Method and system for autonomous integrity and information control of component PNT elastic terminals

Abstract

The present invention discloses a method and system for autonomous integrity and information control of component PNT elastic terminals. The method first performs a fusion solution on multi-source PNT information based on Bayesian estimation theory; secondly, it constructs system-level, subsystem-level, and sensor-level fault monitoring models using information factors, local optimization domain global optimization, and nonlinear optimization methods, respectively, to decouple and isolate faults and / or anomalies in the system; then, it verifies, calibrates, and reconstructs the isolated faults and / or anomalies, and dynamically adjusts and controls the use of faulty and / or abnormal components and their output information; finally, it calculates the autonomous integrity protection level based on the integrity risk required by the system, and completes autonomous integrity alarms. The present invention improves the integrity and reliability of the component PNT terminal system by monitoring, isolating, verifying, calibrating, and reconstructing faults and / or anomalies in the component PNT elastic terminal system, and coordinating autonomous integrity alarms and dynamic information adjustment control.

Description

Technical Field

[0001] The present invention relates to the technical field of autonomous integrity and information control of component PNT terminals, and in particular to a method and system for autonomous integrity and information control of component PNT elastic terminals. Background Art

[0002] Building a comprehensive PNT (positioning, navigation, and timing) system centered around the BeiDou satellite navigation system is a major national strategy. With the widespread deployment of my country's BeiDou satellite navigation system, autonomous integrity monitoring of integrated PNT application terminal systems will be the foundation for achieving resilient PNT and an effective guarantee for secure and reliable terminal system applications.

[0003] While countries around the world attach great importance to the development of resilient PNT technology and are researching related key technologies, research on terminal system integrity for specific applications is relatively lagging. To meet the demands for accurate, continuous, and reliable positioning and navigation of carriers in typical scenarios such as deep space, airborne, near-Earth, urban, indoor, offshore, and underwater, the support of a comprehensive national PNT infrastructure is required. Furthermore, PNT terminal systems must provide accurate, continuous, reliable, and secure PNT service information. Different application scenarios require PNT terminals to be able to integrate PNT sensors with varying performance from different manufacturers. This inevitably necessitates modularization of PNT sensors and the terminal system's ability to provide autonomous integrity monitoring. Component PNT terminals feature redundant observations, and any component failure or anomaly will impact the performance of the PNT terminal's application services. Therefore, based on the component PNT elastic integrated terminal architecture, real-time monitoring of faults / anomalies and dynamic regulation of PNT components involved in PNT terminal solutions and their output information according to the hierarchical structure between sensor components, PNT signal sources and PNT terminals are the key to ensuring the safety and reliability of PNT terminals. In addition, the autonomous integrity and information control methods of component PNT terminals are indispensable hot topics for building a comprehensive PNT framework. Summary of the Invention

[0004] The present invention provides a method and system for autonomous integrity and information control of componentized PNT terminals to solve the problem of dynamic control of elastic integrated information of PNT terminals in the event of PNT component failure and / or abnormality, so as to enable PNT terminals to have high reliability and high anti-interference capabilities.

[0005] In a first aspect, the present invention provides a method for autonomous integrity and information control of a component PNT resilient terminal, comprising the following steps:

[0006] Step 1: Based on the Bayesian estimation method, the information factor of each component PNT is calculated. By minimizing the information factor of all components PNT, a flexible fusion solution of multi-source PNT information is achieved.

[0007] Step 2: Integrate the information factors provided by each PNT information source to build a system-level fault anomaly monitoring model;

[0008] If the system-level fault and anomaly monitoring model detects a fault and / or anomaly, the subsystem-level fault and anomaly monitoring model is started; otherwise, the subsystem-level fault and anomaly monitoring model is not started;

[0009] Step 3: Based on local and global optimization methods, a subsystem model containing high-trust PNT components is constructed. Using consistency detection principles, a subsystem-level fault anomaly monitoring model is constructed.

[0010] If the subsystem-level fault and anomaly monitoring model detects a fault and / or anomaly, the PNT signal source of the component that is elastically connected to the PNT terminal is regulated and the sensor-level fault and anomaly monitoring model is activated; otherwise, the sensor-level fault and anomaly monitoring model is not activated;

[0011] Step 4: For PNT components with different redundancy characteristics, motion constraints and sliding window calculations are introduced to build a sensor-level fault anomaly monitoring model.

[0012] If the sensor-level fault and anomaly monitoring model detects a fault and / or anomaly, information regulation is performed on the sensor components involved in the PNT signal source solution. Otherwise, information regulation is not performed on the sensor components involved in the PNT signal source solution.

[0013] Step 5: Integrate the multi-level fault and / or anomaly monitoring results and initiate real-time verification, calibration, and reconstruction and restart of the corresponding model for the isolated fault and / or anomaly PNT signal sources and sensor components;

[0014] The real-time verification model verifies the isolated PNT signal source and sensor components. If the verification passes, the corresponding PNT signal source and sensor component information involved in the solution is dynamically adjusted. Otherwise, the calibration model is started.

[0015] The calibration model calibrates the isolated PNT signal source and sensor components. After calibration, the verification model is restarted. If the verification passes, the corresponding PNT signal source and sensor component information involved in the solution is dynamically adjusted. Otherwise, the reconstruction and restart model is started.

[0016] The reconstruction and restart model reconstructs the solution model of the isolated PNT signal source and restarts the isolated sensor components. After the reconstruction and restart, the verification model pair is restarted. If the verification passes, the information of the corresponding PNT signal source and sensor components participating in the solution is dynamically adjusted. Otherwise, the isolated PNT signal source and sensor components are set to failure mode and enter periodic recovery verification.

[0017] Step 6: Based on the system integrity risk requirements and the prior failure probability of each PNT signal source, dynamically allocate the integrity risk according to the combination of subsystems. Combined with the subsystem failure and / or anomaly monitoring thresholds, calculate the protection level of the PNT terminal and implement autonomous integrity monitoring of the component PNT terminals.

[0018] Furthermore, the step 1 includes:

[0019] Step 11): Based on the measurement information z of the PNT component at time k k , calculate the information factor f of PNT component a a for

[0020]

[0021] In the formula, h(x k ) is the measurement equation at time k, x k is the state of the PNT component at time k, Σ is the measurement noise variance matrix;

[0022] Step 12): Based on the Bayesian estimation method, the Gauss-Newton algorithm is used to solve the navigation state that satisfies the minimum PNT information factor of all components, realizing the flexible fusion solution of multi-source PNT information.

[0023] Furthermore, the step 2 specifically includes:

[0024] Step 21): Integrate the information factors provided by each PNT information source to construct the system-level fault and / or anomaly monitoring statistic D sys for

[0025]

[0026] Where N is the number of PNT sources, and A is the number of PNT components contained in the PNT source;

[0027] Step 22): If system-level failure and / or abnormal monitoring statistics D sys Greater than the set threshold T sys , if there are faults and / or anomalies in the system, the subsystem-level fault anomaly monitoring model needs to be started; otherwise, the subsystem-level fault anomaly monitoring model will not be started.

[0028] Furthermore, the step 3 specifically includes:

[0029] Step 31): Based on the number of PNT signal sources N, assuming that the number of PNT signal sources that fail and / or are abnormal at the same time is F, calculate the number of subsystems C that include all combinations. n for

[0030]

[0031] Step 32): For each subsystem j, the standard deviation of the measurement residuals of all observations is used as the subsystem fault and / or abnormality monitoring statistic D sub,j for

[0032]

[0033] Where M is the number of observations, w m is the measurement residual vector corresponding to the mth observation;

[0034] Step 33): If there is only one subsystem j that satisfies the fault and / or abnormality monitoring statistic D sub,j Greater than the set threshold T sub , then the PNT signal source excluded by subsystem j is a faulty and / or abnormal signal source, otherwise the number of PNT signal sources with simultaneous faults and / or abnormalities is increased, and the subsystem fault and / or abnormality monitoring is re-executed;

[0035] Step 34) If the subsystem-level fault and anomaly monitoring model detects a fault and / or an abnormal signal source, the fault and / or abnormal signal source detected by the subsystem-level fault and anomaly monitoring model is isolated, the signal sources of the components involved in the PNT terminal calculation are regulated, and the sensor-level fault and anomaly monitoring model is activated; otherwise, the sensor-level fault and anomaly monitoring model is not activated.

[0036] Furthermore, the step 4 specifically includes:

[0037] Step 41): Introduce sliding window calculation to count the measurement values ​​R of sensor component s at all times within the sliding window s (t k )={r s (t k-p+1 ),...,r s (t k-1 ),r s (t k )}, forming the self-evaluation parameter D of the sensor component self for

[0038]

[0039] Where r s (t k ) represents t k The measured value of the sensor component at the moment, med(*) is the median function, and e is the exponential function f=e (x) ;

[0040] Step 42): If the PNT component is a non-redundant sensor component, the mutual evaluation parameter is not calculated; otherwise, the sensor component mutual evaluation parameter D is calculated using the Pearson coefficient. mutual for

[0041]

[0042] Where μ s is the measurement value R of sensor component s at all times within the sliding window s (t k )={r s (t k-p+1 ),...,r s (t k-1 ),r s (t k )}, σ s The measurement sequence R s (t k ), μ q is the measurement value R of the sensor component q at all times within the sliding window q (t k )={r q (t k-p+1 ),…,r q (t k-1 ),r q (t k )}, σ q The measurement sequence R q (t k )’s standard deviation;

[0043] Step 43): Integrate the self-evaluation parameters and mutual evaluation parameters of the sensor components to construct the sensor-level fault and / or anomaly monitoring statistic D sensor,s for

[0044]

[0045] Where α1 and α2 are adjustable weight factors, s is the sensor component being evaluated, and S is the number of redundant sensors;

[0046] Step 44): If there is a sensor level fault and / or abnormal monitoring statistic D sensor,s Greater than the set threshold T sensor , the sensor component s is a faulty and / or abnormal sensor component; otherwise, the sensor-level fault and anomaly monitoring model does not detect the fault;

[0047] Step 45): If the sensor-level fault and anomaly monitoring model detects a faulty and / or abnormal sensor component, information regulation is performed on the sensor components participating in the PNT signal source solution to isolate the faulty and / or abnormal sensor components; otherwise, information regulation is not performed on the sensor components participating in the PNT signal source solution.

[0048] Furthermore, the step 5 specifically includes:

[0049] Step 51): Build a real-time verification model to verify the isolated PNT signal source and sensor components. If the verification passes, dynamically adjust and solve the corresponding PNT signal source and sensor component information. Otherwise, start the calibration model.

[0050] Step 52): Construct a calibration model to calibrate the isolated PNT signal source and sensor components. After calibration, restart the verification model. If the verification passes, dynamically adjust the information of the corresponding PNT signal source and sensor components involved in the solution. Otherwise, start the reconstruction and restart model.

[0051] Step 53): Reconstruct the solution model of the isolated PNT signal source and restart the isolated sensor component. After the reconstruction and restart, restart the verification model pair. If the verification passes, dynamically adjust the information of the corresponding PNT signal source and sensor component involved in the solution. Otherwise, set the isolated PNT signal source and sensor component to failure mode and enter periodic recovery verification.

[0052] Furthermore, the step 6 specifically includes:

[0053] Step 61): Based on the system integrity risk requirements and the prior failure probability of each PNT signal source, the integrity risk is dynamically allocated according to the subsystem combination;

[0054] Step 62): According to the assigned integrity risk P risk,j and subsystem fault and / or abnormality monitoring threshold T sub , calculate the protection level PL of the PNT terminal as

[0055]

[0056]

[0057] Where, slope j The projection slope from the measurement domain to the position domain is calculated by converting the threshold in the measurement domain to the position domain. Specifically, it can be calculated by calculating the square of the mean position error The noncentral parameter λ of the noncentral chi-square distribution obeyed by the test quantity j The ratio of K md is the integrity risk factor calculated by the inverse probability function, σ j is the standard deviation of position error;

[0058] Step 63): If the protection level is greater than the alarm limit required by the system, a navigation system integrity loss alarm is issued to the user within the specified alarm time, reminding the user that the positioning information provided by the navigation system at the current moment is unreliable; otherwise, no integrity loss alarm is issued.

[0059] In a second aspect, the present invention also provides a system for autonomous integrity and information control of component PNT elastic terminals, which applies the method for autonomous integrity and information control of component PNT elastic terminals as described in any of the above embodiments to realize autonomous integrity and information control of componentized PNT terminals, thereby enabling the terminal system to have elastic capabilities.

[0060] Compared with the prior art, the present invention has the following advantages:

[0061] This invention addresses faults and / or anomalies in component PNT terminal systems, PNT signal sources, and sensor components by decoupling and isolating them layer by layer. Through verification, calibration, and reconstruction of isolated PNT signal sources and sensor components, dynamic adjustment, flexible access, removal, and plug-and-play of PNT component information are achieved. Furthermore, the protection level of the PNT terminal system is calculated, forming a componentized PNT terminal autonomous integrity and information control system. This invention improves the anti-interference capability of the PNT terminal system, ensuring that carriers can obtain highly accurate and reliable PNT service information in complex application environments, thereby resolving the problem of existing PNT terminal systems lacking the flexibility to handle system faults and / or anomalies. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1 Schematic diagram of the component PNT terminal autonomous integrity and information control method in an embodiment of the present invention.

[0063] Figure 2 Schematic diagram of the PNT terminal information control mechanism and strategy in an embodiment of the present invention. DETAILED DESCRIPTION

[0064] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0065] The embodiment of the present invention provides a method for controlling the autonomous integrity and information of a component PNT elastic terminal, based on the following Figure 1 and Figure 2As shown in the schematic diagram, the autonomous integrity and information control system of the component PNT terminal mainly includes three core parts: PNT components, autonomous integrity monitoring and information control mechanism, and self-protection integrity protection level calculation and alarm. Among them, the PNT component, as the input of the PNT elastic terminal, can be divided into high-trust PNT components and extended PNT components; the autonomous integrity monitoring and information control mechanism mainly includes the system-level fault anomaly monitoring model, the subsystem fault anomaly monitoring model and the sensor-level fault anomaly monitoring model, and realizes PNT information control through monitoring, verification, calibration and reconstruction restart model; the autonomous integrity protection level calculation and alarm part mainly compares the calculated protection level of the PNT terminal system with the alarm limit required by the system to realize integrity risk alarm.

[0066] The embodiment of the present invention provides a method for autonomous integrity and information control of component PNT elastic terminals, such as Figure 1 and Figure 2 As shown, the following steps are included:

[0067] Step 1: Based on Bayesian estimation theory and methods, calculate the information factor of each component PNT and achieve elastic fusion solution of multi-source PNT information by minimizing the information factor of all components PNT;

[0068] In step 1, the specific steps of elastic fusion calculation of multi-source PNT information include:

[0069] Step 11): Based on the measurement information z of the PNT component at time k k , calculate the information factor f of PNT component a a for

[0070]

[0071] In the formula, h(x k ) is the measurement equation at time k, x k is the state of the PNT component at time k, Σ is the measurement noise variance matrix;

[0072] Step 12): Based on the Bayesian estimation theory and method, the Gauss-Newton algorithm is used to solve the navigation state that satisfies the minimum PNT information factor of all components, realizing the flexible fusion solution of multi-source PNT information.

[0073] Step 2: Integrate the information factors provided by each PNT information source to build a system-level fault anomaly monitoring model;

[0074] In step 2, the specific steps of the system-level fault anomaly monitoring model monitoring include:

[0075] Step 21): Integrate the information factors provided by each PNT information source to construct the system-level fault and / or anomaly monitoring statistic Dsys for

[0076]

[0077] Where N is the number of PNT sources, and A is the number of PNT components contained in the PNT source;

[0078] A PNT source may contain multiple PNT components. The information factor of a PNT source is the product of the information factors of all components. The detection statistic D sys is the sum of all PNT source factors.

[0079] Step 22): If the system-level fault / abnormal monitoring statistics D sys Greater than the set threshold T sys (This threshold is related to the system's prior failure probability and can be obtained by querying the chi-square distribution critical value table). If there are faults and / or anomalies in the system, the subsystem-level fault anomaly monitoring model needs to be activated; otherwise, the subsystem-level fault anomaly monitoring model will not be activated.

[0080] Step 3: Based on local and global optimization methods, a subsystem model containing high-trust PNT components is constructed. Using consistency detection principles, a subsystem-level fault anomaly monitoring model is constructed.

[0081] In step 3, the specific steps of the subsystem-level fault anomaly monitoring model are as follows:

[0082] Step 31): Based on the number of PNT signal sources N, assuming that the number of PNT signal sources that fail and / or are abnormal at the same time is F, calculate the number of subsystems C that include all combinations. n for

[0083]

[0084] Step 32): For each subsystem j, the standard deviation of the measurement residual w of all observations M is used as the subsystem fault and / or abnormality monitoring statistic D sub,j for

[0085]

[0086] Where M is the number of observations, w m is the measurement residual vector corresponding to the mth observation;

[0087] Step 33): If there is only one subsystem j that satisfies the fault and / or abnormality monitoring statistic D sub,j Greater than the set threshold T sub(This threshold is related to the prior failure probability of the PNT signal sources that make up the subsystem). The PNT signal sources excluded by subsystem j are faulty and / or abnormal signal sources. Otherwise, the number of PNT signal sources that are simultaneously faulty and / or abnormal is increased, and the subsystem fault and / or abnormality monitoring is re-executed.

[0088] Step 34) If the subsystem-level fault and anomaly monitoring model detects a fault and / or an abnormal signal source, the fault and / or abnormal signal source detected by the subsystem-level fault and anomaly monitoring model is isolated, the signal sources of the components participating in the terminal PNT calculation are regulated, and the sensor-level fault and anomaly monitoring model is started; otherwise, the sensor-level fault and anomaly monitoring model is not started.

[0089] Step 4: For PNT components with different redundancy characteristics, motion constraints and sliding window calculations are introduced to build a sensor-level fault anomaly monitoring model.

[0090] In step 4, the specific steps of the sensor-level fault anomaly monitoring model are as follows:

[0091] Step 41): Introduce sliding window calculation to count the measurement values ​​R of sensor component s at all times within the sliding window s (t k )={r s (t k-p+1 ),...,r s (t k-1 ),r s (t k )}, forming the self-evaluation parameter D of the sensor component self for

[0092]

[0093] Where r s (t k ) represents t k The measured value of the sensor component at the moment, med(*) is the median function, and e is the exponential function f=e (x) ;

[0094] Step 42): If the PNT component is a non-redundant sensor component, the mutual evaluation parameter is not calculated; otherwise, the sensor component mutual evaluation parameter D is calculated using the Pearson coefficient. mutual for

[0095]

[0096] Where μ s is the measurement value R of sensor component s at all times within the sliding window s (t k )={r s (t k-p+1 ),...,rs (t k-1 ),r s (t k )}, σ s The measurement sequence R s (t k ), μ q is the measurement value R of the sensor component q at all times within the sliding window q (t k )={r q (t k-p+1 ),...,r q (t k-1 ),r q (t k )}, σ q The measurement sequence R q (t k )’s standard deviation;

[0097] Step 43): Integrate the self-evaluation parameters and mutual evaluation parameters of the sensor components to construct the sensor-level fault and / or anomaly monitoring statistic D sensor,s for

[0098]

[0099] Where α1 and α2 are adjustable weight factors, s is the sensor component being evaluated, and S is the number of redundant sensors. Self-evaluation only calculates the current sensor component s, while mutual evaluation traverses all sensor components in S except the current sensor component s.

[0100] Step 44): If there is a sensor level fault and / or abnormal monitoring statistic D sensor,s Greater than the set threshold T sensor (This threshold is related to the prior failure probability of the sensor), the sensor component s is a faulty / abnormal sensor component; otherwise, the sensor-level fault anomaly monitoring model does not detect the fault;

[0101] Step 45): If the sensor-level fault and anomaly monitoring model detects a faulty and / or abnormal sensor component, information regulation is performed on the sensor components participating in the PNT signal source solution to isolate the faulty and / or abnormal sensor components; otherwise, information regulation is not performed on the sensor components participating in the PNT signal source solution.

[0102] Step 5: Integrate the multi-level fault and / or anomaly monitoring results and initiate real-time verification, calibration, and reconstruction and restart of the corresponding model for the isolated fault and / or anomaly PNT signal sources and sensor components;

[0103] In step 5, the specific steps of verification, calibration, and reconstruction / restart are:

[0104] Step 51): Build a real-time verification model to verify the isolated PNT signal source and sensor components. If the verification passes, dynamically adjust and solve the corresponding PNT signal source and sensor component information. Otherwise, start the calibration model.

[0105] Step 52): Construct a calibration model to calibrate the isolated PNT signal source and sensor components. After calibration, restart the verification model. If the verification passes, dynamically adjust the information of the corresponding PNT signal source and sensor components involved in the solution. Otherwise, start the reconstruction and restart model.

[0106] Step 53): Reconstruct the solution model of the isolated PNT signal source and restart the isolated sensor component. After the reconstruction and restart, restart the verification model pair. If the verification passes, dynamically adjust the information of the corresponding PNT signal source and sensor component involved in the solution. Otherwise, set the isolated PNT signal source and sensor component to failure mode and enter periodic recovery verification.

[0107] Step 6: Based on the system integrity risk requirements and the prior failure probability of each PNT signal source, the integrity risk is dynamically allocated according to the subsystem combination. Combined with the subsystem failure and / or anomaly monitoring thresholds, the protection level of the PNT terminal is calculated to achieve autonomous integrity monitoring of the component PNT terminal.

[0108] In step 6, the specific steps for calculating the PNT terminal protection level are:

[0109] Step 61): Based on the system integrity risk requirements and the prior failure probability of each PNT signal source, the integrity risk is dynamically allocated according to the subsystem combination;

[0110] Step 62): According to the assigned integrity risk P risk,j and subsystem fault and / or abnormality monitoring threshold T sub , calculate the protection level PL of the PNT terminal as

[0111]

[0112]

[0113] Where, slope j The projection slope from the measurement domain to the position domain is calculated by converting the threshold in the measurement domain to the position domain. Specifically, it can be calculated by calculating the square of the mean position error The noncentral parameter λ of the noncentral chi-square distribution obeyed by the test quantity j The ratio of K md is the integrity risk factor calculated by the inverse probability function, σ jis the standard deviation of the position error. The subsystem-level fault detection metric is constructed from measurement residuals, so the threshold is set in the measurement domain and needs to be converted to the position domain using the projection slope. The projection slope is calculated as the ratio of the square of the position error caused by the fault / anomaly to the noncentral parameter of the noncentral chi-square distribution of the detection metric.

[0114] Step 63): If the protection level is greater than the alarm limit required by the system, a navigation system integrity loss alarm is issued to the user within the specified alarm time, reminding the user that the positioning information provided by the navigation system at the current moment is unreliable; otherwise, no integrity loss alarm is issued.

[0115] If the calculated protection level is greater than the alarm limit required by the system, the system integrity is lost, the positioning information provided by the navigation system is unreliable, and the user needs to be alerted within the specified time.

[0116] The method for autonomous integrity and information control of component PNT elastic terminals provided by the present invention first performs a fusion solution on multi-source PNT information based on Bayesian estimation theory; secondly, it respectively utilizes information factors, local optimization domain global optimization, and nonlinear optimization methods to construct system-level, subsystem-level, and sensor-level fault monitoring models to decouple and isolate faults and / or anomalies in the system; then, it performs verification, calibration, and reconstruction operations on the isolated faults and / or anomalies, and dynamically adjusts and controls the use of faulty and / or abnormal components and their output information; finally, it calculates the autonomous integrity protection level and completes the autonomous integrity alarm based on the integrity risk required by the system. The present invention improves the integrity and reliability of the component PNT terminal system by monitoring, isolating, verifying, calibrating, and reconstructing the faults and / or anomalies in the component PNT elastic terminal system, and coordinating autonomous integrity alarms and information dynamic adjustment control.

[0117] Based on the same inventive concept, the present invention also provides a system for autonomous integrity and information control of component PNT terminals that are flexible. The method for autonomous integrity and information control of component PNT terminals described in the above embodiment can be programmed and implemented, and the autonomous integrity and information control of component PNT terminals can be implemented using a computer processor or an embedded processor to form a component PNT terminal autonomous integrity and information control system, so that the terminal system has the ability to flexibly handle faults and / or anomalies.

[0118] The present invention addresses the information control problem of existing PNT terminal systems in the event of component failures and / or anomalies. It monitors and isolates faults and / or anomalies at each level of the PNT system, PNT signal source, and sensor components. Through verification, calibration, and reconstruction of isolated PNT signal sources and sensor components, the invention enables dynamic adjustment, flexible access, removal, and plug-and-play of PNT component information. Furthermore, the protection level of the PNT terminal system is calculated, forming a componentized PNT terminal autonomous integrity and information control system. This improves the anti-interference capability of the PNT terminal system and ensures that the carrier can obtain high-precision and high-reliability PNT service information in complex application environments.

[0119] Those skilled in the art will understand that all or part of the steps of implementing the above-mentioned method embodiments can be completed by hardware related to program instructions, and the aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it executes the steps of the above-mentioned method embodiments; and the aforementioned storage medium includes: mobile storage devices, read-only memory (ROM), random access memory (RAM), magnetic disks or optical disks, and other media that can store program codes.

[0120] The present invention is applicable to the field of multi-source PNT information elastic fusion navigation technology. The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any modifications or substitutions that can be readily conceived by persons skilled in the art within the technical scope disclosed herein are intended to be covered by the scope of protection of the present invention. Therefore, the scope of protection of the present invention shall be subject to the scope of protection of the claims.

[0121] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any modifications or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection of the claims.

Claims

1. A method for autonomous integrity and information control of component PNT resilient terminals, characterized in that: The following steps are involved: Step 1: Based on the Bayesian estimation method, the information factor of each component PNT is calculated. By minimizing the information factor of all components PNT, a flexible fusion solution of multi-source PNT information is achieved. Step 2: Integrate the information factors provided by each PNT information source to build a system-level fault anomaly monitoring model; If the system-level fault and anomaly monitoring model detects a fault and / or anomaly, the subsystem-level fault and anomaly monitoring model is started; otherwise, the subsystem-level fault and anomaly monitoring model is not started; Step 3: Based on local and global optimization methods, a subsystem model containing high-trust PNT components is constructed. Using consistency detection principles, a subsystem-level fault anomaly monitoring model is constructed. If the subsystem-level fault and anomaly monitoring model detects a fault and / or anomaly, the PNT signal source of the component that is elastically connected to the PNT terminal is regulated and the sensor-level fault and anomaly monitoring model is activated; otherwise, the sensor-level fault and anomaly monitoring model is not activated; Step 4: For PNT components with different redundancy characteristics, motion constraints and sliding window calculations are introduced to build a sensor-level fault anomaly monitoring model. If the sensor-level fault and anomaly monitoring model detects a fault and / or anomaly, information regulation is performed on the sensor components involved in the PNT signal source solution. Otherwise, information regulation is not performed on the sensor components involved in the PNT signal source solution. Step 5: Integrate the multi-level fault and / or anomaly monitoring results and initiate real-time verification, calibration, and reconstruction and restart of the corresponding model for the isolated fault and / or anomaly PNT signal sources and sensor components; The real-time verification model verifies the isolated PNT signal source and sensor components. If the verification passes, the corresponding PNT signal source and sensor component information involved in the solution is dynamically adjusted. Otherwise, the calibration model is started. The calibration model calibrates the isolated PNT signal source and sensor components. After calibration, the verification model is restarted. If the verification passes, the corresponding PNT signal source and sensor component information involved in the solution is dynamically adjusted. Otherwise, the reconstruction and restart model is started. The reconstruction and restart model reconstructs the solution model of the isolated PNT signal source and restarts the isolated sensor components. After the reconstruction and restart, the verification model pair is restarted. If the verification passes, the information of the corresponding PNT signal source and sensor components participating in the solution is dynamically adjusted. Otherwise, the isolated PNT signal source and sensor components are set to failure mode and enter periodic recovery verification. Step 6: Based on the system integrity risk requirements and the prior failure probability of each PNT signal source, dynamically allocate the integrity risk according to the combination of subsystems. Combined with the subsystem failure and / or anomaly monitoring thresholds, calculate the protection level of the PNT terminal and implement autonomous integrity monitoring of the component PNT terminals.

2. The method for autonomous integrity and information control of a component PNT elastic terminal according to claim 1 is characterized in that: The step 1 comprises: Step 11): Based on the measurement information z of the PNT component at time k k , calculate the information factor f of PNT component a a for In the formula, h(x k ) is the measurement equation at time k, x k is the state of the PNT component at time k, Σ is the measurement noise variance matrix; Step 12): Based on the Bayesian estimation method, the Gauss-Newton algorithm is used to solve the navigation state that satisfies the minimum PNT information factor of all components, realizing the elastic fusion solution of multi-source PNT information.

3. The method for autonomous integrity and information control of a component PNT resilient terminal according to claim 2, wherein: The step 2 specifically includes: Step 21): Integrate the information factors provided by each PNT information source to construct the system-level fault and / or anomaly monitoring statistic D sys for Where N is the number of PNT sources, and A is the number of PNT components contained in the PNT source; Step 22): If system-level failure and / or abnormal monitoring statistics D sys Greater than the set threshold T sys , if there are faults and / or anomalies in the system, the subsystem-level fault anomaly monitoring model needs to be started; otherwise, the subsystem-level fault anomaly monitoring model will not be started.

4. The method for autonomous integrity and information control of a component PNT resilient terminal according to claim 3, wherein: The step 3 specifically includes: Step 31): Based on the number of PNT signal sources N, assuming that the number of PNT signal sources that fail and / or are abnormal at the same time is F, calculate the number of subsystems C that include all combinations. n for Step 32): For each subsystem j, the standard deviation of the measurement residuals of all observations is used as the subsystem fault and / or abnormality monitoring statistic D sub,j for Where M is the number of observations, w m is the measurement residual vector corresponding to the mth observation; Step 33): If there is only one subsystem j that satisfies the fault and / or abnormality monitoring statistic D sub,j Greater than the set threshold T sub , then the PNT signal source excluded by subsystem j is a faulty and / or abnormal signal source, otherwise the number of PNT signal sources with simultaneous faults and / or abnormalities is increased, and the subsystem fault and / or abnormality monitoring is re-executed; Step 34) If the subsystem-level fault and anomaly monitoring model detects a fault and / or an abnormal signal source, the fault and / or abnormal signal source detected by the subsystem-level fault and anomaly monitoring model is isolated, the signal sources of the components involved in the PNT terminal calculation are regulated, and the sensor-level fault and anomaly monitoring model is activated; otherwise, the sensor-level fault and anomaly monitoring model is not activated.

5. The method for autonomous integrity and information control of component PNT flexible terminals according to claim 4, characterized in that: The step 4 specifically includes: Step 41): Introduce sliding window calculation to count the measurement values ​​R of sensor component s at all times within the sliding window s (t k )={r s (t k-p+1 ),...,r s (t k-1 ),r s (t k )}, forming the self-evaluation parameter D of the sensor component self for Where r s (t k ) represents t k The measured value of the sensor component at the moment, med(*) is the median function, and e is the exponential function f=e (x) ; Step 42): If the PNT component is a non-redundant sensor component, the mutual evaluation parameter is not calculated; otherwise, the sensor component mutual evaluation parameter D is calculated using the Pearson coefficient. mutual for Where μ s is the measurement value R of sensor component s at all times within the sliding window s (t k )={r s (t k-p+1 ),...,r s (t k-1 ),r s (t k )}, σ s The measurement sequence R s (t k ), μ q is the measurement value R of the sensor component q at all times within the sliding window q (t k )={r q (t k-p+1 ),…,r q (t k-1 ),r q (t k )}, σ q The measurement sequence R q (t k )’s standard deviation; Step 43): Integrate the self-evaluation parameters and mutual evaluation parameters of the sensor components to construct the sensor-level fault and / or anomaly monitoring statistic D sensor,s for Where α1 and α2 are adjustable weight factors, s is the sensor component being evaluated, and S is the number of redundant sensors; Step 44): If there is a sensor level fault and / or abnormal monitoring statistic D sensor,s Greater than the set threshold T sensor , the sensor component s is a faulty and / or abnormal sensor component; otherwise, the sensor-level fault and anomaly monitoring model does not detect the fault; Step 45): If the sensor-level fault and anomaly monitoring model detects a faulty and / or abnormal sensor component, information regulation is performed on the sensor components participating in the PNT signal source solution to isolate the faulty and / or abnormal sensor components; otherwise, information regulation is not performed on the sensor components participating in the PNT signal source solution.

6. The method for autonomous integrity and information control of a component PNT elastic terminal according to claim 5, characterized in that: The step 5 specifically includes: Step 51): Build a real-time verification model to verify the isolated PNT signal source and sensor components. If the verification passes, dynamically adjust and solve the corresponding PNT signal source and sensor component information. Otherwise, start the calibration model. Step 52): Construct a calibration model to calibrate the isolated PNT signal source and sensor components. After calibration, restart the verification model. If the verification passes, dynamically adjust the information of the corresponding PNT signal source and sensor components involved in the solution. Otherwise, start the reconstruction and restart model. Step 53): Reconstruct the solution model of the isolated PNT signal source and restart the isolated sensor component. After the reconstruction and restart, restart the verification model pair. If the verification passes, dynamically adjust the information of the corresponding PNT signal source and sensor component involved in the solution. Otherwise, set the isolated PNT signal source and sensor component to failure mode and enter periodic recovery verification.

7. The method for autonomous integrity and information control of a component PNT flexible terminal according to claim 6, characterized in that: The step 6 specifically includes: Step 61): Based on the system integrity risk requirements and the prior failure probability of each PNT signal source, the integrity risk is dynamically allocated according to the subsystem combination; Step 62): According to the assigned integrity risk P risk,j and subsystem fault and / or abnormality monitoring threshold T sub , calculate the protection level PL of the PNT terminal as Where, slope j The projection slope from the measurement domain to the position domain is calculated by converting the threshold in the measurement domain to the position domain by calculating the square of the mean position error. The noncentral parameter λ of the noncentral chi-square distribution obeyed by the test quantity j The ratio of K md is the integrity risk factor calculated by the inverse probability function, σ j is the standard deviation of position error; Step 63): If the protection level is greater than the alarm limit required by the system, a navigation system integrity loss alarm is issued to the user within the specified alarm time, reminding the user that the positioning information provided by the navigation system at the current moment is unreliable; otherwise, no integrity loss alarm is issued.

8. The component PNT resilient terminal autonomous integrity and information control system is characterized by: The method for autonomous integrity and information control of component PNT elastic terminals as described in any one of claims 1 to 7 is applied to realize autonomous integrity and information control of componentized PNT terminals, so that the terminal system has elastic capabilities.

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