Satellite navigation control method, system and receiver based on task driving

Abstract

The application provides a satellite navigation control method, system and receiver based on task driving, and relates to the technical field of satellite navigation. Through a task-driven closed-loop space observation control mechanism, candidate space observation configurations are dynamically generated and evaluated, and the optimal configuration is selected in combination with multi-dimensional constraint conditions, so that precise matching of observation resources and real-time task targets is realized, the problem of separation of space processing strategy and navigation task in the prior art is effectively solved, and the effect of improving navigation precision is achieved. After the space observation configuration is reconstructed, the satellite navigation state is updated, and a task-driven closed-loop space observation control is formed. Through continuous closed-loop optimization, the system can actively adapt to changes in task targets and challenges of external environment, thereby improving the performance and reliability of the satellite navigation system as a whole.

Description

Technical Field

[0001] This invention relates to the field of satellite navigation technology, and more specifically, to a mission-driven satellite navigation control method, system, and receiver. Background Technology

[0002] Satellite navigation typically uses array antennas to receive signals from multiple satellites. Through code tracking, carrier tracking, and Doppler estimation, pseudorange, carrier phase, and frequency observations are generated. Position, velocity, clock bias, attitude, integer ambiguity, and other states are then estimated by positioning or integrated navigation algorithms. Multi-element array antennas utilize the spatial amplitude and phase differences between elements, employing beamforming, null formation, space-time processing, or multi-channel joint processing to improve the signal-to-interference-plus-noise ratio and suppress interference. A typical array output is obtained by multiplying the element synchronization sampling vector by the spatial array weights.

[0003] In existing array satellite navigation systems, the space processing target is mainly determined by the signal-to-interference-plus-noise ratio (SINR), output power, or null depth. The array weights are usually used as front-end filtering parameters. Navigation control relies on fixed priors, and there is a lack of dynamic feedback between the front-end and back-end navigation tasks, resulting in poor system flexibility and accuracy. Summary of the Invention

[0004] The problem that this invention aims to solve is that traditional satellite navigation arrays lack dynamic feedback between the front-end and back-end navigation tasks, resulting in poor system flexibility and accuracy.

[0005] To address the aforementioned problems, in a first aspect, the present invention provides a task-driven satellite navigation control method, comprising: Acquire satellite navigation observations, including the mission status of the current navigation processing target; Based on current satellite navigation observations, array space manifold information, and current space observation configurations, multiple candidate space observation configurations are generated. For each candidate spatial observation configuration, the mission-related observation value is calculated based on the mission status. The mission-related observation value represents the measurement capability of the navigation observation formed by the candidate spatial observation configuration after being applied to the multi-element array for the current mission target. Candidate spatial observation configurations are selected based on preset constraints. The target spatial observation configuration is determined from the filtered candidate spatial observation configurations by solving the objective function; The actual target space observation configuration is executed, and the reconstructed space observation configuration is loaded into the satellite navigation receiving link to change the space observation mapping from the multi-element array input to the satellite navigation measurement output; New satellite navigation observations are generated under the modified space observation mapping, the satellite navigation status is updated, and the subsequent space observation configurations are repeatedly generated, evaluated, filtered and reconstructed based on the updated satellite navigation status to form a mission-driven closed-loop space observation control.

[0006] Optionally, the mission-related observation value is calculated based on at least one of the following data: the rank or singular value of the observed Jacobian, Fisher information, equivalent Fisher information, predicted posterior covariance, conditional mutual information, state entropy reduction, floating-point ambiguity covariance, ambiguity surrogate quantity, fixed solution risk surrogate quantity, assumption separability, array calibration parameter information, or mission-related satellite joint observation quality.

[0007] Optionally, when the state to be estimated includes both target and non-target states, the task-related observation value is calculated based on the equivalent information matrix after eliminating the influence of non-target states, the marginal posterior covariance, or the target state conditional information.

[0008] Optionally, the objective function is the mission-related observation value, or a comprehensive function consisting of the mission-related observation value and residual interference cost, continuity risk, integrity risk and configuration change cost; The target space observation configuration is determined in the following way: among the selected candidate space observation configurations, the candidate space observation configuration that maximizes the objective function is selected as the target space observation configuration.

[0009] Optionally, when actually executing the target space observation configuration, if switching directly from the current space observation configuration to the target space observation configuration does not meet the predetermined safety conditions, at least one intermediate space observation configuration is generated to form a multi-segment configuration path from the current space observation configuration to the target space observation configuration, and the adjacent configurations in the configuration path meet the predetermined safety conditions, wherein the predetermined safety conditions include at least one of the preset carrier continuity conditions or key satellite availability conditions.

[0010] Optionally, the loading of the space observation configuration includes at least one of the following: updating digital beamforming weights, updating space-time filtering coefficients, updating analog or radio frequency phase shifters, updating controllable gainers, enabling or disabling array elements, reorganizing subarrays, establishing multiple parallel or time-division space projection branches, changing the reference beam or auxiliary observation beam for a specific satellite, and adjusting the resource mapping between correlators and space projections.

[0011] Secondly, the present invention also provides a mission-driven satellite navigation control system, comprising: The sampling module is used to acquire satellite navigation observations, which include the task status of the current navigation processing target; The candidate space observation configuration generation module is used to generate multiple candidate space observation configurations based on the current satellite navigation observations, array space manifold information, and the current space observation configuration. The mission observation value evaluation module is used to calculate the mission-related observation value for each candidate spatial observation configuration based on the mission status. The mission-related observation value characterizes the measurement capability of the navigation observation formed by the candidate spatial observation configuration after being applied to the multi-element array for the current mission target. The continuity and integrity constraint module is used to filter candidate spatial observation configurations based on preset constraint conditions; The configuration decision module is used to determine the target spatial observation configuration from the filtered candidate spatial observation configurations by solving the objective function; The space observation reconstruction execution module is used to actually execute the target space observation configuration. After the space observation configuration is reconstructed, it is loaded into the satellite navigation receiving link to change the space observation mapping from the multi-element array input to the satellite navigation measurement output. The navigation status update module is used to generate new satellite navigation observations under the changed space observation mapping, update the satellite navigation status, and repeatedly generate, evaluate, filter and reconstruct subsequent space observation configurations based on the updated satellite navigation status, so as to form a mission-driven closed-loop space observation control.

[0012] Thirdly, the present invention provides a satellite navigation receiver, including a processor and a memory; The memory is used to store computer programs; The processor is configured to, when executing the computer program, cause the satellite navigation receiver to perform the task-driven satellite navigation control method as described in the first aspect.

[0013] This invention provides a task-driven satellite navigation control method, system, and receiver. Compared with existing technologies, it has the following advantages: Through a mission-driven closed-loop space observation control mechanism, candidate space observation configurations are dynamically generated and evaluated. The optimal configuration is then selected based on multi-dimensional constraints, achieving precise matching between observation resources and real-time mission objectives. This effectively addresses the disconnect between space processing strategies and navigation tasks in existing technologies, thereby improving navigation accuracy. Continuous closed-loop optimization enables the system to proactively adapt to changes in mission objectives and external environmental challenges, thus enhancing the overall performance and reliability of the satellite navigation system. Attached Figure Description

[0014] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0015] Figure 1 A flowchart illustrating a task-driven satellite navigation control method provided in an embodiment of the present invention; Figure 2 A schematic diagram of the security screening process provided in an embodiment of the present invention; Figure 3 A schematic diagram illustrating the spatial configuration switching process provided in an embodiment of the present invention; Figure 4 This is a schematic diagram of a task-driven satellite navigation control system provided in an embodiment of the present invention. Detailed Implementation

[0016] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions in the embodiments of this application are described clearly and completely. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0017] In satellite navigation systems, the spatial processing target of multi-element array antennas is typically statically determined by the signal-to-interference-plus-noise ratio (SINR), output power, or null depth. The array weights are fixed as front-end filtering parameters, and navigation control relies on prior knowledge, resulting in a lack of dynamic interaction between front-end signal processing and back-end navigation tasks. This problem prevents the system from adjusting its spatial observation configuration according to real-time mission requirements, limits the accuracy of navigation state estimation, reduces overall system reliability, and consequently affects the accuracy of position, velocity, and attitude calculations.

[0018] To better understand the above technical solutions, the following will provide a detailed explanation of the technical solutions in conjunction with the accompanying drawings and specific implementation methods.

[0019] like Figure 1 As shown in the embodiment of this application, a task-driven satellite navigation control method includes: S1: Acquire satellite navigation observations, which include complex sampling vectors received by a multi-element array and the task state representing the current navigation processing target.

[0020] Specifically, a multi-element array refers to an array composed of multiple antenna elements, capable of receiving satellite navigation signals and performing signal processing using the spatial characteristics between the elements, such as beamforming or null formation. Complex sampling vectors can be synchronously sampled from each element of the multi-element array to form the original digital signal stream. The mission state can be input from an external system; for example, when an UAV performs a precision landing mission, the mission state is set to "high-precision vertical positioning."

[0021] S2: Based on the current satellite navigation observations, array space manifold information, and current space observation configuration, generate multiple candidate space observation configurations.

[0022] Specifically, array spatial manifold information refers to information describing the response characteristics of a multi-element array to signals from different directions, including element positions, radiation patterns, and mutual coupling; this information is crucial for generating and evaluating space observation configurations. Space observation configuration refers to the specific settings adopted by a multi-element array when receiving and processing satellite navigation signals, such as beamforming weights, element selection, and space-time processing parameters; this configuration directly affects the quality and characteristics of navigation observations.

[0023] Based on the received satellite signal strength and direction, as well as the array's geometric structure information, a series of possible beamforming weight combinations can be generated using a pre-defined algorithm. Alternatively, multiple configuration parameter sets can be randomly generated within a predefined parameter space, each representing a potential space observation configuration.

[0024] S3: For the mission status, calculate the mission-related observation value for each candidate spatial observation configuration. The mission-related observation value characterizes the measurement capability of the navigation observation formed by the candidate spatial observation configuration after being applied to the multi-element array for the current mission target.

[0025] Specifically, if the mission status is "high-precision positioning," the reciprocal of the geometrical factor of precision (GDOP) of the positioning error under each candidate configuration can be calculated as the mission-related observation value. Alternatively, if the mission status is "interference resistance," the ability to suppress known interference sources under each candidate configuration can be calculated as a value indicator.

[0026] S4: Select candidate spatial observation configurations based on preset constraints.

[0027] Specifically, a threshold can be set; if a candidate configuration causes the signal strength of a critical satellite to fall below this threshold, the configuration is eliminated. Alternatively, if a candidate configuration shows a high risk of carrier phase cycle slip in simulation evaluation, that configuration is not considered.

[0028] S5: Determine the target spatial observation configuration from the filtered candidate spatial observation configurations by solving the objective function.

[0029] Specifically, the objective function can be the value of mission-related observations, and the candidate configuration that maximizes this value can be selected as the target space observation configuration. Alternatively, a comprehensive objective function can be constructed, which weights and sums the value of mission-related observations with some penalty terms (e.g., configuration changes, residual interference power), and the configuration that optimizes the comprehensive objective function can be selected.

[0030] S6: The actual target space observation configuration is executed. After the space observation configuration is reconstructed, it is loaded into the satellite navigation receiving link to change the space observation mapping from the multi-element array input to the satellite navigation measurement output.

[0031] Specifically, the satellite navigation receiver link refers to the entire signal processing path from the signal received by the multi-element array to the final output navigation measurement values. Space observation mapping refers to the conversion relationship between the raw input signal of the multi-element array and the satellite navigation measurement output; this mapping can be changed by altering the space observation configuration.

[0032] The objective function can be the mission-related observation value, and the candidate configuration that maximizes this value can be selected as the target space observation configuration. Alternatively, a comprehensive objective function can be constructed, which weights and sums the mission-related observation value with some penalty terms (e.g., configuration change, residual interference power), and the configuration that optimizes the comprehensive objective function can be selected.

[0033] S7: Under the changed space observation mapping, new satellite navigation observations are formed, the satellite navigation status is updated, and the generation, evaluation, screening and reconstruction of subsequent space observation configurations are repeated based on the updated satellite navigation status to form a mission-driven closed-loop space observation control.

[0034] Specifically, under the new space observation configuration, the receiver can generate more accurate pseudorange and carrier phase observations. These observations are input into the navigation filter to update the navigation state (such as position, velocity, and attitude). Subsequently, the system will restart the above configuration optimization process based on the new navigation state and possible changes in the mission state to achieve dynamic adaptive control.

[0035] In this optional embodiment, a task-driven closed-loop space observation control mechanism dynamically generates and evaluates candidate space observation configurations. Combined with multi-dimensional constraints, the optimal configuration is selected, achieving precise matching between observation resources and real-time task objectives. This effectively solves the problem of the disconnect between space processing strategies and navigation tasks in existing technologies, offering advantages in improving navigation accuracy, reliability, and anti-interference capabilities. This method can dynamically optimize the space observation configuration of the multi-element array based on real-time navigation task requirements and environmental changes. For example, in the aforementioned high-precision hovering mission of a UAV, traditional systems may not be able to effectively suppress dynamic interference while ensuring high accuracy. However, this method, by calculating the value of task-related observations and combining multiple constraints, can intelligently select the optimal configuration, ensuring that the navigation system can still provide high-precision and high-completeness services in complex environments. This dynamic adaptability not only solves the problem of lack of dynamic feedback between the front-end and back-end navigation tasks in existing systems but also, through continuous closed-loop optimization, enables the system to proactively adapt to changes in task objectives and challenges in the external environment, thereby improving the overall performance and reliability of the satellite navigation system.

[0036] The following is a detailed description of each step.

[0037] S1: Acquire satellite navigation observations, which include complex sampling vectors received by a multi-element array and the task state representing the current navigation processing target.

[0038] Specifically, set The discrete-time complex sampling vector received by the array element array is: (1) In the formula, For the current set of tracked satellites, Indicates satellite The common complex link term relative to the selected reference point, This represents the array space manifold at sampling point n. This indicates the incident direction of the satellite signal reaching the array at sampling point n; Indicates interference or abnormal signal components. Indicates noise.

[0039] Define task status The task status can be specified by the upper-layer application, automatically generated by the navigation receiver status, or determined by the task scheduling module based on the current environment and performance requirements. The task status can correspond to at least one or more of the following tasks: position, velocity, or clock bias estimation; RTK or PPP-AR integer ambiguity preservation, search, or recovery; carrier continuity preservation; attitude or angular motion estimation; interference suppression; spoofing, anomaly, or multipath discriminability enhancement; array manifold, channel phase, or phase center parameter calibration; navigation integrity or hazardous misleading information risk control; and weighted combination or priority switching of multiple tasks.

[0040] The mission status also includes corresponding mission parameters, such as target status subspace, accuracy threshold, risk limit, priority satellite set, continuity requirements, mission time limit or weight parameters.

[0041] S2: Based on the current satellite navigation observations, array space manifold information, and current space observation configuration, generate multiple candidate space observation configurations.

[0042] Specifically, such as Figure 2 As shown, state information is generated based on current satellite navigation observations and historical satellite navigation observations. This state information is as follows: (2) in, For navigation or attitude state estimation, To estimate covariance or equivalent uncertainty, For array manifold or environment model parameters, This is a carrier phase continuity related state. In a state of integrity, This refers to the remaining risk budget or other constraint status.

[0043] Generate a candidate spatial observation configuration set based on task status and status information. ,in, This represents the Lth candidate spatial observation configuration in the candidate spatial observation configuration set.

[0044] Candidate spatial observation configurations can be generated in one or more of the following ways: pre-setting a weight dictionary; searching within the neighborhood of the current weight; generating baseline weights by MVDR, LCMV, power inversion or other anti-interference algorithms and then applying task-related perturbations; solving the optimization problem based on the array manifold model; generating a configuration path by model predictive control; generating candidates by the learning model and then filtering them by the physical constraint module.

[0045] Define the candidate spatial observation configuration within the control period t. It must contain at least one or more of the following: (3) in, It is a spatial weight vector or weight matrix. For the enabled beam or projection set, Select the state for the array element or subarray. For the allocation of relevant or observational resources, These are control parameters related to phase reference, time alignment, or calibration. The configuration may contain only a single weight vector, or it may include multi-weight, multi-beam, time-division projection, or other equivalent spatial linear or nonlinear observation maps.

[0046] S3: For the mission status, calculate the mission-related observation value for each candidate spatial observation configuration. The mission-related observation value characterizes the measurement capability of the navigation observation formed by the candidate spatial observation configuration after being applied to the multi-element array for the current mission target.

[0047] Specifically, in a space observation configuration, for satellites The resulting spatial response can be written as: (4) In this space observation configuration, multiple sampling points are set within the control period t.

[0048] Under the space observation configuration, array sampling is spatially weighted to obtain a spatially mapped output: (5) Substituting equation (1) into equation (5) and using the spatial response definition of equation (4), we get: (6) The first term in the formula represents the useful components of each satellite after space processing, the second term represents the residual interference components, and the third term represents the space-weighted noise components. It can be seen that the space observation configuration... Different complex gains are applied to each satellite signal, while the power and spatial correlation of residual interference and noise are changed.

[0049] right With satellite The local code and carrier copy are correlated and despread, and approximate within the correlation integration interval. and If constant, the relevant output is: (7) In the formula, For satellite Local reference copy, For the relevant accumulated points, The expression represents complex conjugate. Substituting equation (6) into equation (7), and utilizing the condition that different satellite pseudocodes are approximately orthogonal, the corresponding baseband observation can be written as: (8) In the formula, To configure the space observation with the relevant equivalent interference plus noise term, that is, the component formed by the correlation despreading of the residual interference and noise components in equation (7), This indicates that during control period t, the satellite Common multilink terms relative to the selected reference point; This indicates that within the control period t, the satellite The resulting spatial response; This represents the incident direction of the satellite signal arriving at the array within the control period t. The baseband observation covariance is: (9) In the formula, Let be the spatial covariance matrix of the interference plus noise. When it is a matrix, For parallel branch multidimensional complex observation vectors, Add a noise vector to the corresponding equivalent interference. Its covariance matrix; when When it degenerates into a single weight vector, Degenerate into a scalar This leads to the satellite. In space observation configuration The equivalent carrier-to-noise ratio is as follows: (10) Therefore, changing the space observation configuration changes the space observation mapping from multi-element physical input to navigation measurement output.

[0050] For candidate spatial observation configurations, the task-related observation values ​​are calculated. These observation values ​​are not limited to a single fixed mathematical form and can be calculated based on at least one or more of the following data: the Jacobian rank, minimum singular value, or condition number of local observations of the target state; the Fisher information matrix, equivalent Fisher information, or other data. Optimal Optimal Optimal The optimal function; the trace, determinant, maximum eigenvalue, or target state orientation variance of the predicted posterior covariance; the conditional mutual information or state entropy reduction between candidate spatial observations and the target state; the floating-point ambiguity covariance of RTK or PPP-AR, the ambiguity distinguishability surrogate, or the fixed solution risk surrogate; the hypothesis separability between the true signal and the deceptive or anomalous hypothesis; the information content of the array calibration parameters (calibration information gain of unknown parameters of the array manifold); and the availability, geometric strength, or joint observation quality of the mission-related satellite set.

[0051] The baseband observations generated by equation (6) are further used to generate pseudorange and carrier phase observations: (11) In the formula and Satellites Pseudorange and carrier phase observations, and These are the corresponding observation functions for pseudorange and carrier phase observations, respectively. For the target state, and The observation noises are pseudorange and carrier phase observations, respectively. The variance of the observation noise is inversely proportional to the equivalent carrier-to-noise ratio in equation (10). In carrier phase observations... The term indicates that the spatial configuration directly introduces additional phase, which is the physical source of the carrier phase continuity constraint discussed later.

[0052] Record the target state The observed Jacobian matrix is , Represents the observation model, Representing the target state, the observation noise covariance is... , If is a calibration constant, then the task equivalent information matrix is: (12) Equation (12) shows the space observation configuration pass and Influence This determines the mission-related observation value. Thus, the array sampling of Equation (1) is continuously mapped to the mission observation value through Equations (5) to (12), forming a complete mission-driven causal chain for space observation reconstruction.

[0053] For example, under the local Gaussian approximation, the corresponding task equivalent information matrix can be configured using candidate space observations. The proxy quantity for calculating the value of observations relevant to the task: (13) or: (14) In the formula, Configure candidate space observations The corresponding task equivalent information matrix is ​​determined by equation (12); It is the determinant of a matrix; A small positive regularization coefficient is used to ensure that the logarithmic determinant of the information matrix is ​​still defined even when it is rank deficient or ill-conditioned; To and Identity matrices of the same dimension; It is the smallest eigenvalue of the matrix.

[0054] Proxy quantity of task-related observation value under the D-optimal criterion The larger the value, the stronger the joint estimability of the task state and the smaller the prediction error ellipsoid volume; E represents the proxy quantity of the task-related observation value under the optimality criterion. This represents the amount of information about the worst observable direction of the task state; the larger the value, the less likely there is a significant weak observable direction.

[0055] Based on rigorous mathematical statistics such as the rank or singular values ​​of observed Jacobian data and Fisher information, it is possible to more accurately characterize the measurement capabilities and information contributions of different space observation configurations to the current mission objective. This enables the system to make more informed and effective decisions during the closed-loop control process of generating, evaluating, filtering, and reconstructing space observation configurations, thereby significantly improving the adaptability, accuracy, and reliability of the satellite navigation system in complex environments and ensuring that navigation missions are completed in an optimal manner.

[0056] When the state to be estimated includes both target and non-target states, the mission-related observation value is calculated based on the equivalent information matrix after eliminating the influence of non-target states, the marginal posterior covariance, or the target state conditional information. The target state refers to the core parameters of interest to the current navigation mission, such as the aircraft's position, velocity, and attitude; these are key information directly affecting mission execution and decision-making. Non-target states refer to auxiliary parameters that need to be processed simultaneously during navigation estimation but are not directly of interest to the current mission, such as receiver clock bias, ionospheric delay, tropospheric delay, multipath effect parameters, array manifold error parameters, or carrier phase ambiguity. Accurate estimation of these non-target states is crucial for the accurate solution of the target state, but it is not the ultimate goal of the mission itself.

[0057] For example, when non-target parameters exist, the equivalent information of the target state can be obtained through the Schur complement or generalized Schur complement of the block information matrix. For states with time evolution, the finite-time domain task value can preferably be calculated under a prediction model: (15) In the formula, Indicates length is Candidate spatial observation configuration sequence; To predict the number of time-domain steps; For the first Step-by-step spatial observation configuration; For the first Step in configuration The instantaneous task equivalent information matrix is ​​calculated according to formula (12); For the state disturbance to propagate from the initial time to the th time... The state transition Jacobian matrix for each step is used to convert information from each time step to the same state reference point; This is the matrix transpose. The scalar criterion function can be any scalar mapping such as the logarithmic determinant of equation (13), the minimum eigenvalue of equation (14), the trace, A-optimal or c-optimal, etc. This application does not limit its specific form.

[0058] For non-negligible process noise or intertemporal correlation observations, the full joint likelihood, Bayesian information, or predicted posterior covariance can be used directly for evaluation, instead of being limited to the summation of simple information matrices.

[0059] Different satellites may be equipped with the same space observation configuration, different space observation configurations, or a shared main space configuration, and one or more auxiliary space observation branches may be set up so that the auxiliary space observation branches are used for candidate space observation configuration evaluation without replacing the main navigation carrier observation branches.

[0060] This application ensures that, in complex scenarios where the state to be estimated includes both target and non-target states, the calculated mission-related observation values ​​accurately reflect the observations' ability to measure a specific mission objective (i.e., the target state). This avoids interference from the uncertainty of non-target states on the evaluation of target state observation values, allowing the optimization process of space observation configuration to focus more on the core requirements of the mission. Therefore, the system can more effectively select the space observation configuration most conducive to improving the accuracy of target state estimation, thereby significantly improving the accuracy and reliability of navigation tasks, especially in application scenarios with high accuracy requirements for specific navigation parameters.

[0061] S4: Based on preset constraints, candidate space observation configurations are screened. The preset constraints include at least one of the following: key satellite availability constraints, carrier phase continuity constraints, interference suppression constraints, navigation integrity constraints, array model uncertainty constraints, and space observation configuration change constraints.

[0062] Specifically, to prevent high-value candidate space observation configurations from leading to critical satellite lock-up, carrier phase reference abrupt changes, or increased integrity risks, this application implements constraint screening for candidate space observation configurations. Preferred constraints include at least one or more of the following constraints.

[0063] The key satellite availability constraints: (16) in, Represents a spatial weight vector; This indicates the incident direction of the satellite signal arriving at the array within the control period t; This represents the array space manifold of satellite s within period t; For a collection of key satellites, This represents the minimum spatial complex response amplitude threshold. The vector norm is used. This constraint requires that the spatial complex response amplitude of the critical satellite be no less than a threshold to prevent it from falling into a null trap and losing lock.

[0064] The carrier phase continuity constraint: (17) (18) (19) in, For phase sensitivity, To continuously increase the error probability of the carrier, Risk of weekly fluctuations; This indicates the upper limit of allowable phase sensitivity. This represents the upper limit of the allowable probability of continuous carrier error increase. This represents the upper limit of the allowable cycle slip risk. Furthermore, it is not required that all implementations explicitly calculate the error probability; instead, monotonically correlated or experimentally calibrated engineering surrogate quantities can be used, such as the phase increment confidence interval, PLL residual, predicted frequency jump, minimum carrier-to-noise ratio, weight change rate, array response lower bound, or integrity protection level. This constraint assesses and controls the impact of space observation configuration switching on carrier phase continuity to avoid cycle slips or phase loss, thereby ensuring the accuracy of high-precision navigation and positioning.

[0065] The interference suppression constraint: (20) in, Configure the output residual interference power under C for candidate space observations. To the interference space covariance matrix, The upper limit of the allowable residual interference power is... The trace is a matrix. This constraint ensures that, under the new space observation configuration, the system's ability to suppress external interference still meets the requirements, avoiding significant impacts on navigation performance from interfering signals. Its function is to guarantee the purity and anti-interference capability of the navigation signal.

[0066] The navigation integrity constraint: (twenty one) in, Risk of misleading information This represents the upper limit of the permissible risk of misleading information. Navigation integrity constraints are used to assess and control the risk of misleading information output by the navigation system, ensuring the reliability of the navigation solution under any space observation configuration. Its function is to prevent the system from failing to issue timely warnings when providing erroneous navigation information.

[0067] The array model uncertainty constraints are as follows: (twenty two) in, As an indicator of model uncertainty, This represents the upper limit of the allowable uncertainty index for the model. This constraint considers the potential errors or uncertainties inherent in the multi-element array model itself and ensures that the space observation configuration remains robust under these uncertainties. Its purpose is to improve the system's adaptability and robustness to changes in the real environment.

[0068] The constraints on the changes in the space observation configuration are as follows: (twenty three) in, This represents a measure of configuration changes. Configure the allowed upper limit for change metrics; This represents the candidate space observation configuration within the control period t-1. Space observation configuration change constraints are used to limit the drasticness or frequency of changes during space observation configuration switching, in order to avoid instability and resource consumption caused by frequent or large-scale system adjustments. Its function is to ensure the smooth operation of the system and the efficiency of resource management.

[0069] Configuration change metrics are defined separately for each configuration component and then weighted and synthesized: (twenty four) in, It is the Frobenius norm, used to measure the continuous change of weight components; , , and For the definition of , see the definition of formula (3); This represents the spatial weight vector within the control period t-1; This indicates the selection state of array elements or subarrays within the control period t-1. This indicates the allocation of relevant or observational resources within the control period t-1. This represents the control parameters within the control period t-1. For the set symmetric difference, It serves as the set cardinality, used to measure changes in discrete components such as element selection states and beam sets; , , , , The non-negative weighting coefficients for the corresponding items can be set according to the task status or hardware constraints; spatial phase change The key satellite spatial phase jump is determined according to equation (27) or equation (29). When the configuration only includes weight components, equation (24) degenerates into... .

[0070] Furthermore, there is no limitation on the specific form of the configuration change metric. Any change metric that satisfies non-negativity and takes zero when the configuration remains unchanged can be used, such as weighted Euclidean distance, Hamming distance, switch count, or experimentally calibrated engineering proxy quantity.

[0071] The introduction of key satellite availability constraints ensures continuous tracking capability of core mission satellite signals; carrier phase continuity constraints effectively avoid cycle slip problems in high-precision positioning, guaranteeing positioning accuracy and stability; interference suppression constraints significantly improve the system's anti-interference performance in complex electromagnetic environments; navigation integrity constraints fundamentally guarantee the reliability and security of navigation information, reducing the risk of dangerous misleading information; array model uncertainty constraints enhance the system's robustness to errors in the actual array model; and space observation configuration change constraints optimize the system's operational stability and resource utilization efficiency. These specific constraints work synergistically, ensuring that the final selected space observation configuration not only maximizes the mission-related observation value but also comprehensively guarantees the performance, reliability, security, and stability of the navigation system under multiple complex factors, thereby significantly improving the practicality and reliability of mission-driven satellite navigation control.

[0072] S5: Determine the target spatial observation configuration from the filtered candidate spatial observation configurations by solving the objective function.

[0073] Specifically, the target spatial observation configuration is determined as follows: among the screened candidate spatial observation configurations, the one that maximizes the objective function is selected as the target spatial observation configuration. The objective function is the task-related observation value, or a comprehensive function comprising the task-related observation value, residual interference cost, continuity risk, integrity risk, and configuration change cost.

[0074] The target spatial observation configuration is selected from the set of candidate spatial observation configurations that satisfy the constraints (i.e., the filtered set of candidate spatial observation configurations). For example, the objective function can be solved as follows: (25) In the formula, This represents the set of candidate spatial observation configurations after filtering. Characterizing the residual interference cost or interference exposure, The weight representing the residual cost of interference or the exposure to interference. Characterizing continuity risk or integrity risk, The weight representing continuity risk or integrity risk. The cost of configuration changes, such as changes in weights, number of switching operations, and additional related resources or power consumption, is represented. The weights represent the costs of configuration changes. This indicates the mission-related observational value under candidate space observation configuration C. This indicates the target space observation configuration.

[0075] The aforementioned objective function can quantitatively evaluate each selected candidate spatial observation configuration. Its value can simply reflect the mission-related observation value, or it can comprehensively consider multiple factors such as residual interference costs, continuity risks, integrity risks, and configuration change costs. By calculating the objective function value corresponding to each selected candidate spatial observation configuration and selecting the configuration that maximizes the objective function value, the system can intelligently determine the target spatial observation configuration that satisfies all constraints and has the best overall performance under the current mission state and environmental conditions.

[0076] In another implementation, mission value and constraints are not treated as a weighted sum, but rather as a hierarchical priority: first, critical physical security and carrier continuity are guaranteed; second, the integrity risk cap is met; and then, mission observation value is maximized within the remaining feasible set.

[0077] S6: The actual target space observation configuration is executed. After the space observation configuration is reconstructed, it is loaded into the satellite navigation receiving link to change the space observation mapping from the multi-element array input to the satellite navigation measurement output.

[0078] Specifically, after selecting the target space observation configuration, the target space observation configuration is actually written into the receiving link. Loading the space observation configuration includes at least one of the following: updating digital beamforming weights; updating space-time filter coefficients; updating analog or radio frequency phase shifters, controllable gainers, or hybrid beam networks; enabling, disabling, or reconfiguring array elements and subarrays; establishing multiple parallel or time-division space projection branches; changing the reference beam, auxiliary observation beam, or calibration beam used for a specific satellite; adjusting the resource mapping between the correlator and the space projection to align the specified weight output with the specified satellite code or carrier local oscillator for observation; and implementing a step-by-step path transition for the target weights rather than a one-time jump.

[0079] After reconstruction, the receiver uses the new configuration to generate codes, carrier waves, Doppler, co-source multi-space projection, spatial relative observations, or other navigation measurements, and updates the state information for the next time step. Then, the next task-driven refactoring cycle begins.

[0080] like Figure 3As shown, during the actual execution of the target space observation configuration, if switching directly from the current space observation configuration to the target space observation configuration does not meet predetermined safety conditions, at least one intermediate space observation configuration is generated, forming multiple configuration paths from the current space observation configuration to the target space observation configuration. The predetermined safety conditions are ensured to satisfy predetermined safety conditions between adjacent configurations within the configuration paths. These predetermined safety conditions include at least one of preset carrier continuity conditions or critical satellite availability conditions. The carrier continuity conditions and critical satellite availability conditions can directly adopt the aforementioned carrier continuity constraints and critical satellite availability constraints.

[0081] For implementations that require maintaining high-precision carrier continuity, the configuration changes before and after the satellite... The array complex responses are as follows: (26) The spatial phase change introduced by the configuration change is: (27) The phase change can be predicted by an array manifold model or measured through observations using dual-weighted or multi-weighted methods. For example, under the conditions of the same original sample and shared code oscillator and carrier oscillator, the following can be formed: (28) Then it can be estimated that: (29) In the formula, and These are the spatial weight vectors before and after reconstruction, respectively. and The weight components in; and Satellites The complex space response before and after reconstruction is calculated according to equation (4); for The abbreviated form; For configuration changes to satellite The introduced spatial phase change is the amount that needs to be compensated by the carrier loop or corrected by the phase reference. This indicates that the phase angle of a complex number is taken.

[0082] For satellite The amplitude of the related signal after reconstruction is approximately the same before and after reconstruction under dual-weighted observation from the same source. and Applying the same batch of original samples in parallel with a shared code local oscillator and a carrier local oscillator. and The resulting related output; The phase term is shared by both paths, including common components such as local oscillator phase, propagation delay, and clock difference; It is the imaginary unit.

[0083] because and Originating from the same batch of samples and sharing the same local oscillator, and Since the two paths are the same, the conjugate multiplication operation of equation (29) cancels out the two, thereby separating the spatial phase change introduced by the configuration change; for The estimated value, Indicates complex conjugation.

[0084] In a preferred embodiment, a new space configuration is submitted only when the phase transfer quality, carrier tracking status, and critical satellite response meet the thresholds; otherwise, the original configuration is maintained, the reconstruction step size is reduced, an intermediate configuration is inserted, or the current reconstruction is abandoned.

[0085] For example, when the current configuration To target configuration When direct switching does not meet carrier continuity conditions or critical satellite availability conditions, a configuration path can be planned: (30) in, Indicates the current configuration With target configuration The first intermediate space observation configuration between them, Indicates the current configuration With target configuration The Kth intermediate space observation configuration between adjacent configurations ensures that predetermined safety conditions are met. The path objective integrates finite time-domain information gain, total control variation, path minimum satellite response, and cumulative risk.

[0086] The configuration path can be pre-calculated under a fixed model; the configuration path can also be executed in a rolling time domain manner, where only the current first segment of the planned configuration path is executed in each control cycle, and subsequent configuration paths are regenerated or updated after obtaining new satellite navigation observations after reconstruction, thus forming a causal closed-loop control.

[0087] By introducing intermediate space observation configurations and constructing multiple configuration paths, and ensuring that adjacent configurations within the paths meet predetermined safety conditions, this application's scheme achieves a smooth and gradual switching of space observation configurations. This not only guarantees the continuity and stability of the navigation system during configuration reconfiguration, avoiding navigation interruptions or accuracy degradation caused by drastic switching, but also enables the system to more reliably execute optimized space observation configurations under dynamically changing navigation task requirements and complex electromagnetic environments, thereby continuously providing high-quality and highly reliable navigation services. This mechanism, while maintaining navigation integrity and availability, fully leverages the advantages of task-driven space observation configurations, enhancing the robustness of the overall navigation system.

[0088] S7: Under the changed space observation mapping, new satellite navigation observations are formed, the satellite navigation status is updated, and the generation, evaluation, screening and reconstruction of subsequent space observation configurations are repeated based on the updated satellite navigation status to form a mission-driven closed-loop space observation control.

[0089] Specifically, the closed-loop space observation control is executed in each control cycle in the following causal order: predict the current state based on historical observations, determine the current space observation configuration based on the predicted state, execute the current space observation configuration and obtain the current observations, update the state using the current observations, and then determine the space observation configuration for the next control cycle.

[0090] The reconstructed satellite navigation observations include at least one of pseudorange, carrier phase, Doppler, carrier-to-noise ratio, co-source multi-spatial projection complex observations, spatial relative amplitude and phase observations, or the quality indicators of the observations.

[0091] like Figure 4 As shown in the figure, an embodiment of this application provides a mission-driven satellite navigation control system, comprising: The sampling module 10 is used to acquire satellite navigation observations, which include complex sampling vectors received by a multi-element array and a task state representing the current navigation processing target.

[0092] The candidate space observation configuration generation module 20 is used to generate multiple candidate space observation configurations based on the current satellite navigation observations, array space manifold information and the current space observation configuration.

[0093] The mission observation value evaluation module 30 is used to calculate the mission-related observation value for each candidate spatial observation configuration based on the mission status. The mission-related observation value characterizes the navigation observation formed by the candidate spatial observation configuration acting on the multi-element array to measure the current mission target.

[0094] The continuity and integrity constraint module 40 is used to screen candidate space observation configurations according to preset constraints. The preset constraints include at least one of the following: key satellite availability constraints, carrier phase continuity constraints, interference suppression constraints, navigation integrity constraints, array model uncertainty constraints, and space observation configuration change constraints.

[0095] The configuration decision module 50 is used to determine the target spatial observation configuration from the selected candidate spatial observation configurations by solving the objective function.

[0096] The space observation reconstruction execution module 60 is used to actually execute the target space observation configuration. After the space observation configuration is reconstructed, it is loaded into the satellite navigation receiving link to change the space observation mapping from the multi-element array input to the satellite navigation measurement output.

[0097] The navigation state update module 70 is used to generate new satellite navigation observations under the changed space observation mapping, update the satellite navigation state, and repeatedly generate, evaluate, filter and reconstruct subsequent space observation configurations based on the updated satellite navigation state to form a mission-driven closed-loop space observation control.

[0098] The satellite navigation receiver obtains the original array samples through the sampling module. In addition, the satellite tracking and basic observation module maintains tracking of each satellite code, carrier, and Doppler and outputs the tracking quality. The sampling module also generates the mission state based on upper-layer application requirements, fixed solution state, integrity state, interference state, or array model uncertainty. This forms the navigation state, covariance, array spatial manifold, continuity state, and residual risk budget. The candidate spatial observation configuration generation module generates weight vectors, weight matrices, beam sets, subarray combinations, and related resource configurations or configuration paths. The mission observation value evaluation module and the continuity and integrity constraint module calculate the mission observation value based on the current mission and eliminate candidates that do not meet the safety conditions. The configuration decision module selects the target configuration, and the spatial observation reconstruction execution module loads it into the real receiving link. The reconstructed observations are used to update the navigation state and feed back to the next control cycle.

[0099] In this embodiment, the system can dynamically adjust the spatial observation configuration according to real-time task requirements and navigation status, effectively solving the problem of lack of dynamic feedback between the front-end and back-end navigation tasks. Compared with traditional systems that only focus on single indicators such as signal-to-interference-plus-noise ratio, this application ensures a high degree of matching between the spatial observation configuration and the navigation task objective by calculating the value of task-related observations and screening multiple constraints, significantly improving the system's flexibility and accuracy. For example, in high-precision positioning tasks, the system can prioritize configurations that are conducive to improving positioning accuracy; in anti-interference tasks, it can prioritize configurations with strong interference suppression capabilities, thereby achieving adaptive optimization for different navigation tasks.

[0100] In practical applications, this system can continuously monitor changes in navigation status and mission requirements, and adjust space observation configurations in a timely manner to ensure that navigation performance is always optimal. This dynamic closed-loop control mechanism not only improves the robustness of the navigation system but also enhances its adaptability to complex electromagnetic environments, providing reliable technical support for high-precision satellite navigation applications.

[0101] In one specific implementation, candidate spatial configurations are generated within a neighborhood centered on the current digital beamforming weights, satisfying constraints such as unity gain, weight norm, analog phase shift quantization level, or subarray switching. For each candidate spatial observation configuration, the receiver uses the current array manifold model to predict the complex responses of each satellite, further forming the carrier-to-noise ratio, carrier phase increment, observation noise covariance, state Jacobian, and integrity risk proxy quantities under the candidate spatial observation configuration. Candidate evaluation can be completed either within a single epoch or through finite-domain predictions of attitude and satellite line-of-sight changes over multiple future control cycles.

[0102] Configuration decisions employ a combination of hard constraints and soft objectives. Key satellite response lower bounds, carrier continuity, hardware executability, and integrity risk upper limits serve as hard constraints; mission information gain, residual interference, configuration changes, additional relevant resources, and power consumption are considered soft costs within the overall objective. When a candidate generated by a learning model, heuristic algorithm, or numerical optimizer fails to meet the hard constraints, the system either discards it or replaces it with the nearest executable configuration via a safe projection unit.

[0103] The system also includes a continuity management module, which is used to generate co-source complex observations of the current configuration and candidate spatial observation configurations before the target spatial observation configuration is submitted, estimate the spatial phase changes introduced by configuration changes, and decide whether to submit, maintain, reduce the change step size or insert an intermediate configuration based on the estimation quality.

[0104] The task observation value evaluation module selects different evaluation functions based on the current task, resulting in different ranking results for the same candidate spatial observation configuration under different task states. The configuration decision module includes a safe projection or feasible region projection unit, used to project or replace the candidate spatial observation configuration generated by the optimization algorithm or learning model with an executable spatial observation configuration that meets predetermined physical and integrity constraints.

[0105] Apply the above methods or systems to specific scenarios.

[0106] Example 1: Task-Driven Space Reconstruction for RTK Fixed Solution Preservation In the vehicle RTK receiver, the multi-element array employs adaptive anti-jamming weights. The system detects that it is currently in a fixed-solution state and sets the task status to "fixed-solution preservation priority." The candidate generation module then uses the current anti-jamming weights... Generate multiple neighborhood candidates, for example, , Let L represent the anti-interference weight of the Lth neighboring candidate. For each candidate, the residual interference power is calculated, and the complex response amplitude, array-induced phase increment, and corresponding carrier continuity risk of the key satellite are predicted. At the same time, the floating-point ambiguity covariance surrogate quantity is calculated based on the predicted carrier observation covariance.

[0107] The system first eliminates those that could cause any critical satellite Alternatively, for candidates with phase transfer confidence below a threshold, a configuration that balances anti-interference and ambiguity covariance is selected from the remaining candidates. Before switching configurations, the same-source candidate measurement branch is activated to estimate the relative spatial phase between the current weight and the candidate weights. After verification, the new weights are submitted at the coherent integration boundary. If direct switching does not meet the conditions, the weight change is decomposed into several intermediate configurations and executed step by step.

[0108] This embodiment transforms the "anti-interference weight update" from a simple power optimization process into an observation reconstruction process driven by the RTK task.

[0109] Example 2: Information Augmentation Reconstruction for Pose Estimation In multi-antenna or array attitude navigation, the mission state is set to "attitude observability enhancement". The system calculates the attitude parameters under candidate spatial observation configurations based on the current attitude estimate and the array manifold model. Valid Jacobian: (31) in, Indicates space observation configuration Next satellite Observations on attitude parameters The Jacobian matrix is ​​used to measure the sensitivity of observations to attitude changes in this configuration; Indicates space observation configuration Next satellite The observation function, which takes the attitude parameters Mapped to observables, attitude changes are achieved by altering the array's incident direction relative to the satellite. This, in turn, changes the spatial response. And it acts on observation; The attitude parameters to be estimated can be Euler angles, quaternions, or rotation vectors; This represents taking the partial derivative with respect to the attitude parameters. For multiple satellites, the partial derivatives of each satellite's parameters are... Stacking them row by row yields the unified Jacobian matrix. The minimum singular value or the minimum eigenvalue of the corresponding Fisher information matrix represents the amount of information in the weakest observable direction of the attitude.

[0110] The evaluation module maximizes the minimum singular value of the joint Jacobian of multiple satellites or the minimum eigenvalue of the corresponding Fisher information matrix, while simultaneously constraining the carrier-to-noise ratio of the main navigation branch and the carrier continuity of key satellites. Therefore, the system can prioritize space observation configurations that are more sensitive to the current weakly observable attitude direction on the same array hardware.

[0111] Example 3: Separability Reconstruction for Deception or Anomaly Detection When the anomaly detection module detects multiple satellite observations sharing a common direction of arrival, exhibiting anomalous correlation, or showing increased residuals, the mission status switches to "enhanced anomaly separability." The system generates multiple spatial projection candidates and predicts the mean difference or statistical distance between the normal satellite model and the anomaly source model under different candidate spatial observation configurations. For example: (32) in, Indicates the configuration of space observation The separability between the normal hypothesis and the abnormal hypothesis is expressed as a weighted quadratic form of the difference between the observed means of the two hypotheses, i.e., the square of the Mahalanobis distance. This is the mean vector of observation statistics under the anomalous assumption (e.g., the existence of deceptive signals or anomalous arrival directions); This is the mean vector of the observed statistics under the normal assumption. The covariance matrix of the observation statistics can be determined by the spatial covariance of the interference plus noise according to equation (9) or its equivalent form, and is used to perform weighted whitening of the mean difference; for The inverse matrix; This indicates the conjugate transpose. The larger the value, the easier it is to distinguish between the two hypotheses under this configuration, that is, the stronger the anomaly separability.

[0112] Under the premise of satisfying normal navigation tracking and continuity constraints, choose to increase The configuration is designed to proactively improve the spatial distinguishability between anomalous and normal hypotheses.

[0113] Example 4: Dual Control for Array Manifold Self-calibration When the uncertainty of the array model increases, the mission state can simultaneously incorporate "navigation performance" and "array calibration information" into the objective function: (33) in, Indicates space observation configuration The comprehensive objective function value; Configuration for space observation The mission-related observation value of the current navigation task can be calculated according to the information matrix scalarization criteria of Equations (12) to (14); Configuration for space observation The amount of calibration information for unknown parameters of the array manifold is used to characterize the contribution of this configuration to reducing array model uncertainty; Configuration for space observation The corresponding continuity risk or integrity risk proxy amount is consistent with the meaning of the same term in equation (25); To calibrate the non-negative weighting coefficient of the information content, this coefficient can be increased when the uncertainty of the array model increases; is the non-negative weighting coefficient of the risk term. Equation (33) is the specific form of Equation (25) under the dual objectives of navigation and array calibration.

[0114] The system selects an information configuration that maintains current navigation performance while providing additional stimulation to unknown array parameters. After obtaining new observations, the array manifold parameters are updated, and then a new candidate spatial observation configuration for the next cycle is generated, achieving closed-loop coordination between navigation and calibration.

[0115] Example 5: Multi-task priority switching The receiver simultaneously performs positioning, anti-interference, integrity, and carrier continuity monitoring. When there is no strong interference and the fixed solution is stable, high-precision positioning information is prioritized; when interference is detected to be increasing, the anti-interference weight is increased; when the integrity protection level approaches the threshold, integrity constraints are upgraded to hard constraints; when the risk of carrier continuity increases, large weight changes are frozen or an intermediate path is adopted. Therefore, the same array does not need to configure a completely independent fixed processing chain for each task, but rather the spatial observation reconstruction strategy is changed by altering the task state.

[0116] Example 6: Path Reconstruction Based on Finite-Time Domain Prediction For highly dynamic platforms, the system predicts changes in platform attitude and satellite line-of-sight over multiple decision cycles. Candidates are no longer single configurations, but rather a sequence of configurations. The system calculates the predicted mission information, minimum critical satellite response, and cumulative continuity risk for each sequence, selects the optimal sequence, executes only the first segment, and performs rolling replanning in the next cycle. This implementation avoids instantaneous greedy configurations that could lead the system into unrecoverable or low-observable regions in the future.

[0117] The above methods can be implemented using digital signal processors, field-programmable gate arrays, graphics processors, microprocessors, application-specific integrated circuits (ASICs), or combinations thereof. Multi-element receiving channels preferably share a reference clock, and channel amplitude, phase, delay, and array manifold parameters are obtained through factory calibration or online calibration. For analog arrays or hybrid beam arrays, the continuous weights output by the configuration decision module can be further quantized into discrete control codes for phase shifters and gainers, and the key satellite response, continuity risk, and mission observation value of the quantized configuration are recalculated before submission.

[0118] In multi-frequency, multi-constellation receivers, the mission state and navigation state can be shared for different frequencies, while maintaining the frequency-related array manifold, hardware constraints, and phase continuity states separately. For integrated navigation systems, the states and covariances of the inertial measurement unit, visual odometry, or wheel velocity meter can serve as additional inputs to the state and model modules, but the space observation reconstruction of this invention is still achieved by actually changing the space observation mapping of the satellite navigation receiver link.

[0119] In summary, compared with existing technologies, it has the following beneficial effects: 1. Transform spatial weights, weight matrices, or equivalent spatial configurations from simple filter parameters into observation control variables that can be driven by navigation tasks.

[0120] 2. Enables array space processing targets to be directly associated with backend tasks such as position, attitude, integer ambiguity, anomaly detection, integrity, or array calibration.

[0121] 3. By using critical satellite response and carrier continuity constraints, the likelihood of high-value but high-risk space configurations being directly executed is reduced.

[0122] 4. Through closed-loop state feedback, the next space observation reconstruction can utilize the real observation results after the previous reconstruction, rather than relying solely on fixed priors.

[0123] 5. Supports single-point configuration selection and path-based configuration refactoring, thus balancing the value of the target configuration with the security during the process of reaching the target configuration.

[0124] 6. It is compatible with existing GNSS tracking and high-precision positioning backends, and can evaluate candidate space observation configurations using auxiliary space observation branches in addition to the main navigation branch.

[0125] 7. Provide an explicit physical security interface for intelligent PNTs based on model predictive control, information optimization, or learning strategies, so that candidate strategies output by the learning module can only be applied to the receiving link after being configured with executable spatial observations and integrity constraints.

[0126] This application provides a satellite navigation receiver, including a processor and a memory; The memory is used to store computer programs; the processor is used to cause the satellite navigation receiver to execute the above-described task-driven satellite navigation control method when the computer program is executed. The receiver also includes a multi-element antenna and multiple synchronous radio frequency or intermediate frequency receiving channels.

[0127] The receiver also includes a high-precision positioning module, which is an RTK, network RTK, PPP, or PPP-AR module, and feeds back at least one of the fixed solution state, floating-point ambiguity covariance, carrier continuity state, or positioning integrity state as input to the task state module or state and model module.

[0128] The receiver has at least one auxiliary space observation branch in addition to the main navigation observation branch. The auxiliary space observation branch is used to evaluate candidate space observation configurations, estimate space phase changes, perform array calibration or anomaly detection, and trigger the reconstruction of the space observation configuration of the main navigation observation branch when predetermined conditions are met.

[0129] This application provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it implements the task-driven satellite navigation control method described above.

[0130] In this embodiment, the beneficial effects of the satellite navigation receiver and the computer-readable storage medium are similar to those of the task-driven satellite navigation control method described above, and will not be repeated here.

[0131] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0132] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A mission-driven satellite navigation control method, characterized in that, include: Acquire satellite navigation observations, including the mission status of the current navigation processing target; Based on current satellite navigation observations, array space manifold information, and current space observation configurations, multiple candidate space observation configurations are generated. For each candidate spatial observation configuration, the mission-related observation value is calculated based on the mission status. The mission-related observation value characterizes the measurement capability of the navigation observation formed by the candidate spatial observation configuration after being applied to the multi-element array for the current mission target. Candidate spatial observation configurations are selected based on preset constraints. The target spatial observation configuration is determined from the filtered candidate spatial observation configurations by solving the objective function; The actual target space observation configuration is executed, and the reconstructed space observation configuration is loaded into the satellite navigation receiving link to change the space observation mapping from the multi-element array input to the satellite navigation measurement output; New satellite navigation observations are generated under the modified space observation mapping, the satellite navigation status is updated, and the subsequent space observation configurations are repeatedly generated, evaluated, filtered and reconstructed based on the updated satellite navigation status to form a mission-driven closed-loop space observation control.

2. The mission-driven satellite navigation control method as described in claim 1, characterized in that, Status information is generated based on current and historical satellite navigation observations. This status information is as follows: ； in, For navigation or attitude state estimation, To estimate covariance or equivalent uncertainty, For array manifold or environment model parameters, This is a carrier phase continuity related state. In a state of integrity, This represents a remaining risk budget or other constraint state; Generate a candidate spatial observation configuration set based on task status and status information. ,in, This represents the Lth candidate spatial observation configuration in the candidate spatial observation configuration set; The candidate space observation configuration within the control period t is as follows: ； in, For spatial weight vectors, For the enabled beam or projection set, Select a state for the array element. For the allocation of relevant observation resources, These are control parameters related to phase reference, time alignment, or calibration.

3. The mission-driven satellite navigation control method as described in claim 1, characterized in that, The mission-related observation value is calculated based on at least one of the following data: the rank or singular value of the observed Jacobian, Fisher information, equivalent Fisher information, predicted posterior covariance, conditional mutual information, state entropy reduction, floating-point ambiguity covariance, ambiguity surrogate quantity, fixed solution risk surrogate quantity, hypothesis separability, array calibration parameter information, or mission-related satellite joint observation quality.

4. The mission-driven satellite navigation control method as described in claim 1, characterized in that, When the state to be estimated includes both target and non-target states, the task-related observation value is calculated based on the equivalent information matrix after eliminating the influence of non-target states, the marginal posterior covariance, or the target state conditional information.

5. The mission-driven satellite navigation control method as described in claim 2, characterized in that, The preset constraints include at least one of the following: critical satellite availability constraints, carrier phase continuity constraints, interference suppression constraints, navigation integrity constraints, array model uncertainty constraints, and space observation configuration change constraints. The key satellite availability constraints: ； in, Represents a spatial weight vector; This indicates the incident direction of the satellite signal arriving at the array within the control period t; This represents the array space manifold of satellite s within period t; For a key satellite collection, This represents the minimum spatial complex response amplitude threshold. It is the vector norm; The carrier phase continuity constraint: ； ； ； in, For phase sensitivity, To continuously increase the error probability of the carrier, Risk of cycle jump; This indicates the upper limit of the allowable phase sensitivity. This represents the upper limit of the allowable probability of continuous carrier error increase. This indicates the maximum allowable risk of cycle slips; The interference suppression constraint: ； in, Configure candidate space observations The output residual interference power is below. To the interference space covariance matrix, The upper limit of the allowable residual interference power is set at 100%. The trace of the matrix; The navigation integrity constraint: ； in, Risk of misleading information This represents the maximum permissible risk level for dangerous or misleading information. The array model uncertainty constraints are as follows: ； in, As an indicator of model uncertainty, This represents the upper limit allowed for the model's uncertainty index; The constraints on the changes in the space observation configuration are as follows: ； in, This represents a measure of configuration changes. This indicates the candidate space observation configuration within the control period t-1. Configure the allowed upper limit for change metrics.

6. The mission-driven satellite navigation control method as described in claim 1, characterized in that, The objective function is the mission-related observation value, or a comprehensive function consisting of the mission-related observation value and residual interference cost, continuity risk, integrity risk, and configuration change cost. The target space observation configuration is determined in the following way: among the selected candidate space observation configurations, the candidate space observation configuration that maximizes the objective function is selected as the target space observation configuration.

7. The mission-driven satellite navigation control method as described in claim 1, characterized in that, When actually executing the target space observation configuration, if switching directly from the current space observation configuration to the target space observation configuration does not meet the predetermined safety conditions, at least one intermediate space observation configuration is generated to form a multi-segment configuration path from the current space observation configuration to the target space observation configuration, and the adjacent configurations in the configuration path meet the predetermined safety conditions, wherein the predetermined safety conditions include at least one of the preset carrier continuity conditions or key satellite availability conditions.

8. The mission-driven satellite navigation control method as described in claim 1, characterized in that, The loading of the space observation configuration includes at least one of the following: updating digital beamforming weights, updating space-time filtering coefficients, updating analog or radio frequency phase shifters, updating controllable gainers, enabling or disabling array elements, reorganizing subarrays, establishing multiple parallel or time-division space projection branches, changing the reference beam or auxiliary observation beam for a specific satellite, and adjusting the resource mapping between the correlator and the space projection.

9. A mission-driven satellite navigation control system, characterized in that, include: The sampling module is used to acquire satellite navigation observations, which include the task status of the current navigation processing target; The candidate space observation configuration generation module is used to generate multiple candidate space observation configurations based on the current satellite navigation observations, array space manifold information, and the current space observation configuration. The mission observation value evaluation module is used to calculate the mission-related observation value for each candidate spatial observation configuration based on the mission status. The mission-related observation value characterizes the measurement capability of the navigation observation formed by the candidate spatial observation configuration after being applied to the multi-element array for the current mission target. The continuity and integrity constraint module is used to filter candidate spatial observation configurations based on preset constraint conditions; The configuration decision module is used to determine the target spatial observation configuration from the filtered candidate spatial observation configurations by solving the objective function; The space observation reconstruction execution module is used to actually execute the target space observation configuration. After the space observation configuration is reconstructed, it is loaded into the satellite navigation receiving link to change the space observation mapping from the multi-element array input to the satellite navigation measurement output. The navigation status update module is used to generate new satellite navigation observations under the changed space observation mapping, update the satellite navigation status, and repeatedly generate, evaluate, filter and reconstruct subsequent space observation configurations based on the updated satellite navigation status, so as to form a mission-driven closed-loop space observation control.

10. A satellite navigation receiver, characterized in that, Including processor and memory; The memory is used to store computer programs; The processor is configured to, when executing the computer program, cause the satellite navigation receiver to perform the task-driven satellite navigation control method as described in any one of claims 1 to 8.

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