, and spatial information calculation; to perform signal enhancement processing on the preprocessed observation data to obtain enhanced observation data; and to analyze the enhanced observation data based on an analytical algorithm to obtain the time delay difference between the GNSS reflected signal and the GNSS direct signal, environmental time delay correction parameters, and geophysical correction parameters.

[0139] In another exemplary embodiment, the enhanced observation data includes the reflected signal power waveform, observation time, location, and environmental parameters; the data processing module is further configured to analyze the reflected signal power waveform based on an analytical algorithm to obtain the time delay difference between the GNSS reflected signal and the GNSS direct signal; and to calculate environmental time delay correction parameters and geophysical correction parameters based on the observation time, location, and environmental parameters.

[0140] In another exemplary embodiment, the accuracy assessment module is further configured to calculate the difference between the measured altitude value and the true altitude reference value; and determine the altitude measurement accuracy of the spaceborne GNSS-R payload based on the difference.

[0141] In another exemplary embodiment, the observation scene data includes a first environmental parameter of the observed object and a second environmental parameter of the signal propagation path; the GNSS signal simulator is further configured to determine the signal receiving power of the spaceborne GNSS-R payload based on the first environmental parameter and the signal propagation data; determine the signal receiving delay of the spaceborne GNSS-R payload based on the second environmental parameter and the signal propagation data; and generate a GNSS direct signal and a GNSS reflected signal based on the signal receiving delay and the signal receiving power.

[0142] In another exemplary embodiment, please refer to [link / reference]. Figure 5 , Figure 5 Based on Figure 4 The illustrated embodiment shows a schematic diagram of another spaceborne GNSS-R altimeter semi-physical closed-loop simulation verification system. The observation scene data includes the spatiotemporal parameters of the observed object; the system 400 also includes:

[0143] The altitude reference truth value module 510 is used to determine the reference simulation value and correction amount from the simulation model and the correction model respectively based on the spatiotemporal parameters; and to correct the reference simulation value based on the correction amount to obtain the altitude reference truth value.

[0144] This application system adopts a "hardware-in-the-loop" architecture, constructing a semi-physical testing environment of "signal simulator + spaceborne GNSS-R payload". It integrates hardware physical simulation and software effect compensation as dual technical paths: the GNSS signal simulator accurately reproduces the direct / reflected dual-path radio frequency signals (including multiple ranging codes and two-way atmospheric / ionospheric delay characteristics) of the space signal source in the spaceborne operation scenario. Combined with the inherent hardware effects of the real spaceborne GNSS-R payload, such as nonlinearity, thermal noise, and electromagnetic interference, it generates raw observation data that is close to the spaceborne on-orbit operating conditions. This fundamentally solves the technical defect that pure software simulation cannot reproduce the hardware physical response, resulting in significant deviations between simulation results and real scenarios, and ensures the high fidelity of the verification data.

[0145] Please see Figure 6 , Figure 6 This is the calibration result of the hardware delay difference at frequency B1 of the spaceborne GNSS-R altimeter semi-physical closed-loop simulation verification system of this application. The horizontal axis represents the sampling point, and the vertical axis represents the hardware delay. Figure 6 The hardware latency of the characterization system 400, when converted to a length unit, is approximately 10 meters.

[0146] Please see Figure 7 and Figure 8 , Figure 7 This is a comparison chart of the sea surface height output by the spaceborne GNSS-R altimeter semi-physical closed-loop simulation verification system of this application and the true value of the simulation input. Figure 7 This demonstrates that the system in this application has the capability to successfully achieve high-precision observation of the height of the sea surface (the object of observation). Figure 8 This is a comparison chart of the true values ​​of the ionospheric TEC calculated using the dual-frequency direct and reflected signals of GNSS dual-frequency altimetry in this application and the simulation input. Figure 8 The system described in this application has the ability to evaluate the accuracy of dual-frequency ionospheric TEC measurements and its impact on interferometric altimetry. It can be used to test the performance of GNSS-R altimeter receivers (spaceborne GNSS-R payloads) and ionospheric error correction algorithms.

[0147] This application presents a space-to-ground integrated end-to-end closed-loop verification technology: proposing a closed-loop design encompassing "direct and reflected signal generation → GNSS-R payload in-loop testing → data processing → error correction and calculation → accuracy assessment → error component determination → impact assessment." This achieves end-to-end integrated simulation verification of the spaceborne GNSS-R payload from on-orbit operation to ground data processing, and from signal propagation environment to the reflection characteristics of the observed object. It overcomes the limitations of traditional segmented verification (pure software simulation, field tests), enabling independent or joint verification of any component of the system (such as the hardware performance, algorithm robustness, and environmental adaptability of the spaceborne GNSS-R payload). This solves the industry problem of lacking systematic, full-chain, high-fidelity verification methods. For example, high-fidelity, repeatable, and low-cost verification tests can be conducted on any module in the verification system chain (such as the GNSS signal simulator, the spaceborne GNSS-R payload, and the data processing module), providing reliable technical support for system optimization, hardware debugging, and performance evaluation.

[0148] The above description is merely a preferred exemplary embodiment of this application and is not intended to limit the implementation of this application. Those skilled in the art can easily make corresponding modifications or alterations based on the main concept and spirit of this application. Therefore, the scope of protection of this application should be determined by the scope of protection claimed in the claims.

Claims

1. A spaceborne GNSS-R altimeter semi-physical closed-loop simulation verification system, characterized in that, include: The GNSS signal simulator is used to generate direct GNSS signals and reflected GNSS signals based on observation scene data from the onboard GNSS-R payload during its operation in orbit. The spaceborne GNSS-R payload is used to receive the direct GNSS signal and the reflected GNSS signal to output observation data; The data processing module is used to analyze the observation data based on the analytical algorithm to obtain the time delay difference between the GNSS reflected signal and the GNSS direct signal, the environmental time delay correction parameter, and the geophysical correction parameter. The error correction and calculation module is used to correct the time delay difference using the environmental time delay correction parameters and the preset hardware time delay correction value, to obtain the corrected time delay difference, and to calculate the height measurement value of the observed object based on the corrected time delay difference and the geophysical correction parameters. The accuracy assessment module is used to determine the altitude measurement accuracy of the spaceborne GNSS-R payload based on the measured altitude value and the true altitude reference value. The error component determination module is used to determine a first altimetry error component based on the environmental time delay reference true value and the environmental time delay correction parameters, and to determine a second altimetry error component based on the geophysical reference true value and the geophysical correction parameters; the altitude reference true value, the environmental time delay reference true value, and the geophysical reference true value are all parameters determined based on the observation scene data; The impact assessment module is used to analyze the impact on the altimetry accuracy, the first altimetry error component, and the second altimetry error component after adjusting at least one of the observation scene data, the GNSS direct signal, the GNSS reflected signal, the spaceborne GNSS-R payload status, and the analytical algorithm.

2. The system according to claim 1, characterized in that, The GNSS signal simulator is also used to send a combined test signal with a preset time delay truth value to the onboard GNSS-R payload; The system also includes a hardware delay calibration module, used to acquire test observation data output by the spaceborne GNSS-R payload to determine the test signal delay; and to determine the preset hardware delay correction value based on the preset delay truth value and the test signal delay.

3. The system according to claim 2, characterized in that, The number of combined test signals is multiple; The hardware delay calibration module is further configured to calculate a delay threshold based on the test signal delay corresponding to multiple combined test signals; and to filter the test signal delay corresponding to the multiple combined test signals based on the delay threshold to obtain the filtered test signal delay. The preset hardware delay correction value is determined based on the preset delay truth value and the delay of the filtered test signal.

4. The system according to claim 3, characterized in that, The hardware delay calibration module is also used to perform an average calculation on the delay of the test signals corresponding to multiple combined test signals to obtain an average delay value; and to calculate a delay threshold based on the average delay value.

5. The system according to claim 3, characterized in that, The hardware delay calibration module is also used to traverse the test signal delays corresponding to the multiple combined test signals; if the traversed test signal delay is greater than the delay threshold, the traversed test signal delay is filtered out to obtain the filtered test signal delay.

6. The system according to claim 1, characterized in that, The data processing module is further configured to preprocess the observation data to obtain preprocessed observation data; wherein, the preprocessing includes at least one of data timestamp alignment, attitude data correction, and spatial information calculation; to perform signal enhancement processing on the preprocessed observation data to obtain enhanced observation data; and to analyze the enhanced observation data based on an analytical algorithm to obtain the time delay difference between the GNSS reflected signal and the GNSS direct signal, environmental time delay correction parameters, and geophysical correction parameters.

7. The system according to claim 6, characterized in that, The enhanced observation data includes the reflected signal power waveform, observation time, location, and environmental parameters; The data processing module is also used to analyze the power waveform of the reflected signal based on the analytical algorithm to obtain the time delay difference between the GNSS reflected signal and the GNSS direct signal; and to calculate the environmental time delay correction parameters and geophysical correction parameters based on the observation time, location and environmental parameters.

8. The system according to any one of claims 1 to 7, characterized in that, The accuracy assessment module is also used to calculate the difference between the measured altitude value and the true altitude reference value; and to determine the altitude measurement accuracy of the spaceborne GNSS-R payload based on the difference.

9. The system according to any one of claims 1 to 7, characterized in that, The observation scene data includes the first environmental parameters of the observed object and the second environmental parameters of the signal propagation path; The GNSS signal simulator is further configured to determine the signal receiving power of the spaceborne GNSS-R payload based on the first environmental parameters and signal propagation data; determine the signal receiving delay of the spaceborne GNSS-R payload based on the second environmental parameters and the signal propagation data; and generate GNSS direct signals and GNSS reflected signals based on the signal receiving delay and the signal receiving power.

10. The system according to any one of claims 1 to 7, characterized in that, The observation scene data includes the spatiotemporal parameters of the observed object; the system also includes: The altitude reference truth value module is used to determine the reference simulation value and the correction amount from the simulation model and the correction model respectively based on the spatiotemporal parameters; and to correct the reference simulation value based on the correction amount to obtain the altitude reference truth value.

11. A semi-physical closed-loop simulation verification method for spaceborne GNSS-R altimeter measurement, characterized in that, include: Based on the observation scene data of the on-orbit GNSS-R payload, generate GNSS direct signal and GNSS reflected signal; The GNSS direct signal and the GNSS reflected signal are sent to the spaceborne GNSS-R payload, and the observation data output by the spaceborne GNSS-R payload is acquired; The observation data is analyzed using an analytical algorithm to obtain the time delay difference between the GNSS reflected signal and the GNSS direct signal, environmental time delay correction parameters, and geophysical correction parameters. The time delay difference is corrected using the environmental time delay correction parameters and the preset hardware time delay correction value to obtain the corrected time delay difference, and the height measurement value of the observed object is calculated based on the corrected time delay difference and the geophysical correction parameters. The altitude measurement accuracy of the spaceborne GNSS-R payload is determined based on the measured altitude value and the true altitude reference value. The first altimetry error component is determined based on the true value of the environmental time delay reference and the environmental time delay correction parameters, and the second altimetry error component is determined based on the true value of the geophysical reference and the geophysical correction parameters; the true value of the altitude reference, the true value of the environmental time delay reference, and the true value of the geophysical reference are all parameters determined based on the observation scene data; After adjusting at least one of the observation scene data, the GNSS direct signal, the GNSS reflected signal, the GNSS-R payload status, and the analytical algorithm, the impact on the altimeter accuracy, the first altimeter error component, and the second altimeter error component is analyzed.

12. The method according to claim 11, characterized in that, The method further includes: The combined test signal with the preset time delay truth value is sent to the spaceborne GNSS-R payload, and the test observation data output by the spaceborne GNSS-R payload is obtained to determine the test signal time delay; The preset hardware delay correction value is determined based on the preset delay truth value and the test signal delay.

13. The method according to claim 12, characterized in that, The number of combined test signals is multiple; The preset hardware delay correction value is determined based on the preset delay truth value and the test signal delay, including: The delay threshold is calculated based on the delay of the test signals corresponding to multiple combined test signals. Based on the time delay threshold, the test signal delays corresponding to the multiple combined test signals are filtered to obtain the filtered test signal delays; The preset hardware delay correction value is determined based on the preset delay truth value and the delay of the filtered test signal.

14. The method according to claim 13, characterized in that, The delay threshold is calculated based on the delay of the test signals corresponding to multiple combined test signals, including: The average delay of the test signals corresponding to multiple combined test signals is calculated to obtain the average delay value. The delay threshold is calculated based on the average delay value.

15. The method according to claim 13, characterized in that, Based on the delay threshold, the delay of the test signals corresponding to the multiple combined test signals is filtered to obtain the filtered test signal delays, including: Iterate through the test signal delays corresponding to the multiple combined test signals; If the delay of the traversed test signal is greater than the delay threshold, the delay of the traversed test signal will be filtered out to obtain the filtered test signal delay.

16. The method according to claim 11, characterized in that, The observation data is analyzed using an analytical algorithm to obtain the time delay difference between the GNSS reflected signal and the GNSS direct signal, environmental time delay correction parameters, and geophysical correction parameters, including: The observation data is preprocessed to obtain preprocessed observation data; wherein, the preprocessing includes at least one of data timestamp alignment, attitude data correction, and spatial information calculation; The preprocessed observation data is then subjected to signal enhancement processing to obtain enhanced observation data. The enhanced observation data is analyzed using an analytical algorithm to obtain the time delay difference between the GNSS reflected signal and the GNSS direct signal, environmental time delay correction parameters, and geophysical correction parameters.

17. The method according to claim 16, characterized in that, The enhanced observation data includes the reflected signal power waveform, observation time, location, and environmental parameters; The enhanced observation data is analyzed using an analytical algorithm to obtain the time delay difference between the GNSS reflected signal and the GNSS direct signal, environmental time delay correction parameters, and geophysical correction parameters, including: The power waveform of the reflected signal is analyzed based on the waveform analysis algorithm to obtain the time delay difference between the GNSS reflected signal and the GNSS direct signal; Environmental time delay correction parameters and geophysical correction parameters are calculated based on the observation time, location, and environmental parameters.

18. The method according to any one of claims 11 to 17, characterized in that, The altitude measurement accuracy of the spaceborne GNSS-R payload is determined based on the measured altitude value and the true altitude reference value, including: Calculate the difference between the measured height value and the true height reference value; The altitude measurement accuracy of the spaceborne GNSS-R payload is determined based on the difference.

19. The method according to any one of claims 11 to 17, characterized in that, The observation scene data includes the first environmental parameters of the observed object and the second environmental parameters of the signal propagation path; Based on observation data from the on-orbit operation of the spaceborne GNSS-R payload, direct GNSS signals and reflected GNSS signals are generated, including: Based on the first environmental parameters and signal propagation data, the signal receiving power of the spaceborne GNSS-R payload is determined; Based on the second environmental parameters and the signal propagation data, the signal reception delay of the spaceborne GNSS-R payload is determined; GNSS direct signal and GNSS reflected signal are generated based on the signal reception delay and the signal reception power.

20. The method according to any one of claims 11 to 17, characterized in that, The observation scene data includes the spatiotemporal parameters of the observed object; the method further includes: Based on the spatiotemporal parameters, the baseline simulation value and correction amount are determined from the simulation model and the correction model, respectively. The baseline simulation value is corrected based on the correction amount to obtain the true value of the height baseline.

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