GNSS-s radar echo phase correction method based on spaceborne vertical sounding instrument and occultation receiver

Abstract

The application discloses a GNSS-S radar echo phase correction method based on a spaceborne vertical sounding instrument and a occultation receiver, which utilizes a GNSS-S radar, an occultation receiver and a spaceborne vertical sounding instrument on the same low-orbit satellite platform for cooperative detection. The first electron density profile from the bottom to the top of the ionosphere at a specific position in front of the satellite is acquired by the occultation receiver; when the satellite flies to the position, the second electron density profile from the peak height of the ionosphere to the height of the satellite platform is acquired by the vertical sounding instrument; the second profile is used to calibrate and fuse the first profile to obtain a corrected profile; based on the fused profile, the complete electron density distribution of the downlink and uplink propagation paths of the GNSS-S radar signal is reconstructed, and the total electron content of the paths is calculated respectively; then, the phase error correction amount is calculated according to the total electron content and a phase delay model, and finally, the radar echo is phase compensated to correct the target positioning result. The application can realize accurate correction of the GNSS-S radar phase error caused by the ionosphere.

Description

Technical Field

[0001] This invention relates to the fields of radar signal processing and space environment detection technology, and in particular to a GNSS-S radar echo phase correction method based on a spaceborne vertical probe and an occultation receiver. Background Technology

[0002] Global Navigation Satellite System (GNSS-S) external source radar is a bistatic radar system that uses navigation satellites as non-cooperative illumination sources. Due to its advantages such as global coverage, strong concealment, and relatively low cost, it has shown application potential in fields such as marine remote sensing and moving target surveillance. However, GNSS-S radar typically operates in the L-band. Its electromagnetic wave signals need to penetrate the Earth's ionosphere twice during their propagation from high-orbit navigation satellites (external sources) to ground or sea targets, and then be received by low-orbit satellite platforms after being scattered by the targets. As a dispersive medium, the ionosphere's free electrons cause additional phase lead and group delay in the electromagnetic wave signals. This phase error introduced by the ionosphere is a key factor limiting the high-precision ranging, velocity measurement, and imaging capabilities of GNSS-S radar.

[0003] Currently, the main limitations of methods for correcting ionospheric phase errors in GNSS-S radar are as follows:

[0004] (1) Empirical model methods, such as the Klobuchar model, rely on long-term averaged historical ionospheric data. They cannot reflect the dynamic changes and local disturbances of the ionosphere in real time and accurately. Especially during active periods such as ionospheric scintillation and storms, the correction residuals are large and difficult to meet the requirements of high-precision detection.

[0005] (2) Ground-based monitoring network method: The total electron content (TEC) map of the ionosphere is retrieved by using a network of ground-based GNSS receiving stations distributed globally. This method is limited by the geographical distribution density of ground receiving stations. Data is sparse in areas such as oceans and polar regions, resulting in insufficient spatial resolution. Furthermore, there is a certain time delay in data processing and distribution, making it difficult to meet the needs of real-time or near-real-time processing on satellites.

[0006] (3) Insufficient uniformity and adaptability: Existing methods are mostly designed for specific signal frequency bands and fixed observation geometry, lacking universality and adaptive phase compensation capability for GNSS-S radar echo signals in complex scenarios such as multiple frequency bands (such as GPS L1 / L2, Beidou B1 / B2), multiple polarization modes and different signal incident angles. Summary of the Invention

[0007] To address the problems existing in the prior art, the present invention aims to provide a GNSS-S radar echo phase correction method based on a spaceborne vertical probe and an occultation receiver. By coordinating and fusing data from multiple detection payloads carried on a low-orbit satellite platform, a high-precision reconstruction of the ionospheric electron density along the GNSS-S radar signal propagation path is achieved, thereby accurately calculating and compensating for phase errors and improving radar detection performance.

[0008] To achieve the above-mentioned objectives, this invention provides a GNSS-S radar echo phase correction method based on a spaceborne vertical displacement instrument and an occultation receiver. The method, based on a GNSS-S radar, a spaceborne vertical displacement instrument, and an occultation receiver mounted on the same low-Earth orbit satellite platform, includes the following steps:

[0009] Step S1: Receive the echo signal after the external radiation source signal from the navigation satellite near the zenith is scattered by the target using the GNSS-S radar in the downward-looking detection mode, and process the echo signal to obtain the preliminary position information of the target;

[0010] Step S2: Using the occultation receiver in forward occultation detection mode, receive navigation satellite signals and obtain the first vertical electron density profile from the bottom to the top of the ionosphere at position P2 in front of satellite position P1 at time T1. , where H is the ionospheric height measured by occultation;

[0011] Step S3: When the low-orbit satellite flies to position P2, the onboard vertical probe is used in vertical detection mode to obtain a second electron density vertical profile at position P2 at time T2, from the peak ionospheric height to the satellite platform height. , where h is the ionospheric height measured by the plumb line;

[0012] Step S4: Based on the second electron density vertical profile Perpendicular section of the first electron density The corrected electron density profile of the occultation was obtained. ;

[0013] Step S5: Based on the second electron density vertical profile and the corrected occultation electron density profile The complete electron density distribution traversed by the downlink path of the GNSS-S radar signal from the navigation satellite to the target and the uplink path from the target to the low-Earth orbit satellite is reconstructed, and the total electron content (TEC) of the downlink path is calculated respectively. down and total electron content (TEC) of the upward path up ;

[0014] Step S6: Based on the total electron content (TEC) of the downlink pathdown and the total electron content TEC of the uplink path up Calculate the total electron content (TEC) total The corresponding phase error correction ΔΦ was calculated based on the ionospheric phase delay model. true ;

[0015] Step S7: Utilize the phase error correction amount ΔΦ true Phase compensation is performed on the target echo signal received by the GNSS-S radar to correct the target positioning result.

[0016] According to one technical solution of the present invention, step S4 specifically includes:

[0017] Vertical profile of the first electron density and the second electron density vertical profile Spatiotemporal registration was performed using the second electron density vertical profile. The reflected range is in the height range [h peak ,h sat The electron density distribution within the first electron density vertical cross-section. Corrections were performed on the corresponding portions within the same altitude range to obtain the corrected occultation electron density profile. .

[0018] According to one technical solution of the present invention, step S5, reconstructing the complete electron density distribution and calculating the total electron content, specifically includes:

[0019] For the downlink path:

[0020] ;

[0021] For the uplink path:

[0022] ;

[0023] Among them, h target For the target height, h peak h is the peak height of the ionosphere. sat h represents the altitude of the satellite platform. top This represents the height of the top of the ionosphere.

[0024] According to one technical solution of the present invention, in step S6, the phase error correction ΔΦ is calculated based on the ionospheric phase delay model. true Represented as:

[0025] △Φ true =-(40.3 / f)×TEC total ;

[0026] Where f is the operating signal frequency of the GNSS-S radar; TEC total The total electron content is expressed as: TEC total =TEC down +TEC up .

[0027] According to one technical solution of the present invention, the method further includes constructing and deploying a phase correction intelligent model, specifically including:

[0028] Step M1: Based on the long-term on-orbit observation data of the spaceborne vertical probe, the occultation receiver and the GNSS-S radar, a training dataset is constructed. The input features of the training dataset include at least one of electron density profile data, total electron content, radar signal frequency band f, signal polarization mode and signal incident angle. The output label is the corresponding true phase error correction amount.

[0029] Step M2: Construct a deep neural network model and train the deep neural network model using the training dataset;

[0030] Step M3: Deploy the trained deep neural network model on the on-board processing system to predict the input features of real-time observations in order to quickly obtain the phase error correction.

[0031] According to one technical solution of the present invention, in step M1, the accumulation period of the long-term on-orbit observation data is not less than 3 months, the data sample size is not less than 100,000 sets, and it covers different latitude, longitude, altitude and ionospheric activity intensity scenarios.

[0032] According to one technical solution of the present invention, in step M2, the deep neural network model adopts a hybrid architecture of convolutional neural network (CNN) and long short-term memory network (LSTM). The CNN is used to extract the spatial features of the electron density profile, and the LSTM is used to extract the temporal evolution features of the ionospheric parameters.

[0033] According to one aspect of the present invention, a GNSS-S radar echo phase correction system based on a spaceborne vertical probe and an occultation receiver is proposed, comprising:

[0034] The GNSS-S radar module is configured to receive and process echo signals from external radiation sources in a downward-looking detection mode, and output preliminary position information of the target.

[0035] The occultation receiver module is configured to receive navigation satellite signals in forward occultation detection mode and invert to obtain the first electron density vertical profile;

[0036] The spaceborne vertical probe module is configured to acquire a second electron density vertical profile in vertical detection mode.

[0037] The data processing and fusion module is communicatively connected to the GNSS-S radar module, the occultation receiver module, and the spaceborne vertical measuring instrument module, and is configured to execute steps S4 to S7 of the GNSS-S radar echo phase correction method based on the spaceborne vertical measuring instrument and the occultation receiver as described in any of the above technical solutions.

[0038] According to one aspect of the present invention, an electronic device is proposed, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement steps S4 to S7 of the GNSS-S radar echo phase correction method based on a spaceborne vertical probe and an occultation receiver as described in any of the above technical solutions.

[0039] According to one aspect of the present invention, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements steps S4 to S7 of the GNSS-S radar echo phase correction method based on a spaceborne vertical probe and an occultation receiver as described in any of the above technical solutions.

[0040] Compared with existing technologies, the GNSS-S radar echo phase correction method based on a spaceborne vertical probe and an occultation receiver provided by this invention has the following significant technical advantages:

[0041] This invention discloses a GNSS-S radar echo phase correction method based on a spaceborne vertical displacement instrument (VLI) and an occultation receiver. By jointly utilizing the high-precision local detection capability of the VLI and the wide-area detection capability of the occultation receiver, it overcomes the limitations of spatiotemporal resolution of a single data source and achieves high-precision reconstruction of ionospheric electron density along the GNSS-S radar signal path. Furthermore, this method introduces a deep learning-based intelligent correction model, combining the physical advantages of data fusion with the data-driven capabilities of artificial intelligence. Ultimately, it achieves adaptive and high-precision compensation for phase errors in multi-band, multi-polarization radar echoes, significantly improving target positioning performance.

[0042] This invention integrates three payloads with different principles and complementary functions—GNSS-S radar, spaceborne vertical probe, and occultation receiver—onto a single platform to construct a collaborative observation system. Utilizing the high-precision, high-vertical-resolution electron density profile acquired by the vertical probe at a specific location (point P2), the electron density profile retrieved earlier by the occultation receiver at the same geographical location, which has good top coverage but may contain systematic errors or ambiguities, is calibrated and constrained. This effectively combines the local high-precision advantage of the vertical probe with the wide-area coverage capability of occultation data, improving the reconstruction accuracy of the ionospheric electron density distribution along the actual propagation path of the GNSS-S radar signal.

[0043] This invention designs a temporal and spatial coordination process of "forward occultation detection - platform flyby - vertical detection," and performs spatiotemporal registration processing on profile data acquired by different sensors at different times for the same geographical location P2, reducing system errors introduced by ionospheric spatiotemporal variations and sensor differences. Furthermore, specifically targeting the two-way penetration path of GNSS-S radar signals ("downlink (navigation satellite-target) + uplink (target-receiving satellite),"), the electron density distribution on both paths is reconstructed using fused profile data, and the TEC is calculated. This makes the phase error calculation more closely reflect the actual signal propagation process, theoretically resulting in higher correction accuracy compared to methods using single-path or regional average TEC.

[0044] This invention, by introducing a deep learning model (such as a CNN-LSTM hybrid model) trained on long-term on-orbit data, can utilize the complex nonlinear mapping relationship between ionospheric variation patterns, signal characteristics, and phase errors contained in historical data. After deploying this intelligent model, the system can achieve rapid and adaptive phase compensation for GNSS-S radar echo signals in complex scenarios such as multi-band, multi-polarization, and multi-incidence angles, improving the system's robustness and real-time processing capabilities in dynamically changing ionospheric environments.

[0045] This invention provides a more accurate and spatiotemporally matched method for correcting ionospheric phase errors, applicable to fields such as aerospace microwave remote sensing and target detection imaging. It can effectively reduce the positioning error of GNSS-S radar, improve its detection and imaging performance for sea surface targets and slow-moving targets, and enhance the practical value of this technology in fields such as marine monitoring and situational awareness. Attached Figure Description

[0046] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly described below. Obviously, the drawings described below are merely some embodiments of the present invention, and those skilled in the art can obtain other drawings based on these drawings without creative effort.

[0047] Figure 1 This diagram illustrates the system architecture and signal path of a low-Earth orbit satellite platform for multi-payload collaborative detection according to an embodiment of the present invention.

[0048] Figure 2 This schematic diagram illustrates the core flowchart of phase correction data processing according to one embodiment of the present invention.

[0049] Figure 3 The diagram illustrates the construction and application flowchart of a phase correction intelligent model according to one embodiment of the present invention. Detailed Implementation

[0050] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0051] It should be noted that, unless otherwise specified, the embodiments and features described in the embodiments of this application can be combined with each other. The following embodiments only illustrate several implementation methods of this application, and their descriptions are relatively specific and detailed, but they should not be construed as limiting the scope of the patent application. It should be pointed out that, for those skilled in the art, several modifications and improvements can be made without departing from the concept of this application, and these all fall within the protection scope of this application.

[0052] like Figure 1 and Figure 2 As shown, this invention provides a GNSS-S radar echo phase correction method based on a spaceborne vertical displacement instrument and an occultation receiver. The method, based on a GNSS-S radar, a spaceborne vertical displacement instrument, and an occultation receiver mounted on the same low-Earth orbit satellite platform, includes the following steps:

[0053] Step S1: Receive the echo signal after the external radiation source signal from the navigation satellite near the zenith is scattered by the target using the GNSS-S radar in the downward-looking detection mode, and process the echo signal to obtain the preliminary position information of the target;

[0054] GNSS-S radar employs a downward-looking (nadir or near-nadir) detection mode to continuously observe the sea surface or land. Its receiving antenna is pointed towards the zenith to receive backscattered echo signals from navigation signals (external radiation source signals) emitted by high-orbit GNSS satellites (such as GPS, BeiDou, Galileo, etc.) after being scattered by sea surface or land targets (such as ships, sea buoys, specific ground features).

[0055] After receiving the echo signal, a series of preprocessing steps are performed on it, including but not limited to: adaptive filtering to suppress out-of-band interference and noise, low-noise amplification to improve the signal level, coherent demodulation to extract the in-phase (I) and quadrature (Q) components of the signal, and signal coherent processing (such as pulse compression, Doppler processing, etc.) to initially form a one-dimensional range image or two-dimensional image of the target, and output the target's preliminary range, velocity or position information.

[0056] Step S2: Using the occultation receiver in forward occultation detection mode, receive navigation satellite signals and obtain the first vertical electron density profile from the bottom to the top of the ionosphere at position P2 in front of satellite position P1 at time T1. , where H is the ionospheric height measured by occultation;

[0057] The occultation receiver operates in forward occultation detection mode. At time T1, the low-orbit satellite is located at spatial position P1, which is above the geographic latitude and longitude (Lon1, Lat1). The occultation receiver begins to track and receive dual-frequency (such as L1 and L2) navigation signals transmitted from another high-orbit navigation satellite ahead of its flight direction (usually a different signal source than the one in step S1, or using different satellites from the same constellation).

[0058] As the satellite moves, the navigation signal path gradually cuts into and penetrates the ionosphere. Using differential phase or differential code delay observations of the dual-frequency signal, combined with precise satellite orbit and clock data, and through Abel integral transform or other ionospheric inversion algorithms, the vertical distribution of electron density at the tangent point P2 (Lon2, Lat2) where the signal path is tangent to the ionosphere, from the bottom (e.g., 60 km or 80 km) to the top (e.g., 1000 km or above), is determined. This distribution is denoted as the first electron density vertical profile. , where H represents the altitude variable.

[0059] Occultation detection can provide overall profile information from the top to the bottom of the ionosphere.

[0060] Step S3: When the low-orbit satellite flies to position P2, the onboard vertical probe is used in vertical detection mode to obtain a second electron density vertical profile at position P2 at time T2, from the peak ionospheric height to the satellite platform height. , where h is the ionospheric height measured by the plumb line;

[0061] Spaceborne vertical probes (such as digital altimeters for the ionosphere) employ a vertically downward detection mode. When a low-Earth orbit satellite, following its orbit, flies to position P2 (Lon2, Lat2) at a later time T2, the spaceborne vertical probe initiates vertical detection of the ionosphere above that point.

[0062] The spaceborne vertical displacement instrument transmits a series of variable-frequency radio pulses (or linear frequency modulated signals) directly downwards and receives echoes reflected from the ionosphere at different altitudes. Range resolution is improved through pulse compression technology, and a frequency-altitude analysis algorithm is used to convert the echo delays of different frequencies into the virtual altitudes of the corresponding reflection points, thereby retrieving the altitude (h) from the satellite platform. sat (i.e., orbital altitude) down to the peak ionospheric altitude (h peak The electron density vertical distribution within a certain range. This distribution is denoted as the second electron density vertical profile. Where h is the variable of ionospheric height measured by the plumb line (h peak ≤ h ≤ h sat ).

[0063] Vertical measuring instruments directly measure the ionosphere below the satellite, and the profiles obtained from their inversions typically have high vertical resolution and accuracy within the detection range.

[0064] Through steps S2 and S3, two electron density profiles for the same geographical location P2 were obtained: the occultation profile provides the macroscopic structure from bottom to top, but may have systematic biases; the plumb line profile provides local high-precision details from satellite altitude to peak altitude.

[0065] Step S4: Based on the second electron density vertical profile Perpendicular section of the first electron density The corrected electron density profile of the occultation was obtained. ;

[0066] Since the observation times (T1 and T2) of the second electron density vertical profile and the first electron density vertical profile are different, and the observation geometry and inversion principle are also different, direct use may result in spatiotemporal mismatch and systematic bias.

[0067] Vertical profile of the first electron density and the second electron density vertical profile Spatiotemporal registration was performed using the second electron density vertical profile. The reflected range is in the height range [h peak ,h sat The electron density distribution within the first electron density vertical cross-section. Corrections were performed on the corresponding portions within the same altitude range to obtain the corrected occultation electron density profile. It can effectively "inject" the high-precision local measurement information of the vertical measuring instrument into the occultation data, overcome the common error problem of occultation inversion near the peak region, and generate an electron density vertical profile that is continuous above and below the ionospheric peak height and has improved overall accuracy.

[0068] Step S5: Based on the second electron density vertical profile and the corrected occultation electron density profile The complete electron density distribution traversed by the downlink path of the GNSS-S radar signal from the navigation satellite to the target and the uplink path from the target to the low-Earth orbit satellite is reconstructed, and the total electron content (TEC) of the downlink path is calculated respectively. down and total electron content (TEC) of the upward path up ;

[0069] Reconstructing the complete electron density distribution and calculating the total electron content, specifically including:

[0070] For the downlink path:

[0071] ;

[0072] For the uplink path:

[0073] ;

[0074] Among them, h target For the target height, h peak h is the peak height of the ionosphere. sat h represents the altitude of the satellite platform. top This represents the height of the top of the ionosphere.

[0075] By using the fused high-precision profile, the accurate path integral TEC value was calculated separately for the unique two-way penetration path of GNSS-S radar signals, instead of using regional average or single-path approximation of TEC, which can improve the path specificity and accuracy of subsequent phase error calculation.

[0076] Step S6: Based on the total electron content (TEC) of the downlink path down and the total electron content TEC of the uplink path up Calculate the total electron content (TEC) total The corresponding phase error correction ΔΦ was calculated based on the ionospheric phase delay model. true ;

[0077] Calculation of phase error correction ΔΦ based on ionospheric phase delay model true Represented as:

[0078] △Φ true =-(40.3 / f)×TEC total ;

[0079] Where f is the operating signal frequency of the GNSS-S radar; TEC totalThe total electron content is expressed as: TEC total =TEC down +TEC up .

[0080] Step S7: Utilize the phase error correction amount ΔΦ true Phase compensation is performed on the target echo signal received by the GNSS-S radar to correct the target positioning result.

[0081] After phase compensation, GNSS-S radar can effectively eliminate or reduce phase errors introduced by the ionosphere by performing subsequent precise positioning, velocity measurement or imaging processing, thereby obtaining more accurate target position and velocity information and clearer radar images.

[0082] In some embodiments of this invention, the GNSS-S radar echo phase correction method based on a spaceborne vertical probe and an occultation receiver also includes constructing and deploying a smart phase correction model, such as... Figure 3 As shown, it specifically includes:

[0083] Step M1: Based on the long-term on-orbit observation data of the spaceborne vertical probe, the occultation receiver and the GNSS-S radar, a training dataset is constructed. The input features of the training dataset include at least one of electron density profile data, total electron content, radar signal frequency band f, signal polarization mode and signal incident angle. The output label is the corresponding true phase error correction amount.

[0084] Long-term on-orbit observations (e.g., continuous operation for more than 6 months) are conducted using onboard vertical probes, occultation receivers, and GNSS-S radars on low-Earth orbit satellite platforms to systematically accumulate a large number of synchronous or quasi-synchronous observation data pairs. Typically, the accumulation period for these long-term on-orbit observation data is no less than 3 months, the data sample size is no less than 100,000 sets, and the data covers different latitudes, longitudes, altitudes, and ionospheric activity intensities.

[0085] The process of constructing the training dataset is as follows:

[0086] (a) Input feature parameter acquisition

[0087] For each (or group of) valid collaborative observation instances, extract and organize the following multidimensional features as model input:

[0088] (1) Electron density profile data: including the original or pre-processed second electron density vertical profile and the first electron density vertical profile, as well as the occultation electron density profile after fusion correction in step S4;

[0089] (2) Total electron content: The total electron content TEC of the downlink path calculated according to step S5. downand the total electron content TEC of the uplink path up Calculate the total electron content (TEC) total ;

[0090] (3) Radar signal parameters: the signal center frequency f used by the GNSS-S radar to observe the target, the signal polarization mode pol (such as right-hand circular polarization RHCP, left-hand circular polarization LHCP), and the average incident angle θ of the signal relative to the ionosphere;

[0091] (3) Spatiotemporal and environmental parameters: season, geographical location, etc. at the time of observation.

[0092] (ii) Obtaining output label parameters

[0093] The corresponding output label is "true" for the phase error correction ΔΦ. true The high-precision profile of occultation electron density, corrected by a vertical measuring instrument, was obtained through integration and phase correction model calculations.

[0094] Step M2: Construct a deep neural network model and train the deep neural network model using the training dataset;

[0095] The deep neural network model adopts a hybrid architecture of convolutional neural network (CNN) and long short-term memory network (LSTM). The CNN is used to extract the spatial features of the electron density profile, and the LSTM is used to extract the temporal evolution features of the ionospheric parameters.

[0096] The constructed dataset is divided into training, validation, and test sets in a proportional ratio (e.g., 8:1:1). The model is trained using a gradient descent optimization algorithm (such as the Adam optimizer), with the loss function typically chosen as mean squared error (MSE) or mean absolute error (MAE). During training, the model's performance is monitored using the validation set. Early stopping is used to prevent overfitting, and model hyperparameters (such as the number of network layers, neurons, learning rate, batch size, etc.) are adjusted through cross-validation until the model's prediction error on the validation set converges to a preset threshold (e.g., MSE falls below a certain value).

[0097] Step M3: Deploy the trained deep neural network model on the on-board processing system to predict the input features of real-time observations, so as to quickly obtain the phase error correction amount, input the observation parameters in real time, and realize rapid adaptive compensation for the phase of multi-band, multi-polarization, and multi-incident angle GNSS-S radar echo signals.

[0098] The phase correction intelligent model, after being trained and evaluated to meet accuracy requirements using a test set, is solidified and deployed on the onboard data processing unit of a low-Earth orbit satellite. In real-time missions, when the GNSS-S radar is conducting observations, the onboard system synchronously or asynchronously acquires occultation data and vertical probe data (after fusion processing in steps S2-S4) from the current or most recent moment, and combines this with the signal parameters (f, pol, θ, etc.) observed by the current radar to quickly organize them into an input feature vector in the same format as during training. This vector is then input into the deployed intelligent model, which can output the predicted phase error correction ΔΦ almost instantaneously (in milliseconds). true Subsequently, the system utilizes △Φ true Phase compensation is performed directly on the echo signal of the GNSS-S radar (step S7) to complete the correction.

[0099] According to one aspect of the present invention, a GNSS-S radar echo phase correction system based on a spaceborne vertical probe and an occultation receiver is proposed, comprising:

[0100] The GNSS-S radar module includes a downward-looking receiving antenna, a low-noise amplifier, a down-converter, an analog-to-digital converter, and a digital signal processor. Its core function is to receive and process echo signals from external GNSS radiation sources, perform signal acquisition, tracking, demodulation, and primary imaging processing, and output preliminary observation data of the target.

[0101] The occultation receiver module includes a forward-pointing GNSS receiving antenna, an RF front-end, and a baseband processing chip. Its core function is to track navigation satellites ahead of the flight path, acquire dual-frequency pseudorange and carrier phase observations, and combine them with satellite ephemeris data to run ionospheric inversion software, outputting the first electron density vertical profile along the satellite trajectory at different puncture points and the corresponding time and position information.

[0102] The spaceborne vertical probe module includes a vertically downward transmitting / receiving antenna, a transmitter, a receiver, and a signal processing unit. Its core function is to transmit probe signals according to instructions, receive ionospheric echoes, and, through pulse compression and frequency-altitude analysis algorithms, retrieve in real time the second electron density vertical profile below the satellite and the corresponding time and position information.

[0103] The data processing and fusion module is communicatively connected to the GNSS-S radar module, the occultation receiver module, and the spaceborne vertical measuring instrument module, and is configured to execute steps S4 to S7 of the GNSS-S radar echo phase correction method based on the spaceborne vertical measuring instrument and the occultation receiver as described in any of the above technical solutions.

[0104] According to one aspect of the present invention, an electronic device is provided, comprising: one or more processors, one or more memories, and one or more computer programs; wherein the processor is connected to the memory, and the one or more computer programs are stored in the memory. When the electronic device is running, the processor executes the one or more computer programs stored in the memory to cause the electronic device to perform steps S4 to S7 of a GNSS-S radar echo phase correction method based on a spaceborne vertical probe and an occultation receiver as described in any of the above technical solutions.

[0105] The processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor.

[0106] The memory can be an internal storage unit of the terminal device, such as a hard drive or RAM. Alternatively, it can be an external storage device, such as a plug-in hard drive, Smart Media Card (SMC), Secure Digital (SD) card, or Flash Card. Furthermore, the memory can include both internal and external storage units. The memory is used to store the computer program and other programs and data required by the terminal device. It can also be used to temporarily store data that has been output or will be output.

[0107] According to one aspect of the present invention, a computer-readable storage medium is provided for storing computer instructions, which, when executed by a processor, implement steps S4 to S7 of a GNSS-S radar echo phase correction method based on a spaceborne vertical probe and an occultation receiver as described in any of the above technical solutions.

[0108] For example, computer-readable storage media can be read-only memory (ROM), random access memory (RAM), read-only optical disc (CD-ROM), magnetic tape, floppy disk, and optical data storage devices. They can be implemented using computer-executable program code, thus allowing them to be stored in a storage device for execution by a computing device, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. Therefore, this invention is not limited to any particular hardware and software combination.

[0109] This invention provides a GNSS-S radar echo phase correction method based on a spaceborne vertical probe and an occultation receiver. By jointly utilizing the high-precision local detection capability of the spaceborne vertical probe and the wide-area detection capability of the occultation receiver, it overcomes the limitations of spatiotemporal resolution of a single data source and achieves high-precision reconstruction of ionospheric electron density along the GNSS-S radar signal path. This method further introduces a deep learning-based intelligent correction model, combining the physical advantages of data fusion with the data-driven capabilities of artificial intelligence. Ultimately, it achieves adaptive and high-precision compensation for phase errors in multi-band, multi-polarization radar echoes, significantly improving target positioning performance.

[0110] This invention integrates three payloads—GNSS-S radar, spaceborne plumb line instrument, and occultation receiver—into a collaborative observation system. By utilizing the high-precision profile of the plumb line instrument at a specific location (point P), the profile of the occultation receiver at the same location at an earlier time is calibrated and corrected. This solves the core contradiction of the mismatch between the spatiotemporal sparsity of occultation data and the real-time requirements of GNSS-S radar, achieving a fusion benefit of "1+1>2".

[0111] This invention abandons the traditional static empirical model and constructs a hybrid architecture intelligent model based on long-term on-orbit data. It can automatically extract the mapping relationship between radar signal features and phase error, realize rapid compensation of multi-band, multi-polarization, and multi-incident angle signals, and significantly improve the correction adaptability and real-time performance in complex scenarios.

[0112] This invention comprehensively improves the accuracy, real-time performance, and adaptability of low-orbit GNSS-S radar phase correction by integrating multi-load coordination, dynamic registration, and intelligent model technologies, providing an innovative technical solution for ionospheric error correction.

[0113] The above description is merely one embodiment of this application and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of the invention involved in this application is not limited to the technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the inventive concept. For example, technical solutions formed by substituting the above features with (but not limited to) technical features with similar functions disclosed in this application.

Claims

1. A GNSS-S radar echo phase correction method based on a spaceborne vertical probe and an occultation receiver, characterized in that, The method, based on a GNSS-S radar, a spaceborne vertical probe, and an occultation receiver mounted on the same low-Earth orbit satellite platform, includes the following steps: Step S1: Receive the echo signal after the external radiation source signal from the navigation satellite near the zenith is scattered by the target using the GNSS-S radar in the downward-looking detection mode, and process the echo signal to obtain the preliminary position information of the target; Step S2: Using the occultation receiver in forward occultation detection mode, receive navigation satellite signals to obtain the first electron density vertical profile from the bottom to the top of the ionosphere at position P2 in front of satellite position P1 at time T1. , where H is the ionospheric height measured by occultation; Step S3: When the low-orbit satellite flies to position P2, the onboard vertical probe is used in vertical detection mode to obtain a second electron density vertical profile at position P2 at time T2, from the peak ionospheric height to the satellite platform height. , where h is the ionospheric height measured by the plumb line; Step S4: Based on the second electron density vertical profile Perpendicular section of the first electron density The corrected electron density profile of the occultation was obtained. ; Step S5: Based on the second electron density vertical profile and the corrected occultation electron density profile The complete electron density distribution traversed by the downlink path of the GNSS-S radar signal from the navigation satellite to the target and the uplink path from the target to the low-Earth orbit satellite is reconstructed, and the total electron content (TEC) of the downlink path is calculated respectively. down and total electron content (TEC) of the upward path up ; Step S6: Based on the total electron content (TEC) of the downlink path down and the total electron content TEC of the uplink path up Calculate the total electron content (TEC) total The corresponding phase error correction ΔΦ was calculated based on the ionospheric phase delay model. true ; Step S7: Utilize the phase error correction amount ΔΦ true Phase compensation is performed on the target echo signal received by the GNSS-S radar to correct the target positioning result.

2. The GNSS-S radar echo phase correction method based on a spaceborne vertical probe and an occultation receiver according to claim 1, characterized in that, Step S4 specifically includes: Vertical profile of the first electron density and the second electron density vertical profile Spatiotemporal registration was performed using the second electron density vertical profile. The reflected range is in the height range [h peak ,h sat The electron density distribution within the first electron density vertical cross-section. Corrections were performed on the corresponding portions within the same altitude range to obtain the corrected occultation electron density profile. .

3. The GNSS-S radar echo phase correction method based on a spaceborne vertical probe and an occultation receiver according to claim 1, characterized in that, In step S5, the complete electron density distribution is reconstructed and the total electron content is calculated, specifically including: For the downlink path: ； For the uplink path: ； Among them, h target For the target height, h peak h is the peak height of the ionosphere. sat h represents the altitude of the satellite platform. top This represents the height of the top of the ionosphere.

4. The GNSS-S radar echo phase correction method based on a spaceborne vertical probe and an occultation receiver according to claim 1, characterized in that, Step S6 involves calculating the phase error correction ΔΦ based on the ionospheric phase delay model. true Represented as: △Φ true =-(40.3 / f)×TEC total ; Where f is the operating signal frequency of the GNSS-S radar; TEC total The total electron content is expressed as: TEC total =TEC down +TEC up .

5. The GNSS-S radar echo phase correction method based on a spaceborne vertical probe and an occultation receiver according to claim 1, characterized in that, It also includes building and deploying intelligent phase correction models, specifically including: Step M1: Based on the long-term on-orbit observation data of the spaceborne vertical probe, the occultation receiver and the GNSS-S radar, a training dataset is constructed. The input features of the training dataset include at least one of electron density profile data, total electron content, radar signal frequency band f, signal polarization mode and signal incident angle. The output label is the corresponding true phase error correction amount. Step M2: Construct a deep neural network model and train the deep neural network model using the training dataset; Step M3: Deploy the trained deep neural network model on the on-board processing system to predict the input features of real-time observations in order to quickly obtain the phase error correction.

6. The GNSS-S radar echo phase correction method based on a spaceborne vertical probe and an occultation receiver according to claim 5, characterized in that, In step M1, the accumulation period of the long-term on-orbit observation data is no less than 3 months, the data sample size is no less than 100,000 sets, and it covers different latitude, longitude, altitude and ionospheric activity intensity scenarios.

7. The GNSS-S radar echo phase correction method based on a spaceborne vertical probe and an occultation receiver according to claim 5, characterized in that, In step M2, the deep neural network model adopts a hybrid architecture of convolutional neural network (CNN) and long short-term memory network (LSTM). The CNN is used to extract the spatial features of the electron density profile, and the LSTM is used to extract the temporal evolution features of the ionospheric parameters.

8. A GNSS-S radar echo phase correction system based on a spaceborne vertical probe and an occultation receiver, characterized in that, include: The GNSS-S radar module is configured to receive and process echo signals from external radiation sources in a downward-looking detection mode, and output preliminary position information of the target. The occultation receiver module is configured to receive navigation satellite signals in forward occultation detection mode and invert to obtain the first electron density vertical profile; The spaceborne vertical probe module is configured to acquire a second electron density vertical profile in vertical detection mode. The data processing and fusion module is communicatively connected to the GNSS-S radar module, the occultation receiver module, and the spaceborne vertical probe module, and is configured to perform steps S4 to S7 of the method as described in any one of claims 1 to 7.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements steps S4 to S7 of the method as described in any one of claims 1-7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements steps S4 to S7 of the method as described in any one of claims 1-7.

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