GNSS low power estimation intervention system and method for spaceborne targets

Abstract

The application discloses a kind of GNSS low-power estimation formula intervention system and method for spaceborne target, the special constraint of the present application to spaceborne scene high dynamic, on-board resource limited, high-power intervention is easy to expose and interfere with ground non-target receiver, by constructing target orbit estimation, intervention window planning, optimal channel screening, intervention parameter solution, the technical system of low-power signal generation, it can still control the decision output of delay lock loop DLL when intervention signal is lower than real GNSS signal Power, generate baseband intervention signal embedded Doppler compensation and accurate intervention phase, realize accurate controllable deviation injection to target spaceborne receiver pseudorange, and avoid receiver anomaly detection.The present application does not need high-power signal suppression, significantly reduce on-board load power consumption, while the receiving power of intervention signal at ground GNSS receiver antenna end can be lower than the acquisition sensitivity of ground GNSS receiver, effectively avoid interference to ground non-target GNSS receiver, with good concealment and effect.

Description

Technical Field

[0001] This invention belongs to the field of non-cooperative intervention of space targets and satellite navigation countermeasures, and relates to an active defense scheme adapted to spaceborne platforms for non-cooperative satellites. Specifically, it relates to a GNSS (Global Navigation Satellite System) low-power estimation intervention system and method for spaceborne targets. Background Technology

[0002] With the large-scale deployment of remote sensing satellite constellations and low-Earth orbit (LEO) communication constellations, the continuous staring imaging, high-precision orbit determination, and signal monitoring of sensitive areas by non-cooperative satellites have posed a significant space security threat. Simultaneously, with the increasing number of LEO satellites, conventional space management methods are insufficient to effectively constrain non-cooperative LEO satellites that arbitrarily change orbits and engage in high-risk maneuvers, lacking an effective contactless control scheme. Taking remote sensing satellites as an example, during imaging missions of specific areas, the image georegistration accuracy of non-cooperative remote sensing satellites highly depends on the real-time orbit determination and timing results of onboard GNSS. Inter-satellite GNSS intervention can introduce controllable deviations in the positioning calculations of onboard GNSS receivers, causing the image center to deviate from the predetermined target area, rendering the acquired image intelligence worthless and thus suppressing image intelligence in sensitive areas without triggering physical confrontation.

[0003] For non-cooperative low-Earth orbit satellites that arbitrarily change orbits and are highly vulnerable to maneuvering, inter-satellite GNSS intervention provides a non-contact intervention approach: by continuously injecting controllable pseudorange bias, the target satellite's autonomous orbit maintenance system can make misjudgments. Incorrect positioning calculations may trigger orbit change requirements, resulting in unplanned consumption of its propellant. Continuous orbit determination bias will also cause its telemetry data to deviate systematically from the expected orbit on the ground, reducing its mission execution capability.

[0004] To address the aforementioned active defense requirements, GNSS intervention is a feasible approach. This solution provides a GNSS low-power estimation-based intervention system and method for spaceborne targets. Summary of the Invention

[0005] The purpose of this invention is to address the shortcomings of existing technologies by providing a GNSS low-power estimation-based intervention system and method for spaceborne targets. This solution is designed for high-dynamic spaceborne scenarios and can inject pseudorange deviations into the target receiver without high-power signal suppression. This allows the intervening satellite to complete the injection without the target satellite being aware of it, providing a continuous, stable, and covert means for intervening in the orbital behavior of non-cooperative satellites.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: A GNSS low-power estimation intervention method for spaceborne targets includes the following steps: (1) Receive signals from visible navigation satellites, complete signal acquisition, tracking and message demodulation, and calculate and output the pseudocode phase, carrier phase, Doppler frequency offset, ephemeris parameters of visible navigation satellites, as well as the real-time orbit parameters of the satellites themselves. (2) Combine TLE files, ground-based radar or spaceborne radar to obtain the initial orbital parameters of the target satellite, and based on the ephemeris parameters of the visible navigation satellite, calculate the dynamic propagation time from the navigation satellite to the target satellite using the Newton iteration method, combine the Runge-Kutta method to recursively estimate the orbit of the target satellite, estimate the real-time position and velocity vector of the target satellite, and output the pre-compensated Doppler frequency offset. (3) Construct the constrained equations of the spaceborne intervention range, and based on the satellite orbit model, solve the feasible region of the true anomaly angle between the intervention satellite and the target satellite, and quantify the start and end times and effective duration of the intervention window; (4) Within the intervention window, construct the observation matrix and weight matrix for target satellite positioning calculation, calculate the intervention efficiency ratio of each visible satellite channel through SVD singular value decomposition, and select the optimal intervention channel; (5) The LPEI algorithm based on low power estimation is used to calculate the intervention phase, Doppler compensation of the intervention signal, and transmission power control sequence of the optimal intervention channel, and the step size parameter calibration of the progressive pull-back and back is completed simultaneously; thereby generating the baseband intervention signal and transmitting it to the target satellite.

[0007] In the above technical solution, further, the pre-compensation for Doppler frequency offset in step (2) specifically involves: based on the dynamic propagation time calculation results Calculate the theoretical Doppler shift of the target satellite's reception of navigation satellite signals based on the relative motion parameters of the navigation satellite and the target satellite. And the Doppler shift between the intervening satellite and the target satellite The Doppler pre-compensation amount was obtained. : .

[0008] Furthermore, the theoretical Doppler frequency shift of the target satellite receiving navigation satellite signals... And the Doppler shift between the intervening satellite and the target satellite The calculation method is as follows: First based on target satellite position vector at any time Based on the position vector of the transmitting satellite at each moment, calculate the line-of-sight unit vectors of the navigation satellite and the interfering satellite pointing towards the target satellite. Then, take the dot product of the velocity vector difference between the receiver and the transmitter and the corresponding line-of-sight unit vector. Divide the dot product by the speed of light and multiply by the pseudocode frequency to obtain the Doppler frequency shift corresponding to the navigation satellite signal. Interfering with the Doppler frequency shift corresponding to satellite signals .

[0009] Furthermore, the method for constructing the satellite orbit model in step (3) is as follows: In the geocentric inertial coordinate system, define the six orbital roots of the target satellite L and the intervening satellite S, and the true anomaly angle of the target satellite. Angle of true perimeter with interfering satellite The deviation is The intervention angle to be solved is denoted as ; based on the orbital root numbers and coordinate transformation principle, the position vectors of the target satellite and the intervening satellite in the geocentric inertial coordinate system are derived respectively. , The expression will Substitution The expression yields the result of... For time variables, The position vector function of the intervention angle to be determined Complete the general orbit modeling.

[0010] Furthermore, by integrating the message phase delay constraint, antenna elevation angle coverage constraint, and navigation satellite antenna beam constraint, a set of constraint equations for the spaceborne interferable range is obtained. Based on the constructed general orbit model, the true anterior angle feasible region that satisfies the set of constraint equations is solved.

[0011] Furthermore, the constraint equations are as follows:

[0012] in, To preset the maximum erroneous message duration in a 1-bit message cycle, To intervene in the timing of satellite message level determination, The speed of light; For navigation satellite antenna half-beamwidth, , , These are the position vectors of the target satellite L, the navigation satellite G, and the intervention satellite S, respectively.

[0013] Furthermore, step (4) specifically includes: (1) Construct a pseudorange positioning weighted observation model for the target satellite: ,in This is the pseudorange measurement vector. For the observation matrix, The three-dimensional position and clock error state quantities to be estimated are: To measure noise, the weight matrix It is a diagonal matrix, and the diagonal elements are the reciprocals of the standard deviation of the measurement noise of each channel; (2) For the weighted observation matrix Performing Singular Value Decomposition (SVD) yields the state subspace. residual subspace Singular value diagonal matrix ; (3) Calculate the intervention efficacy ratio statistic for each channel: , in, For the first Standard basis vectors for each observation channel; (4) Sort the visible satellite channels from high to low according to the statistical value of intervention efficacy ratio, and select the top 1 to 3 channels as the optimal intervention channels.

[0014] Furthermore, the LPEI algorithm specifically includes the following: (1) Calculate the pseudocode deviation of the selected optimal intervention channel based on the desired position deviation. ; (2) The pseudo-code phase deviation between the intervention signal and the real GNSS signal is set to +1 chip or -1 chip, where +1 chip corresponds to positive pseudorange bias and -1 chip corresponds to negative pseudorange bias; the normalized amplitude ratio between the intervention signal and the real signal is obtained by inverse solving. ; (3) Based on the normalized amplitude ratio and the carrier-to-noise ratio of the real navigation signal received by the target satellite, the carrier-to-noise ratio when the intervention signal reaches the target satellite is calculated; (4) Based on the carrier-to-noise ratio when the obtained interference signal reaches the target satellite, and the distance between the interference satellite and the target satellite, calculate the corresponding spatial attenuation and solve for the maximum transmission power of the interference satellite. (5) Based on the maximum transmission power and the orbital altitude of the intervening satellite, the maximum landing power of the intervening signal is obtained. It is then determined whether the maximum landing power is lower than the acquisition sensitivity of common ground receivers. If so, it is determined that the intervening is suitable. (6) A gradual biasing method is used to generate a transmission power control sequence, raising the intervention signal power from 0 to the target power, and lowering the intervention signal power to 0 within the intervention window after the intervention task is completed.

[0015] Furthermore, in (2), the normalized amplitude ratio is obtained according to the following formula: , in, For the target receiver's lead-lag correlator half-spacing, The pseudocode phase deviation between the intervention signal and the real signal is fixed.

[0016] A low-power estimation-based intervention system for spaceborne targets, designed for satellite navigation systems to implement the method described in any of the preceding descriptions, is integrated into a satellite platform and includes a spaceborne GNSS receiving and computing unit, an intervention solution core unit, and a spaceborne GNSS transmitting and computing unit, wherein: The onboard GNSS receiving and computing unit is used to receive navigation satellite signals and calculate basic navigation parameters; The intervention calculation core unit completes target orbit estimation, intervention window calculation, optimal intervention channel selection, and signal parameter calculation based on the data obtained by the on-board GNSS receiving and computing unit. The onboard GNSS transmission computing unit takes the output of the intervention solution core unit as input and is used to generate pseudocode, carrier, and navigation messages and control power within the effective intervention window. The generated baseband intervention signal is then relayed to the target satellite through the transmitting antenna. The present invention has at least the following beneficial effects: This invention addresses the proactive defense needs of non-cooperative remote sensing satellites in suppressing regional sensitive intelligence acquisition and intervening in the orbital behavior of non-cooperative maneuvering satellites. It addresses the unique constraints of highly dynamic spaceborne scenarios, limited onboard resources, and the vulnerability of high-power interventions to interference with ground-based non-target receivers. The invention constructs a technical system encompassing target orbit estimation, intervention window planning, optimal channel selection, intervention parameter calculation, and low-power signal generation. This system enables the application of controllable biases to the GNSS positioning calculations of target satellites in a low-power, highly concealed manner within spaceborne scenarios.

[0017] This method utilizes the superposition characteristics of the correlation function of the GNSS receiver code tracking loop to construct an offset locking point within the steady-state range of the code tracking loop. This allows the intervention signal to control the decision output of the delay-locked loop (DLL) even when its power is lower than that of the real GNSS signal. This generates a baseband intervention signal embedded with Doppler compensation and precise intervention phase, ultimately completing signal forwarding and achieving precise and controllable deviation injection of pseudorange to the target satellite receiver. A progressive biasing and backoff control logic is designed to further avoid receiver anomaly detection.

[0018] This invention eliminates the need for high-power signal suppression, significantly reducing onboard payload power consumption. Simultaneously, the received power of the interference signal at the ground GNSS receiver antenna can be lower than the acquisition sensitivity of the ground GNSS receiver, effectively avoiding interference with non-target ground GNSS receivers and possessing good concealment and effectiveness.

[0019] Furthermore, the technical details adopted in this invention have the following advantages: 1) This invention supports three initial orbit acquisition methods: TLE file, ground-based radar, and spaceborne radar. It can achieve low-cost initial positioning of cooperative targets through publicly available TLE data, and passive initial positioning of non-cooperative targets through ground-based or spaceborne radar. By combining the Newton-Raphson iteration method and the Runge-Kutta method, the real-time orbital position and velocity vector of the target satellite can be obtained in highly dynamic scenarios, improving the accuracy of subsequent intervention parameter calculation and the success rate of intervention.

[0020] 2) Based on a complete satellite orbit model, this invention completes the accurate solution of the feasible region of intervention angle under the whole orbit scenario by integrating the constraint equations of message delay, antenna coverage and beam constraint, and quantifies the start and end time and duration of the intervention window, so as to realize the precise planning of the attack timing and ensure that the intervention behavior is always implemented within the geometric constraint range.

[0021] 3) This invention proposes a low-power estimation-based intervention scheme adapted to spaceborne scenarios, which can inject pseudorange bias into the target receiver without high-power signal suppression. Experimental verification shows that the power of the intervention signal is lower than that of the real signal. It can still be achieved at that time. Level 3 positioning deviation can effectively suppress the image intelligence value of non-cooperative remote sensing satellites; at the same time, the landing power of the interfering signal can be as low as [missing information]. It has a lower acquisition sensitivity than ground-based GNSS receivers, effectively avoiding interference with non-target ground receivers.

[0022] 4) In the proposed LPEI scheme, the intervention phase is maintained at the +1 or -1 chip position, which causes very small changes in the loop carrier-to-noise ratio, with a maximum fluctuation of only 0.779dB. This is within the carrier-to-noise ratio detection blind zone of conventional receivers and has good concealment.

[0023] 5) The carrier phase does not need to be precisely aligned in the proposed LPEI scheme because the power of the interference signal is extremely low and it is difficult to deflect the carrier loop, so there will be no problems such as carrier cycle slip. However, high-power interference signals will inevitably cause loop anomalies.

[0024] 6) This invention achieves optimal intervention channel selection through SVD singular value decomposition, which can quantitatively evaluate the impact efficiency of single-channel intervention on positioning results, prioritize the selection of channels with high intervention efficiency ratio, maximize the intervention effect under single-channel conditions, and effectively avoid WSSE / RAIM anomaly detection, further improving the concealment of intervention.

[0025] 7) This invention designs a joint intervention parameter calculation mechanism for high-dynamic satellite-borne scenarios, simultaneously completing the accurate calibration of the intervention phase and Doppler pre-compensation, ensuring that the carrier and code rate Doppler characteristics of the intervention signal are highly matched with the real signal, avoiding detection and identification of Doppler anomalies; the progressive biasing and backoff control logic realizes smooth parameterized calibration of the biasing process, avoiding signal jumps during intervention window switching that trigger receiver alarms, thus ensuring the intervention satellite... Can be used on target satellites The injection of positioning deviations was completed without anyone noticing, providing a continuous and stable means for intervening in the orbital behavior of non-cooperative satellites. Attached Figure Description

[0026] Figure 1 This is a schematic diagram illustrating the spatial geometry of the SLG three-star system and the feasible range of intervention.

[0027] Figure 2 This is a schematic diagram of a spaceborne low-power estimation intervention.

[0028] Figure 3 This is a schematic diagram of the principle architecture of the GNSS low-power estimation intervention system for spaceborne targets described in this invention.

[0029] Figure 4 This is a spatial schematic diagram of the intervening satellite Starlink-1010-sp and the target satellite Starlink-1010 in a specific embodiment of the present invention.

[0030] Figure 5 The carrier-to-noise ratio and positioning deviation under high-power intervention.

[0031] Figure 6 The carrier-to-noise ratio and positioning deviation are calculated when the intervention signal is 13dB lower than the real signal.

[0032] Figure 7 The carrier-to-noise ratio and positioning deviation are calculated when the intervention signal is 27 dB lower than the real signal. Detailed Implementation

[0033] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. The terminology used throughout the text is standardized as follows: S-satellite refers to the intervention satellite, i.e., the satellite platform carrying this intervention system; L-satellite refers to the target satellite, i.e., the object of this system's action; G-satellite refers to a GNSS navigation satellite.

[0034] Example 1: GNSS Low-Power Estimation Intervention Method for Spaceborne Targets The GNSS low-power estimation intervention method for spaceborne targets provided in this embodiment includes the following steps: 1) Receive signals from visible navigation satellites through a vertically upward receiving antenna, complete signal acquisition, tracking and message demodulation, and calculate and output the pseudocode phase, carrier phase, Doppler frequency offset, ephemeris parameters of the visible navigation satellites, as well as the real-time orbital parameters of the satellites themselves. 2) Combining the initial target orbit obtained from TLE files, ground-based radar, or spaceborne radar, and based on the visible navigation ephemeris, the dynamic propagation time is calculated using the Newton-Kutta method. The orbit is then recursively extrapolated using the Runge-Kutta method to estimate the real-time position and velocity vector of the target satellite, and a pre-compensated Doppler is output. 3) Based on the orbital parameters output in step 2), construct the constrained equations for the spaceborne intervention range. Based on the satellite orbital model, solve the feasible region of the true anomaly angle between the intervention satellite and the target satellite, and quantify the start and end times and effective duration of the intervention window. 4) Within the intervention window, based on the ephemeris parameters output in step 1), construct the observation matrix and weight matrix for target satellite positioning calculation, calculate the intervention efficiency ratio of each visible satellite channel through SVD singular value decomposition, and select the optimal intervention channel. 5) For high dynamic scenarios on spacecraft, jointly calculate the intervention phase, Doppler compensation of the intervention signal, and transmission power control sequence of the optimal intervention channel, and simultaneously complete the step size parameter calibration of the progressive pull-up and back-down. 6) After the radio frequency transmission module performs digital-to-analog conversion, up-conversion and power amplification on the generated baseband interference signal, it transmits it to the target satellite within the interference window through the transmission antenna aligned with the Earth's center.

[0035] Specifically: In this embodiment, step 2), specifically the estimation of the target satellite orbital parameters, includes: (1) Initial orbit acquisition: The initial orbit parameters of the target satellite are acquired through TLE files, ground-based radar or spaceborne radar to provide initial values ​​for subsequent calculations; (2) Orbital recursion: The orbit of a low-Earth orbit satellite can be accurately recursively deduced by integrating a differential equation, as shown in the following formula. This formula can be solved using methods such as Runge-Kutta calculations.

[0036]

[0037] in for Time-state vector, including satellite position and speed 'a' is the acceleration vector in the inertial coordinate system. For dynamic parameters, This represents the noise term. The sources of orbital perturbations for low-Earth orbit satellites mainly include Earth's non-spherical gravity, N-body gravity, solar radiation pressure, atmospheric drag, tidal forces, and general relativistic effects. Considering both the two-body problem forces and the perturbation forces, the satellite acceleration can be expressed as: in This indicates the gravitational perturbation caused by the Earth's non-spherical shape. This chapter primarily considers the gravitational perturbation of the Sun, representing the gravitational perturbation of N bodies. and lunar gravity , This indicates solar radiation pressure perturbation. Indicates atmospheric drag perturbation, Indicates Earth's tidal perturbations, This represents the Earth's radiation perturbations and relativistic effects.

[0038] (3) Dynamic propagation time calculation: The equations are solved using the Newton-Raphson iterative method to determine the dynamic propagation time of the signal from the navigation satellite G to the target satellite L. The iterative formula is:

[0039] The Jacobian matrix is:

[0040] In the formula For the target satellite position vector, For the navigation star position vector, Let c be the velocity vector of the navigation star, and c be the speed of light.

[0041] (4) To ensure the intervention signal enters the target loop, it is necessary to calculate the Doppler frequency offset of two parts, which need to be corrected when generating the intervention signal. One part is the Doppler of the actual signal, i.e., the Doppler frequency offset between the target satellite L and the navigation satellite G; the other part is the Doppler frequency offset caused by the motion of the intervention satellite S and the target satellite L. The two Doppler frequency offsets are respectively... as well as The calculation equations are as follows: The Doppler frequency offset between the target satellite L and the navigation satellite G is defined as :

[0042] In the formula, For the target satellite velocity vector, This refers to the pseudocode frequency.

[0043] Where the unit vector Defined as:

[0044] The Doppler frequency offset between the target satellite L and the intervening satellite S is defined as :

[0045] Where the unit vector Defined as:

[0046] (5) Combination , as well as Calculate Doppler precompensation :

[0047] In this embodiment, step 3), the calculation of the intervention window, may specifically include: (1) Coordinate system definition and position vector modeling based on orbital root numbers: In the geocentric inertial coordinate system (ECI), the orbital root numbers of the target satellite L are defined as: semi-major axis eccentricity Track inclination Right ascension of ascending node Perigeal argument True near point angle Define intervention satellites The orbital has six elements: semi-major axis eccentricity Track inclination Right ascension of ascending node Perigeal argument True near point angle Define the true perimeter angle deviation between two stars as . The angle of intervention to be solved is denoted as ; based on the six orbital roots and the principle of coordinate transformation, the following is derived: Position vector in the ECI coordinate system for:

[0048] in, , These are rotation matrices about the X-axis and Z-axis, respectively. for The instantaneous geocentric distance is a scalar; the expanded position vector is:

[0049] Similarly, the derivation yields... Position vector in the ECI coordinate system :

[0050] in, for The instantaneous geocentric distance is a scalar; Substitution The expression yields the result of... For time variables, The position vector function of the intervention angle to be determined Complete the general orbit modeling.

[0051] (2) Define the navigation star as Based on the real-time orbital parameters of the three, a core constraint inequality for the message phase delay is constructed:

[0052] in, To preset the maximum erroneous message duration in a 1-bit message cycle, To intervene in the timing of satellite message level determination, The speed of light; (3) By integrating the message phase delay constraint, antenna elevation angle coverage constraint, and navigation satellite antenna beam constraint, a complete set of constraint equations for the spaceborne interferable range is constructed:

[0053] in, This refers to the half-beamwidth of the navigation satellite antenna.

[0054] Figure 1 This is a schematic diagram illustrating the spatial geometry of the SLG three-star system and the feasible range of intervention. The maximum range of existence is in and On an ellipsoid with focus 0°, the antenna elevation angle ranges from 0° to 90°. For In other words, on the one hand, its orbital altitude is required to be higher than And in Within the receiving range; on the other hand, it must be able to observe. Considering the antenna range, Need to be in With the center of the Earth The line connecting the inside of the sphere is its diameter. The dark area in the diagram represents... The feasible range is based on The inner side of the ellipsoid with focus The inner side of the sphere with diameter The intersection of the three on the outer side of the vertical plane. Additionally, due to... Half beamwidth of satellite antenna Generally, it is [20°, 35°]. Need to be in Within the beam coverage area, that is Less than half beamwidth.

[0055] (4) , Different navigation satellite positions Substituting into the system of constraint equations, Given the angular parameters over the entire orbital period, solve for the constrained S satellite under different navigation satellites G. Feasible region; (5) Based on the feasible region of the true nearest angle With satellite orbital angular velocity The start and end times and effective duration of the intervention window are calculated using the following method: according to The feasible region is obtained by taking the true near-point angles of the intervention window as follows: and .

[0056] Step 1: Find the deviated angle from the true nearest angle;

[0057]

[0058] Step 2: Find the level nearest angle from the near nearest angle. ;

[0059]

[0060]

[0061] Step 3: Linear reverse calculation of time using the near-point angle; Depend on , It calculates the mean anterior angle at the initial moment. This is the initial moment of the calculation. The moment the intervention began. End time Intervention duration The calculations are as follows:

[0062]

[0063]

[0064] In this embodiment, step 4), the selection of the optimal intervention channel specifically includes: (1) Construct a pseudorange positioning weighted observation model for the target satellite: ,in This is the pseudorange measurement vector. For the observation matrix, For the three-dimensional position and clock error state quantities to be estimated, To measure noise, the weight matrix It is a diagonal matrix, and the diagonal elements are the reciprocals of the standard deviation of the measurement noise of each channel; (2) For the weighted observation matrix Perform SVD singular value decomposition:

[0065] in, For the state subspace, For residual subspace, It is a singular value diagonal matrix. It is a right singular matrix; (3) Define and calculate the intervention efficacy ratio statistic for each channel:

[0066] in For the first Standard basis vectors for each observation channel; (4) According to The visible satellite channels are sorted from highest to lowest value, and the top-ranked channels are selected. The road passage serves as the optimal intervention channel.

[0067] In this embodiment, step 6), the execution of the LPEI algorithm specifically includes: (1) Based on the obtained optimal intervention channel, calculate the pseudocode deviation of the selected channel according to the position deviation to be achieved. ; (2) The pseudo-code phase deviation between the pre-set intervention signal and the real GNSS signal is fixed at +1 chip or -1 chip, where +1 chip corresponds to positive pseudorange deviation and -1 chip corresponds to negative pseudorange deviation; the normalized amplitude ratio between the intervention signal and the real signal is obtained by combining the following formula. .

[0068]

[0069] in The half-spacing of the target receiver's lead-lag correlator is set to 0.5 chips by default.

[0070] (3) By normalized amplitude ratio The carrier-to-noise ratio when the intervention signal reaches the target satellite is calculated using the following formula. :

[0071] (4) Based on the distance between the intervening satellite and the target satellite By converting the corresponding spatial attenuation, the maximum transmission power of the interfering satellite can be obtained:

[0072] (5) Calculate the maximum ground power of the intervention signal:

[0073] in To intervene in the satellite's orbital altitude. If the landing power is higher than the common ground receiver acquisition sensitivity of -147dBm, it is determined that orbital intervention is not suitable at this time. If it is lower than -147dBm, it is determined that intervention is suitable, and proceed to step (6).

[0074] (6) In order to improve the concealment of the intervention effect, a gradual biasing method is adopted in the gradual biasing and retraction control unit to generate a transmission power control sequence, and slowly increase the intervention signal power from 0 to the target power. And after the intervention task is completed, the intervention signal power is slowly reduced to 0 within the intervention window.

[0075] The intervention phase of the interfering signal includes the intervention pseudo-code phase, the intervention carrier phase, and the intervention message phase. As mentioned above, the intervention pseudo-code phase maintains a deviation of one chip from the real pseudo-code phase, remaining relatively stationary. Since this scheme proposes a low-power signal interfering method, low-power signals are unlikely to affect the continuity of the real carrier loop; therefore, the intervention carrier phase is arbitrary. Because some frequency point messages cannot be predicted, the interfering satellite must acquire the interfering message before accurately broadcasting it. However, due to the large geometric delay, the interfering satellite may need to broadcast messages that have not yet been received in advance. For details on the geometric relationship, see [link to details]. Figure 2 This scheme stipulates that the interfering satellite will broadcast an arbitrary 1-bit message level before acquiring the actual message, and will broadcast the actual 1-bit message after acquiring it. In the message phase delay constraint of the constraint equation set, the following is set: This sets the maximum erroneous message duration within a preset 1-bit message period. For example, if the message period is 20ms, The time is set to 5ms. If the next message bit is not obtained in the first 5ms, but it needs to be broadcast in advance, the broadcast can be arbitrarily set from 1 to 5ms, and can be 1 or -1. After the real message level is obtained in the 6ms, the message of the broadcast signal is changed to the real level, so that the phase of the interfering message and the phase of the real message are consistent when the message bit ends.

[0076] Because the true pseudo-code Doppler changes, and the dynamic displacement of both the interfering satellite and the target satellite introduces additional Doppler, the interfering signal needs to be compensated for these two Doppler components, i.e., the aforementioned Doppler pre-compensation amount. This value is for the pseudocode. The Doppler pre-compensation amount for the carrier can be obtained based on the frequency relationship between the carrier and the pseudocode. The Doppler compensation amount for the message can also be calculated based on the frequency relationship.

[0077] Thus, the phase of the interfering signal (including pseudocode phase, message level, and message phase), the Doppler compensation of the interfering signal (including pseudocode Doppler, carrier Doppler, and message Doppler), and the transmission power control sequence are obtained. Based on these quantities, the baseband interfering signal can be generated for transmission.

[0078] Example 2: GNSS Low-Power Estimation Intervention System for Spaceborne Targets The GNSS low-power estimation-based intervention system for spaceborne targets provided in this embodiment is designed for satellite navigation systems and is integrated into the satellite platform, such as... Figure 3 As shown, the functional architecture is divided into a spaceborne GNSS receiving and computing unit, an intervention and solution core unit, and a spaceborne GNSS transmitting and computing unit. The hardware architecture adopts an RF receiving module, an FPGA module, an ARM module, and an RF transmitting module. The FPGA module and ARM module are not limited to a discrete combination architecture of FPGA chip and ARM chip, but also support a single-chip heterogeneous multi-core processor architecture. The onboard GNSS receiving and computing unit is used to receive navigation satellite signals and calculate basic navigation parameters. It includes a baseband signal processing submodule and a PNT calculation submodule. The baseband signal processing submodule is deployed on the FPGA module and is responsible for signal acquisition, carrier / pseudocode tracking, and navigation message demodulation of satellite signals. The PNT calculation submodule is deployed on the ARM module and communicates bidirectionally with the baseband signal processing submodule. It calculates and outputs the pseudocode phase, carrier phase, Doppler frequency offset, ephemeris parameters of visible navigation satellites, as well as the satellite's real-time position, timing, and orbit parameters. In this embodiment, the radio frequency receiving module receives, down-converts, and filters navigation signals, outputting intermediate frequency signals to the FPGA module. The FPGA module has at least 12 parallel tracking channels, each corresponding to one visible navigation satellite, enabling simultaneous signal tracking and parameter calculation for 12 navigation satellites, and supporting parameter estimation and tracking of multi-system civilian code signals. The ARM module performs navigation message demodulation, satellite ephemeris calculation, and positioning and velocity calculation, outputting the parameters of each visible satellite. The satellite's pseudocode phase, carrier phase, Doppler frequency offset, ephemeris parameters, and The satellite's own real-time orbital parameters.

[0079] The core intervention calculation unit, deployed on an ARM module, has its input connected to the output of an FPGA. It is used to perform target orbit estimation, intervention window calculation, optimal intervention channel selection, and signal parameter calculation. It integrates an onboard target orbit parameter estimation module, an inter-satellite intervention window calculation module, an SVD-based optimal intervention channel selection module, and an intervention signal parameter calculation module. The onboard target orbit parameter estimation module is used to combine the initial orbit of the target satellite obtained from the TLE file, ground-based radar or onboard radar, and based on the visible navigation ephemeris output by the onboard GNSS receiving and computing unit, to complete the real-time position and velocity vector calculation, dynamic propagation time solution and pre-compensated Doppler calculation of the target satellite. The inter-satellite intervention window calculation module has its input end connected to the output end of the onboard target orbit parameter estimation module. It is used to construct a set of constraint equations for the onboard intervention range based on the real-time orbit parameters of the navigation satellite, intervention satellite, and target satellite, and integrates message delay constraints, antenna beam coverage constraints, and navigation satellite coverage constraints. Based on the orbit model of the six elements of the satellite orbit, it solves the feasible region of the true anomaly angle between the intervention satellite and the target satellite, and outputs the start and end times of the intervention window, the effective duration, and the list of available navigation satellites within the window. The optimal intervention channel selection module based on SVD has its input end connected to the output end of the onboard GNSS receiving and computing unit and the inter-satellite intervention window calculation module, respectively. It is used to construct a weighted observation matrix based on the visible navigation star ephemeris parameters within the effective intervention window, split the state subspace and residual subspace through SVD singular value decomposition, calculate the intervention efficiency ratio of each visible satellite channel, and select at least one target channel with the best efficiency from high to low efficiency ratio. The intervention signal parameter calculation module has its input terminals connected to the output terminals of the inter-satellite intervention window calculation module and the SVD-based optimal intervention channel selection module, respectively. The intervention parameters to be solved include the pseudorange pull, transmit power, pseudocode Doppler, and carrier Doppler of the intervention signal. The navigation message and the real message of the intervention signal are kept consistent. A low-power estimation-based interference scheme (hereinafter referred to as LPEI) is used to calculate the pseudorange pull and transmit power to achieve relative stillness between the pseudocode phase of the intervention signal and the real signal. The obtained intervention signal phase (including pseudocode phase, message level, and message phase) and power control sequence, along with the intervention signal Doppler compensation (including pseudocode Doppler, carrier Doppler, and message Doppler), are sent to the onboard GNSS transmission calculation unit.

[0080] The onboard GNSS transmission calculation unit, with its input end connected to the output end of the intervention signal parameter calculation module, is divided into a baseband intervention signal generation submodule and a radio frequency transmission submodule. The baseband intervention signal generation submodule is deployed on the FPGA module and is used to generate and control the pseudocode, carrier, and navigation message within the effective intervention window. The radio frequency transmission submodule corresponds to the radio frequency transmission module in the hardware architecture and is connected to the baseband intervention signal generation submodule. It is used to perform digital-to-analog conversion, up-conversion, and power amplification on the generated baseband intervention signal before forwarding it to the target satellite through the transmitting antenna.

[0081] In this embodiment, The satellite is equipped with a vertically upward omnidirectional GNSS receiving antenna to ensure stable reception of navigation satellite signals. The satellite is additionally equipped with a high-gain transmitting antenna, installed with its orientation strictly aligned with the Earth's center, to transmit low-power intervention signals within the intervention window. satellite.

[0082] In this embodiment, the onboard target orbit parameter estimation module is the core front-end module of this system. It is connected to the ARM module of the onboard GNSS receiving and computing unit, and contains an initial orbit acquisition unit, a dynamic propagation time calculation unit, a Doppler frequency shift calculation unit, and an orbit recursion unit connected in sequence. The initial orbit acquisition unit supports three methods: 1) TLE file method, obtained by parsing uploaded from the ground. 1) The satellite's initial orbit number is six; 2) Ground-based radar method, using a ground-based tracking and control radar network to monitor... The satellite performs ranging, angle measurement, and velocity measurement to obtain the results. The satellite's initial position and velocity vector in the ECI coordinate system; 3) Spaceborne radar method, through The satellite's own onboard SAR or lidar Satellites perform space rendezvous measurements, combined with Satellite orbital parameters were obtained. The satellite's initial orbital parameters; the dynamic propagation time calculation unit uses Newton's iterative method to solve for the signal from... satellite to Satellite dynamic propagation time; Doppler shift calculation unit calculation Satellite reception The theoretical Doppler frequency shift of the satellite signal, and the Doppler frequency shift between the S-satellite and L-satellite, are used to obtain the Doppler pre-compensation amount; the orbit recursive unit is performed using the Runge-Kutta method. Satellite orbit recursion, output The satellite's real-time orbital position and velocity vector provide fundamental data for subsequent intervention window calculations and intervention parameter solutions.

[0083] In this embodiment, the inter-satellite intervention window calculation module is primarily responsible for solving the problem of accurate planning of intervention timing in spaceborne scenarios. It is connected to the spaceborne target orbit parameter estimation module and includes a constraint equation construction unit, a true anomaly angle feasible region solution unit, and an intervention window output unit. The constraint equation construction unit integrates message phase delay constraints, antenna elevation angle coverage constraints, and... Satellite antenna beam constraints are used to construct a set of constraint equations for the onboard interference range; the true anomaly angle feasible region solution unit completes general orbit modeling based on the six roots of the satellite orbit, transforming the constraint equations into equations based on the true anomaly angle deviation between the two satellites. Solving the equations for variables yields the feasible region that satisfies the constraints. The intervention window output unit calculates the start and end times and effective duration of the intervention window based on the true anomaly angle feasible region and the satellite orbital angular velocity, and simultaneously outputs the parameters that consistently satisfy the constraints within the intervention window. Satellite list.

[0084] In this embodiment, the SVD-based optimal intervention channel selection module is designed to maximize the intervention effect under conditions of few co-viewing satellites and few channels in a spaceborne scenario. It is connected to the onboard GNSS receiving and computing unit and the inter-satellite intervention window calculation module, and incorporates a weighted least squares solution unit and an SVD decomposition unit. The weighted least squares solution unit constructs the pseudorange positioning observation matrix. ,in To effectively intervene within the visible window Number of satellites Simultaneously construct a weight matrix The weighted observation matrix is ​​obtained. ,in The noise standard deviation of the Nth channel can be estimated using the elevation angle; SVD decomposition unit pairs Perform singular value decomposition and split the state subspace. With residual subspace Calculate the intervention efficacy ratio statistic for each visible channel. ,according to The values ​​are sorted from high to low, and the channels ranked 1st to 3rd are selected as the optimal intervention channels.

[0085] In this embodiment, the intervention signal parameter calculation module is the core decision-making module of the system. It is connected to the inter-satellite intervention window calculation module and the SVD-based optimal intervention channel selection module, and integrates a Doppler pre-compensation calculation unit, an intervention phase calculation unit, a power dynamic control unit, and a progressive biasing and backoff control unit. The Doppler pre-compensation calculation unit calculates the signal parameters according to the system's parameters. Satellite and The relative motion parameters of the satellite are used to calculate the carrier wave of the interfering signal and the Doppler compensation of the message; the interfering phase calculation unit calculates the pseudocode phase and message phase of the interfering signal based on the target pseudorange deviation; the power dynamic control unit determines the transmission power of the interfering signal based on the actual signal power; the progressive pull-up and pull-back control unit completes the parameter calibration of the pull-up step size and pull-back step size, and outputs it to the baseband signal generation submodule for execution.

[0086] In the above scheme, the onboard GNSS receiving and computing unit provides reference ephemeris and time synchronization data for target orbit estimation; the output of target orbit estimation is the sole input reference for the quantization calculation of the intervention window; the feasible region constraint of the intervention window is a prerequisite for the optimal channel selection by SVD; the highly concealed channel selected by SVD is the core prerequisite for the stable implementation of low-power intervention; the intervention signal parameter calculation module simultaneously completes the parameter calibration of Doppler, phase, and bias step size, providing precise control quantities for low-power signal generation; finally, a low-power intervention signal is generated. This scheme can maintain the stability and concealment of pseudorange towing under the stringent constraints of few channels, low power, and high dynamics in the onboard scenario.

[0087] Experimental simulation This solution combines the Spirent simulator to perform a hardware-in-the-loop simulation of a spaceborne scenario. Figure 4 This is a spatial diagram of the intervening satellite Starlink-1010-sp and the target satellite Starlink-1010, with the following orbital parameters:

[0088] The simulation period is from 18:46:00 on 08-Dec-2024 to 18:48:10 on 08-Dec-2024.

[0089] The simulation experiment used a Spirent simulator to obtain track simulation and radio frequency data output. An intermediate frequency acquisition device was used to convert the radio frequency data into intermediate frequency data, and then a software receiver was used to simulate the data.

[0090] Three sets of experiments were conducted. The first set of experiments used a high-power intervention method. The actual signal carrier-to-noise ratio (CNR) was 50 dB, the intervention signal power was 52 dB, and its grounding power was -121.43 dBm. The maximum positional deviation produced was 26.2 m, significantly higher than the sensitivity of the ground receiver, and its CNR fluctuation was large, making it easily detectable. See the detailed experimental results below. Figure 5 .

[0091] The second set of experiments employed the low-power intervention scheme proposed in the patent. The intervention signal carrier-to-noise ratio was 37 dB, the grounding level was -136.43 dBm, and the maximum position error was 25.63 m. Although the grounding power was still higher than the ground sensitivity, the carrier-to-noise ratio fluctuation was significantly reduced, and a similar position deviation was produced as with high power. See the detailed experimental results below. Figure 6 .

[0092] The third set of experiments employed the low-power intervention scheme proposed in the patent. The intervention signal carrier-to-noise ratio was 23dB, the grounding level was -150.43dBm, and the maximum error was 11.26m. The carrier-to-noise ratio fluctuations in this experiment were virtually imperceptible. See the detailed experimental results below. Figure 7 .

[0093] For most satellite missions, orbit determination accuracy is required at the meter level or even the dm and cm level. Therefore, this scheme can effectively achieve the purpose of intervention.

[0094] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0095] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0096] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0097] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0098] The embodiments described above are merely some preferred embodiments of the present invention, and are not intended to limit the invention. Those skilled in the art can make various changes and modifications without departing from the spirit and scope of the invention. Therefore, all technical solutions obtained by equivalent substitution or equivalent transformation fall within the protection scope of the present invention.

Claims

1. A GNSS low-power estimation intervention method for spaceborne targets, characterized in that, Includes the following steps: (1) Receive signals from visible navigation satellites, complete signal acquisition, tracking and message demodulation, and calculate and output the pseudocode phase, carrier phase, Doppler frequency offset, ephemeris parameters of visible navigation satellites, as well as the real-time orbit parameters of the satellites themselves. (2) Combine TLE files, ground-based radar or spaceborne radar to obtain the initial orbital parameters of the target satellite, and based on the ephemeris parameters of the visible navigation satellite, calculate the dynamic propagation time from the navigation satellite to the target satellite using the Newton iteration method, combine the Runge-Kutta method to recursively estimate the orbit of the target satellite, estimate the real-time position and velocity vector of the target satellite, and output the pre-compensated Doppler frequency offset. (3) Construct the constrained equations of the spaceborne intervention range, and based on the satellite orbit model, solve the feasible region of the true anomaly angle between the intervention satellite and the target satellite, and quantify the start and end times and effective duration of the intervention window; (4) Within the intervention window, construct the observation matrix and weight matrix for target satellite positioning calculation, calculate the intervention efficiency ratio of each visible satellite channel through SVD singular value decomposition, and select the optimal intervention channel; (5) The LPEI algorithm based on low power estimation is used to calculate the intervention phase, Doppler compensation of the intervention signal, and transmission power control sequence of the optimal intervention channel, and the step size parameter calibration of the progressive pull-back and back is completed simultaneously; thereby generating the baseband intervention signal and transmitting it to the target satellite.

2. The GNSS low-power estimation intervention method for spaceborne targets according to claim 1, characterized in that, The pre-compensation for Doppler frequency offset in step (2) specifically involves: based on the dynamic propagation time solution results Calculate the theoretical Doppler frequency shift of the target satellite receiving signals from the navigation satellite based on the relative motion parameters of the navigation satellite and the target satellite. And the Doppler shift between the intervening satellite and the target satellite The Doppler pre-compensation amount was obtained. : 。 3. The GNSS low-power estimation intervention method for spaceborne targets according to claim 2, characterized in that, Theoretical Doppler frequency shift of target satellite receiving navigation satellite signals And the Doppler shift between the intervening satellite and the target satellite The calculation method is as follows: First based on target satellite position vector at any time The position vector of the launched satellite is used to calculate the line-of-sight vector between the navigation satellite and the intervention satellite pointing to the target satellite. Next, take the dot product of the velocity vector difference between the receiver and the transmitter and the corresponding line-of-sight unit vector. Divide the dot product by the speed of light and then multiply by the pseudocode frequency to obtain the Doppler frequency shift corresponding to the navigation satellite signal. Interfering with the Doppler frequency shift corresponding to satellite signals .

4. The GNSS low-power estimation intervention method for spaceborne targets according to claim 1, characterized in that, The method for constructing the satellite orbit model in step (3) is as follows: In the geocentric inertial coordinate system, define the six orbital roots of the target satellite L and the intervening satellite S, and the true anomaly angle of the target satellite. Angle of true perimeter with interfering satellite The deviation is , that is, the intervention angle to be solved, where; Based on the orbital root numbers and coordinate transformation principles, the position vectors of the target satellite and the intervening satellite in the geocentric inertial coordinate system are derived respectively. , The expression will Substitution The expression yields the result of... For time variables, The position vector function of the intervention angle to be determined Complete the general orbit modeling.

5. The GNSS low-power estimation intervention method for spaceborne targets according to claim 4, characterized in that, By integrating the message phase delay constraint, antenna elevation angle coverage constraint, and navigation satellite antenna beam constraint, a set of constraint equations for the spaceborne interferable range is obtained. Based on the constructed general orbit model, the true anterior angle feasible region that satisfies the set of constraint equations is solved.

6. The GNSS low-power estimation intervention method for spaceborne targets according to claim 5, characterized in that, The constraint equations are as follows: ， in, To preset the maximum erroneous message duration in a 1-bit message cycle, To intervene in the timing of satellite message level determination, The speed of light; For navigation satellite antenna half-beamwidth, , , These are the position vectors of the target satellite L, the navigation satellite G, and the intervention satellite S, respectively.

7. The GNSS low-power estimation intervention method for spaceborne targets according to claim 1, characterized in that, Step (4) specifically includes: (1) Construct a pseudorange positioning weighted observation model for the target satellite: ,in This is the pseudorange measurement vector. For the observation matrix, For the three-dimensional position and clock error state quantities to be estimated, To measure noise, the weight matrix It is a diagonal matrix, and the diagonal elements are the reciprocals of the standard deviation of the measurement noise of each channel; (2) For the weighted observation matrix Performing Singular Value Decomposition (SVD) yields the state subspace. residual subspace Singular value diagonal matrix ; (3) Calculate the intervention efficacy ratio statistic for each channel: , in, For the first Standard basis vectors for each observation channel; (4) Sort the visible satellite channels from high to low according to the statistical value of intervention efficacy ratio, and select the top 1 to 3 channels as the optimal intervention channels.

8. The GNSS low-power estimation intervention method for spaceborne targets according to claim 1, characterized in that, The LPEI algorithm specifically includes the following: (1) Calculate the pseudocode deviation of the selected optimal intervention channel based on the desired position deviation. ; (2) The pseudo-code phase deviation between the intervention signal and the real GNSS signal is set to +1 chip or -1 chip, where +1 chip corresponds to positive pseudorange bias and -1 chip corresponds to negative pseudorange bias; the normalized amplitude ratio between the intervention signal and the real signal is obtained by inverse solving. ; (3) Based on the normalized amplitude ratio and the carrier-to-noise ratio of the real navigation signal received by the target satellite, the carrier-to-noise ratio when the intervention signal reaches the target satellite is calculated; (4) Based on the carrier-to-noise ratio when the obtained interference signal reaches the target satellite, and the distance between the interference satellite and the target satellite, calculate the corresponding spatial attenuation and solve for the maximum transmission power of the interference satellite. (5) Based on the maximum transmission power and the orbital altitude of the intervening satellite, the maximum landing power of the intervening signal is obtained. It is then determined whether the maximum landing power is lower than the acquisition sensitivity of common ground receivers. If so, it is determined that the intervening is suitable. (6) A gradual biasing method is used to generate a transmission power control sequence, raising the intervention signal power from 0 to the target power, and lowering the intervention signal power to 0 within the intervention window after the intervention task is completed.

9. The GNSS low-power estimation intervention method for spaceborne targets according to claim 8, characterized in that, The normalized amplitude ratio in (2) is obtained according to the following formula: ， in, For the target receiver's lead-lag correlator half-spacing, The pseudocode phase deviation between the intervention signal and the real signal is fixed.

10. A GNSS low-power estimation-based intervention system for spaceborne targets, characterized in that, The system is designed for satellite navigation systems to implement the method described in any one of claims 1-9, and is integrated into a satellite platform, including an onboard GNSS receiving and computing unit, an intervention and solution core unit, and an onboard GNSS transmitting and computing unit, wherein: The onboard GNSS receiving and computing unit is used to receive navigation satellite signals and calculate basic navigation parameters; The core intervention calculation unit completes target orbit estimation, intervention window calculation, optimal intervention channel selection, and signal parameter calculation based on the data obtained by the on-board GNSS receiving and computing unit. The onboard GNSS transmission calculation unit takes the output of the intervention solution core unit as input and is used to generate pseudocode, carrier and navigation messages and control power within the effective intervention window, and forward the generated baseband intervention signal to the target satellite through the transmission antenna.

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