GNSS-R height measurement method and product fusing direct reflection signal separation and strategy switching mechanism

Abstract

The application discloses a GNSS-R height measurement method and product fusing direct reflection signal separation and strategy switching mechanism, and the method comprises the following steps: step 1: obtaining the unmanned aerial vehicle flight height estimation H from GNSS satellite ephemeris data and the receiver position; step 2: judging whether H is less than the low-altitude height threshold value, and if yes, turning to step 3; otherwise, extracting the delay difference of direct reflection signal peak value to reverse the flight height, and ending; step 3: fitting to obtain the direct path initial parameter including the direct path delay; step 4: reconstructing the main path waveform and stripping to obtain the residual waveform; step 5: searching for the local peak value in the residual waveform to obtain the residual signal energy ratio index SRRM, judging whether the SRRM value is lower than the threshold value, and if yes, recording the reflection signal delay and turning to step 6, otherwise, turning to step 5 to find the secondary peak; step 6: obtaining the flight height from the delay difference of the direct reflection signal; and step 7: verifying the consistency of the flight height and H, and if the verification is satisfied, ending, otherwise, turning to step 5 to find the secondary peak.

Description

Technical Field

[0001] This invention belongs to the field of GNSS reflection signal remote sensing technology, and particularly relates to a GNSS-R altimeter measurement method and product that integrates direct and reflective signal separation and strategy switching mechanisms. Background Technology

[0002] GNSS reflectionometry (GNSS-R) is a passive remote sensing technology that utilizes L-band signals emitted by navigation satellites (such as GPS, Galileo, and BDS). These signals are reflected from the ground or water surfaces. By receiving and processing the waveform characteristics of the reflected signals, surface parameters such as sea level, snow thickness, and soil moisture can be retrieved. Its advantages include low cost, low power consumption, strong anti-interference capabilities, and suitability for deployment on small platforms. In recent years, it has been widely used in various fields such as aviation, oceanography, and meteorology.

[0003] The basic principle of GNSS-R altimetry is to obtain the path delay of the reflected signal relative to the direct signal, and then invert the altimeter using the code phase delay (Delay Map, DM) of the direct and reflected signals, i.e., the peak values ​​of the waveforms of the direct and reflected signals. However, in low-altitude platform scenarios, because the platform is close to the ground, the path difference between the direct and reflected signals is very small, resulting in severe overlap between the two in the relevant waveforms. The reflected path information is submerged by the main path signal, making it difficult to distinguish the position of the secondary peaks in the waveform, thus affecting the accuracy of the altitude inversion. Furthermore, the signal-to-noise ratio of low-altitude reflected signals is usually low. Because the energy of the reflected path attenuates during reflection at the ground surface, the reflected signal is lower than the direct signal and is often masked by the main peak, making it impossible to extract accurately.

[0004] More importantly, current mainstream GNSS-R altimeter systems generally employ a fixed signal processing procedure, using a uniform waveform detection and peak extraction strategy regardless of flight altitude, lacking an adaptive adjustment mechanism for low-altitude aliasing scenarios. This processing method ignores the changes in GNSS signal characteristics at different platform altitudes, making the system's altimeter accuracy unstable under low-altitude conditions and difficult to maintain high reliability in complex terrain or dynamic environments.

[0005] Therefore, existing technologies have the following key technical shortcomings in low-altitude GNSS-R altimeter applications: First, direct and reflected signals are severely aliased, making it impossible to effectively separate the reflection path, resulting in significant altimeter errors; second, the fixed waveform processing flow lacks adaptability to aliasing environments, limiting the system's generalization and robustness; third, there is currently a lack of direct and reflected signal separation algorithms for low-altitude GNSS-R platforms, resulting in low efficiency in utilizing reflection information under mixed direct and reflected waveform conditions, making it difficult to achieve high-precision real-time altimeter measurement. Summary of the Invention

[0006] The purpose of this invention is to overcome the defects of the prior art and to propose a GNSS-R altimeter method that integrates direct and reverse signal separation and strategy switching mechanism. This invention also discloses a product.

[0007] In view of this, the present invention proposes a GNSS-R altimeter method that integrates direct and reverse signal separation and strategy switching mechanisms, comprising:

[0008] Step 1: Based on GNSS satellite ephemeris data and receiver location, establish the satellite-to-ground geometric relationship to obtain the estimated flight altitude H of the UAV;

[0009] Step 2: Determine whether the estimated flight altitude H is less than the set low-altitude threshold. If yes, proceed to Step 3; otherwise, extract the delay difference between the peak value of the direct signal and the peak value of the reflected signal to invert the flight altitude and end.

[0010] Step 3: Based on the correlation function waveform of the mixed signal and the flight altitude estimate H, construct a joint model of the direct path, and fit the direct signal to obtain the initial parameters of the direct path, including the direct path delay;

[0011] Step 4: Reconstruct the main path waveform based on the initial parameters of the direct path and separate it from the original signal to obtain the residual waveform;

[0012] Step 5: Search for local peaks in the residual waveform, calculate the residual signal energy ratio index SRRM, and determine whether the SRRM value is lower than the set threshold. If yes, record the reflected signal delay and proceed to step 6; otherwise, proceed to step 5 to continue searching for secondary peaks.

[0013] Step 6: Calculate the flight altitude based on the difference between the delay of the direct signal and the delay of the separated reflected signal;

[0014] Step 7: Verify the consistency between the flight altitude and the estimated flight altitude obtained in Step 1. If the verification is successful, the process ends; otherwise, proceed to Step 5 to continue searching for the secondary peak.

[0015] Preferably, the joint model of the direct path in step 3 is:

[0016]

[0017] in, The value of the simulation function for the direct waveform over time delay τ. The center delay of the direct simulation waveform, θ0 represents the amplitude of the direct simulation waveform, σ represents the phase of the direct simulation waveform, ω represents the standard deviation of the Gaussian envelope, and ω represents the angular frequency of the carrier wave.

[0018] Preferably, step 3 includes:

[0019] Based on the aircraft altitude, satellite orbit, and receiver position, the approximate arrival delay τ0 of the direct signal is calculated using a free-space propagation model.

[0020] Using τ0 as the center of the search window, the envelope of the mixed signal is analyzed within this window with a chip interval width, and the moment with the largest slope of the envelope curve is selected as the precise arrival time.

[0021] At any moment Read the envelope amplitude of the mixed signal separately The initial parameters of the direct path are obtained by combining the instantaneous phase θ0. And θ0.

[0022] Preferably, step 4 includes:

[0023] The direct signal is obtained by fitting the initial parameters of the direct path. The residual waveform R is obtained by stripping it from the original signal R(τ). residual (τ).

[0024] Preferably, the residual signal energy ratio (SRRM) in step 5 is obtained according to the following formula:

[0025]

[0026] in, Let K represent the amplitude, angular frequency, and phase of the k-th path, which includes both the direct and reflected paths; K represents the total number of paths, and j represents the imaginary part. Represents the residual energy remaining after path fitting, ||R(τ)|| 2 This represents the energy of the original signal.

[0027] Preferably, the flight altitude H obtained in step 6 is... GNSS-R for:

[0028]

[0029] Δτ=τ1-τ0

[0030] Where c is the speed of light in vacuum, τ1 is the delay of the reflected signal, and θ is the elevation angle of the current GNSS satellite.

[0031] Preferably, step 7 involves verifying the consistency of altimetry measurements based on the flight altitude and the estimated flight altitude obtained in step 1, including:

[0032] The flight altitude H obtained from step 6 is based on the following formula. GNSS-R The difference ΔH is calculated by comparing the estimated flight altitude H obtained in step 1: ΔH = |H GNSS-R-H| is compared with the set tolerance threshold ε, and if ΔH is less than ε, the verification is satisfied.

[0033] In a second aspect, the present invention provides a computer device, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the above-described method.

[0034] Thirdly, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the above-described method.

[0035] Fourthly, the present invention provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the above-described method.

[0036] Compared with the prior art, the advantages of the present invention are:

[0037] This invention solves the technical problem of unextractable reflection paths and altimeter measurement failures caused by the aliasing of direct and reflected signals under low-altitude platforms by introducing an automatic path separation strategy based on flight altitude determination. For the first time, a dynamic path processing mechanism based on altitude discrimination is introduced into GNSS-R altimeter measurement, enabling the system to accurately extract reflection path information in scenarios with severe signal aliasing, thereby achieving high-precision altimeter inversion. Specifically, it includes:

[0038] 1. Adaptive switching technology for height measurement strategy based on direct and reverse signal separation triggering mechanism

[0039] An innovative flight altitude estimation method based on real-time satellite-ground geometry was constructed, which dynamically judges the signal aliasing state and automatically activates the direct and reflected signal separation algorithm at low altitudes. This achieves effective identification and separation of direct and reflected signals, breaks through the bottleneck of low-altitude altimeter aliasing identification in traditional GNSS-R systems, and significantly improves the system's altimeter stability and accuracy.

[0040] 2. Direct signal stripping and reflected waveform construction technique based on joint delay-amplitude-phase modeling

[0041] This paper proposes a direct signal fitting method that combines delay, amplitude, and phase for the first time. The direct path signal is stripped and the residual waveform is constructed, providing reliable data support for the accurate extraction of GNSS-R reflection signals and altimetry inversion. This method effectively improves the accuracy of altimetry and the quality of signal separation in complex environments.

[0042] 3. Self-correcting closed-loop feedback mechanism based on consistency verification of height measurement results

[0043] An innovative strategy for consistency verification and adaptive retry of altimetry results is proposed. By cross-verifying the GNSS-R inversion altitude and flight geometry altitude in real time, the system automatically reverts to the secondary peak value and re-executes the path separation and altimetry strategy, thereby constructing a system-level self-correction closed loop. This improves the robustness and reliability of the altimetry process and avoids the altimetry error caused by mismatch in abnormal environments of traditional systems. Attached Figure Description

[0044] Figure 1 This is a flowchart of the GNSS-R altimeter method of the present invention, which integrates direct and reverse signal separation and strategy switching mechanisms. Detailed Implementation

[0045] The method of this invention achieves separation of direct and reflected signals based on a main path signal stripping mechanism, enabling high-precision, robust, and real-time altimetry inversion within a low-altitude range. It is widely applicable to UAV remote sensing applications such as topographic mapping, snow thickness monitoring, water level monitoring, and disaster assessment. Figure 1 As shown, it includes the following steps:

[0046] Step 1: Based on GNSS satellite ephemeris data and receiver location, establish the satellite-to-ground geometric relationship to obtain the estimated flight altitude H of the UAV;

[0047] Step 2: Determine whether the estimated flight altitude H is less than the set low-altitude threshold. If yes, proceed to Step 3; otherwise, extract the delay difference between the peak value of the direct signal and the peak value of the reflected signal to invert the flight altitude and end.

[0048] Step 3: Based on the correlation function waveform of the mixed signal and the flight altitude estimate H, construct a joint model of the direct path, and fit the direct signal to obtain the initial parameters of the direct path, including the direct path delay;

[0049] Step 4: Reconstruct the main path waveform based on the initial parameters of the direct path and separate it from the original signal to obtain the residual waveform;

[0050] Step 5: Search for local peaks in the residual waveform, calculate the residual signal energy ratio index SRRM, and determine whether the SRRM value is lower than the set threshold. If yes, record the reflected signal delay and proceed to step 6; otherwise, proceed to step 5 to continue searching for secondary peaks.

[0051] Step 6: Calculate the flight altitude based on the difference between the delay of the direct signal and the delay of the separated reflected signal;

[0052] Step 7: Verify the consistency between the flight altitude and the estimated flight altitude obtained in Step 1. If the verification is successful, the process ends; otherwise, proceed to Step 5 to continue searching for the secondary peak.

[0053] The technical solution of the present invention will be described in detail below with reference to the accompanying drawings and embodiments.

[0054] Example 1

[0055] Embodiment 1 of this invention provides a GNSS-R altimeter method integrating direct and reflected signal separation and strategy switching mechanisms, suitable for high-precision altimeter applications on low-altitude flight platforms (such as UAVs) in complex terrain environments. This method aims to solve the problem of significant altimeter measurement errors in existing GNSS-R altimeter methods at low altitudes due to severe aliasing between direct and reflected signals, leading to inaccurate identification of reflection paths. Specifically, this invention includes the following technical solution steps:

[0056] Step 1: Determine flight altitude based on satellite-ground geometry

[0057] Using GNSS satellite ephemeris data and receiver location, a geometric model between the satellite and the ground is established to calculate the vertical geometric altitude H of the UAV platform above the ground. This altitude calculation result serves as the basic reference parameter for subsequent direct and reflected signal separation determination.

[0058] Step 2: Path Separation Trigger Decision

[0059] The geometric altitude calculated in step one is compared with the low-altitude altitude threshold set by the system. When the estimated altitude is lower than this threshold, it indicates that the GNSS direct signal and the ground reflected signal may have significant aliasing in the correlation function, making it difficult to directly extract effective reflection path information. In this case, the system automatically triggers the path separation module to perform reflection path identification and stripping operations, extracting the reflected signals that are blocked or superimposed by the main path. If the estimated altitude is higher than the threshold, the altitude is inverted by extracting the peak values ​​of the direct and reflected signals according to the traditional GNSS-R code delay altimetry scheme.

[0060] Step 3: Fitting the direct path model

[0061] During path separation, the initial delay estimate τ0 of the direct signal is first calculated using a free-space propagation model based on the spacecraft altitude, satellite orbit, and receiver position. Then, using this delay as the center of the search window and with a chip-width interval, the envelope of the mixed signal is analyzed within this window. The moment with the largest slope of the envelope curve is selected as the precise arrival time. At this moment, the envelope amplitude of the signal is read respectively. The instantaneous phase θ0 is used as the initial amplitude and phase estimate for the direct path model.

[0062] The initial direct-fire path model is represented as:

[0063]

[0064] Step 4: Residual Signal Stripping

[0065] Based on the initial parameters of the direct path (delay estimate) obtained from the fitting in step three Amplitude estimate The phase estimate θ0 is used to reconstruct the main path waveform from the original correlation function waveform, and then removed from the original signal to obtain the residual waveform R. residual (τ). The residual waveform theoretically preserves the reflected signal components that were originally obscured or superimposed by the main path, providing a signal basis for subsequent reflection path identification. The residual waveform is obtained by subtracting the fitted direct signal from the original waveform:

[0066]

[0067] The residual waveform R after stripping residual Possible reflection path signals are preserved in (τ).

[0068] Step 5: Peak Reflection Path Identification and Validity Determination

[0069] Local peaks are searched in the residual waveform to identify potential reflection path delay locations. To further determine whether the peak represents the true reflection path rather than noise or fitting error, the method introduces the Signal Residual Ratio Method (SRRM) as an auxiliary criterion.

[0070] Its definition is as follows:

[0071]

[0072] in: The values ​​are the amplitude, angular frequency, and phase of the k-th path (including the main path and the reflection path), respectively; the numerator is the residual energy remaining after path fitting; and the denominator is the energy of the original correlation function.

[0073] When the SRRM value is below the set threshold, the current path separation effect is considered good, and the reflection path is valid. If the SRRM remains above the threshold, the current residual is considered to be mainly noise or misfit, and the high-level inversion of the reflection path is abandoned. If the above conditions are met, it is determined to be a valid reflection path, and the propagation delay τ1 of the reflection path is recorded.

[0074] Step Six: GNSS-R Altimeter Calculation

[0075] The time delay difference between the reflected path and the direct path is calculated based on the identified direct path delay τ0 and reflected path delay τ1: Δτ = τ1 - τ0. Combined with the current GNSS satellite elevation angle θ, the GNSS-R altimeter formula is used for calculation.

[0076]

[0077] In the formula, c is the speed of light in vacuum, and H GNSS-R The height of the receiver above the ground.

[0078] Step 7: Verification of Consistency of Altitude Measurement Results

[0079] The GNSS-R altimeter inversion results H GNSS-R Compare the flight altitude H estimated using geometric relationships in step one, and calculate the difference ΔH = |H GNSS-R -H|. If the difference is less than the system-set tolerance threshold ε, the altimeter result is considered reliable, and the current GNSS-R altimeter is output; if it exceeds the threshold, the current reflection path estimation is considered to have an error, the algorithm returns to step five, continues to try to match the secondary peak in the residual waveform, and re-performs SRRM determination and altimeter calculation until a satisfactory inversion result is obtained.

[0080] Example 2

[0081] Embodiment 2 of the present invention provides a computer device comprising: at least one processor, a memory, at least one network interface, and a user interface. The various components of the device are coupled together via a bus system. It is understood that the bus system is used to enable communication between these components. In addition to a data bus, the bus system also includes a power bus, a control bus, and a status signal bus.

[0082] The user interface may include a display, keyboard, or clicking device (e.g., mouse, trackball, touchpad, or touchscreen).

[0083] It is understood that the memory in the embodiments disclosed in this application may be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. The non-volatile memory may be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory may be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), Synchronous DRAM (SDRAM), Double Data Rate Synchronous DRAM (DDRSDRAM), Enhanced Synchronous DRAM (ESDRAM), Synchlink DRAM (SLDRAM), and Direct Rambus RAM (DRRAM). The memories described herein are intended to include, but are not limited to, these and any other suitable types of memory.

[0084] In some implementations, the memory stores elements such as executable modules or data structures, or subsets thereof, or extended sets thereof: operating systems and applications.

[0085] The operating system includes various system programs, such as the framework layer, core library layer, and driver layer, used to implement various basic business functions and handle hardware-based tasks. The application programs include various applications, such as media players and browsers, used to implement various application functions. Programs implementing the methods of the embodiments of this disclosure can be included in the application programs.

[0086] In the above embodiments, the processor can also invoke programs or instructions stored in memory, specifically programs or instructions stored in an application program, for the following purposes:

[0087] The steps of performing the method of Example 1.

[0088] The method of Embodiment 1 can be applied to a processor or implemented by a processor. The processor may be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above method can be completed by integrated logic circuits in the processor's hardware or by instructions in software form. The processor can be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in Embodiment 1. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in Embodiment 1 can be directly implemented by a hardware decoding processor, or by a combination of hardware and software modules in the decoding processor. The software modules can reside in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. This storage medium is located in memory; the processor reads information from the memory and, in conjunction with its hardware, completes the steps of the above method.

[0089] It is understood that the embodiments described in this invention can be implemented in hardware, software, firmware, middleware, microcode, or a combination thereof. For hardware implementation, the processing unit can be implemented in one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), general-purpose processors, controllers, microcontrollers, microprocessors, other electronic units for performing the functions described in this application, or combinations thereof.

[0090] For software implementation, the technology of this invention can be achieved by executing the functional modules (e.g., procedures, functions, etc.) of this invention. The software code can be stored in memory and executed by a processor. The memory can be implemented in the processor or externally.

[0091] Example 3

[0092] Embodiments of the present invention may also provide a non-volatile storage medium for storing a computer program. When the computer program is executed by a processor, it can implement the various steps in the above method embodiments.

[0093] Example 4

[0094] Embodiments of the present invention may also provide a computer program product, including a computer program / instructions. When the computer program / instructions are executed by a processor, the various steps in the above method embodiments can be implemented.

[0095] Technical effects:

[0096] This invention offers significant practical advantages, primarily in the following three aspects: First, it improves data utilization. Traditional GNSS-R systems typically discard data segments when they cannot identify reflection paths, resulting in a waste of valuable information. This invention, through precise fitting and stripping of direct signals, can separate the masked reflection paths from mixed waveforms, significantly improving the effective utilization of inversion data. Second, it enables automatic algorithm switching and improves system efficiency. This method introduces a strategy judgment mechanism based on GNSS-R geometric altitude estimation, which can automatically shut down the path stripping module when the flight altitude exceeds a set threshold, avoiding unnecessary computational overhead and thus improving overall processing efficiency. It is suitable for the real-time operation requirements of embedded or edge computing platforms. Third, it enhances system robustness. This invention does not rely on specific waveform morphology, ideal interference fringes, or strong reflection signals, and can operate in complex reflection environments such as urban areas, mountains, and bare soil, enhancing the stability and reliability of the system in practical applications.

[0097] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to the embodiments, those skilled in the art should understand that modifications or equivalent substitutions to the technical solutions of the present invention do not depart from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A GNSS-R altimeter method integrating direct and reverse signal separation and strategy switching mechanisms, comprising: Step 1: Based on GNSS satellite ephemeris data and receiver location, establish the satellite-to-ground geometric relationship to obtain the estimated flight altitude H of the UAV; Step 2: Determine whether the estimated flight altitude H is less than the set low-altitude threshold. If yes, proceed to Step 3; otherwise, extract the delay difference between the peak value of the direct signal and the peak value of the reflected signal to invert the flight altitude and end. Step 3: Based on the correlation function waveform of the mixed signal and the flight altitude estimate H, construct a joint model of the direct path, and fit the direct signal to obtain the initial parameters of the direct path, including the direct path delay; Step 4: Reconstruct the main path waveform based on the initial parameters of the direct path and separate it from the original signal to obtain the residual waveform; Step 5: Search for local peaks in the residual waveform, calculate the residual signal energy ratio index SRRM, and determine whether the SRRM value is lower than the set threshold. If yes, record the reflected signal delay and proceed to step 6; otherwise, proceed to step 5 to continue searching for secondary peaks. Step 6: Calculate the flight altitude based on the difference between the delay of the direct signal and the delay of the separated reflected signal; Step 7: Verify the consistency between the flight altitude and the estimated flight altitude obtained in Step 1. If the verification is successful, the process ends; otherwise, proceed to Step 5 to continue searching for the secondary peak. The joint model for the direct-fire path in step 3 is as follows: ； in, The simulation function for the direct waveform in time delay The value, The center delay of the direct simulation waveform, To simulate the amplitude of the waveform directly, For direct simulation waveform phase, Let be the standard deviation of the Gaussian envelope. The angular frequency of the carrier wave; The residual signal energy ratio (SRRM) in step 5 is obtained according to the following formula: ； in, These represent the amplitude, angular frequency, and phase of the k-th path, which includes both the direct and reflected paths. K Indicates the total number of paths. j Indicates the imaginary part. This represents the residual energy remaining after path fitting. Represents the original signal energy. This represents the original signal.

2. The GNSS-R altimeter method based on the fusion of direct and reverse signal separation and strategy switching mechanisms according to claim 1, characterized in that, Step 3 includes: Based on the spacecraft's altitude, satellite orbit, and receiver position, a rough arrival delay of the direct signal is calculated using a free-space propagation model. ; by Using the center of the search window, the envelope of the mixed signal is analyzed within this window, which has a chip interval width. The moment with the largest slope of the envelope curve is selected as the precise arrival time. ; At any moment Read the envelope amplitude of the mixed signal respectively and instantaneous phase Thus, the initial parameters of the direct path are obtained. , and .

3. The GNSS-R altimeter method based on the fusion of direct and reverse signal separation and strategy switching mechanisms according to claim 1, characterized in that, Step 4 includes: The direct signal is obtained by fitting the initial parameters of the direct path. From the original signal Residual waveform obtained by stripping .

4. The GNSS-R altimeter method based on the fusion of direct and reverse signal separation and strategy switching mechanisms according to claim 1, characterized in that, The flight altitude obtained in step 6 for: ； ； Where c is the speed of light in a vacuum. The reflected signal delay is represented by θ, which is the current elevation angle of the GNSS satellite.

5. The GNSS-R altimeter method based on the fusion of direct and reverse signal separation and strategy switching mechanisms according to claim 1, characterized in that, Step 7 involves verifying the consistency of the altitude measurement with the estimated altitude obtained in step 1, including: The flight altitude obtained from step 6 is based on the following formula. The difference is calculated by comparing the estimated flight altitude H obtained in step 1 with the actual flight altitude H. : and the set tolerance threshold Compare and judge Less than If the result is positive, then the verification is satisfied.

6. A computer device, comprising a memory, a processor, and a computer program stored in the memory, characterized in that, The processor executes the computer program to implement the method as described in any one of claims 1-5.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method as described in any one of claims 1-5.

8. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the method as described in any one of claims 1-5.

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