PPP-RTK correction product credibility comprehensive monitoring method

Abstract

The present application relates to a kind of PPP-RTK correction product credibility comprehensive monitoring method, comprising: EXM-I monitoring stage before correction product broadcast and EXM-II monitoring stage after broadcast, wherein: in EXM-I monitoring stage, including: before correction product broadcast, satellite broadcast ephemeris, satellite signal, atmospheric gradient monitoring information are integrated, and various types of credible observation are screened out;In EXM-II monitoring stage, including: after correction product broadcast, the credible monitoring information of correction product is summarized, the EXM-II stage monitoring method is used to carry out the correction product credibility monitoring and availability decision based on single satellite, and the credible monitoring information of correction product is exported and timely broadcast to user, guarantee the credibility of user real-time high-precision navigation positioning.

Description

Technical Field

[0001] This invention relates to the field of satellite navigation technology, and specifically to a comprehensive monitoring method for the reliability of PPP-RTK correction products. Background Technology

[0002] Global Navigation Satellite System (GNSS) is a crucial tool for achieving informationization and modernization in transportation, encompassing numerous typical civilian applications across sea, land, and air, such as drone swarm navigation, intelligent marine ranching operations, and collaborative smart agricultural machinery operations. Precise Point Position-Real Time Kinematic (PPP-RTK) is a navigation-forward positioning method that balances accuracy and real-time performance. It combines the complementary advantages of Real Time Kinematic (NRTK) for real-time positioning in local areas with Precise Point Position (PPP) for centimeter-level high-precision positioning globally. This allows for better tiered service to meet diverse user needs within large local areas, gaining increasing attention from countries and regions. The PPP-RTK positioning method broadcasts positioning correction products to users through a service platform, achieving convergence within one minute and centimeter-level positioning accuracy. To ensure the reliability of the PPP-RTK positioning service, trusted monitoring stations are deployed within the service area to monitor correction products and generate corresponding reliability information, which is then broadcast to users. Due to differences in geographical location and distance between stations, the monitoring results of credible monitoring stations on the corrected products may be inconsistent. It is necessary to aggregate the monitoring data from different credible monitoring stations and carry out comprehensive monitoring to ensure the reliability of the service platform's positioning service.

[0003] Executive Monitoring (EXM) is a common and effective logical monitoring method on the positioning service system platform that processes integrity monitoring information such as satellite signals, satellite broadcast ephemeris data, and pseudorange / carrier phase observations. It can further improve the overall continuity and integrity of the positioning service system and is widely used in satellite positioning augmentation systems such as Ground Based Augmentation System (GBAS) and Joint Precision Approach and Landing System (JPALS).

[0004] The research and development of reliable monitoring of correction products in PPP-RTK positioning service system platforms is relatively recent, and the correction products are complex and diverse, with varying navigation service needs for both marine and land users. Before the broadcast of PPP-RTK correction products, satellite broadcast ephemeris failures, abnormal satellite signals, and ionospheric / tropospheric storms can all interfere with the reliable monitoring of subsequent correction products. After the broadcast of correction products, when the monitoring results of correction products from multiple monitoring stations are inconsistent, the reliability of the availability label of the correction products cannot be guaranteed. Summary of the Invention

[0005] To address the aforementioned issues, this invention presents a comprehensive monitoring method for the reliability of PPP-RTK corrected products based on the EXM monitoring principle.

[0006] The comprehensive monitoring method for the reliability of PPP-RTK corrected products includes: an EXM-I monitoring stage before broadcasting and an EXM-II monitoring stage after broadcasting, wherein:

[0007] The EXM-I monitoring phase includes:

[0008] Step S1: Summarize the trusted monitoring information from the trusted monitoring network before the corrected product is broadcast, classify the trusted monitoring information according to the propagation process of the navigation information, and extract the fault information recorded in the trusted monitoring information;

[0009] Step S2: Based on the magnitude of the impact of the faults obtained from the trusted monitoring information on the original observations involved in generating residuals of the corrected products, the faults reflected in the trusted monitoring information are divided into two levels: satellite channel level and satellite level.

[0010] Step S3: Based on the smallest original satellite observation unit, reliable observations are selected sequentially according to the "satellite level - channel level" priority criterion, and the available observations are provided to the subsequent correction product generation stage.

[0011] During the EXM-II monitoring phase, the following are included:

[0012] Step S4: Receive monitoring information of the corrected products from the trusted monitoring network and the inspection statistics of the corrected products contained therein;

[0013] Step S5: Based on the minimum detectable deviation decision criterion, determine the Boolean method correction product availability decision threshold, and obtain the detection threshold and minimum detectable deviation of the monitoring station's correction product integrity monitor;

[0014] Step S6: Combine the corrected products of the common-view satellite monitored by each trusted monitoring station, construct the test statistic of the average value of the corrected products, and determine the detection threshold of the test statistic of the average value of the corrected products;

[0015] Step S7: Based on the principle that the false alarm rate index of the correction product of the common-view satellite remains unchanged, the correction product test statistic obtained in step 4, the correction product detection threshold obtained in step 5, and the correction product average test statistic obtained in step 6, along with the detection threshold of the correction product average test statistic, are combined in the orthogonal space of the multidimensional correction product test statistics to form a new detection threshold, thereby determining the availability of the correction product and obtaining reliable monitoring information of the correction product;

[0016] Step S8: Transmit reliable monitoring information of various correction products to the precise positioning service information generation system.

[0017] The beneficial effects of this invention are as follows:

[0018] This invention designs a PPP-RTK correction product reliability monitoring method based on the EXM monitoring principle. It conducts comprehensive monitoring before and after correction product broadcasting on a precise and reliable positioning service platform. Before broadcasting, it integrates satellite broadcast ephemeris, satellite signals, and atmospheric gradient monitoring information, and uses the EXM-I stage monitoring method to screen reliable raw observations such as reliable carrier phase / pseudorange observations, ensuring the reliability of the observation data involved in generating the correction product. After broadcasting, it summarizes the reliability monitoring information of the correction product and uses the EXM-II stage monitoring method to conduct single-satellite-based reliability monitoring and availability decision-making for the correction product. It outputs the reliability monitoring information of the correction product and broadcasts it to users in a timely manner, ensuring the reliability of users' real-time high-precision navigation and positioning, and providing high-precision and highly reliable PPP-RTK positioning services for land and sea users. It not only fully guarantees the reliability of the observation data of the residuals of various PPP-RTK correction products, but also makes full use of the reliable monitoring information of the monitoring station network, providing the most important reliable basis for land and sea users to use correction products, and providing users with highly reliable correction products, which is of great significance for ensuring real-time, high-precision and high-reliability navigation performance services on land and sea. Attached Figure Description

[0019] Figure 1 The flowchart of the PPP-RTK correction product reliability comprehensive monitoring method based on the EXM monitoring principle provided by this invention. Detailed Implementation

[0020] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] This invention proposes a two-stage integrated monitoring technology based on the EXM monitoring principle: an EXM-I monitoring stage before the broadcast of the corrected product and an EXM-II monitoring stage after the broadcast. Specifically, this invention provides a comprehensive monitoring method for the reliability of PPP-RTK corrected products based on the EXM monitoring principle. It conducts comprehensive monitoring before and after the broadcast of the corrected product on a precise and reliable positioning service platform. Before the broadcast, reliable raw observations, such as reliable carrier phase / pseudorange observations, are selected using the EXM-I stage monitoring method, integrating satellite broadcast ephemeris, satellite signals, and atmospheric gradient monitoring information. After the broadcast, the reliable monitoring information of the corrected product is summarized, and the EXM-II stage monitoring method is used to conduct reliable monitoring and availability decision-making for the corrected product based on a single satellite. The reliable monitoring information of the corrected product is then output and broadcast to users in a timely manner.

[0022] refer to Figure 1 This invention proposes a comprehensive monitoring method for the reliability of PPP-RTK corrected products based on the EXM monitoring principle, which includes two parts: the EXM-I monitoring stage before the corrected product is broadcast and the EXM-II monitoring stage after the broadcast.

[0023] The EXM-I monitoring phase includes:

[0024] Step S1: Summarize the trusted monitoring information from the trusted monitoring network before the corrected product is broadcast, classify the trusted monitoring information according to the propagation process of the navigation information, and extract the fault information recorded in the trusted monitoring information.

[0025] Based on the characteristics of navigation information transmission through the atmosphere in the satellite signal band-frequency-frequency point broadcasting format during PPP-RTK positioning, this invention categorizes reliable monitoring information into three types: satellite signal, satellite broadcast ephemeris, and atmospheric gradient. Specifically: satellite signal monitoring information includes both signal power and signal interference immunity monitoring information; ephemeris monitoring information contains only broadcast ephemeris monitoring information; and atmospheric gradient monitoring information includes both regional ionospheric monitoring information and regional tropospheric monitoring information. These three types of monitoring information can reflect whether the monitored risk source has caused a fault, manifested as whether the satellite signal, satellite broadcast ephemeris, and atmospheric gradient availability flags are set to unavailable. Extracting the fault information recorded in the reliable monitoring information involves reading the unavailable information recorded in the satellite signal, satellite broadcast ephemeris, and atmospheric gradient availability flags.

[0026] Step S2: Based on the magnitude of the impact of the faults obtained from the trusted monitoring information on the original observations involved in the generation of residuals in the corrected products, the faults reflected in the trusted monitoring information are divided into two levels: satellite channel level and satellite level.

[0027] Based on the impact of faults caused by risk sources such as satellite broadcast ephemeris failures, satellite signal anomalies, and regional ionospheric / tropospheric gradient anomalies on the raw pseudorange / carrier phase observations, monitoring information reflecting these risk sources is divided into two levels: satellite channel level and satellite level. Satellite signal power anomalies are satellite channel level faults, affecting only one satellite channel while other channels remain unaffected. However, when anomalies are detected by satellite signal interference monitors, broadcast ephemeris monitors, and atmospheric gradient monitors, the satellite becomes unusable; these monitoring anomalies all fall under the category of satellite level faults.

[0028] Step S3: Based on the smallest original satellite observation unit, reliable observations are selected sequentially according to the priority criterion of "satellite level - channel level", and the available observations are provided to the subsequent correction product generation stage.

[0029] Based on the monitoring information categories and fault levels determined in step S2, and following the "satellite-channel" priority criterion, and aided by information category, reliable observations are sequentially filtered across satellites. First, faulty satellites are removed based on unusable flags indicating satellite-level faults, and their channel-level monitoring information is no longer analyzed. Second, satellite channel-level faults are assessed. Building upon the satellite observations retained from the previous screening, the channel's normal condition is determined using channel-level monitoring flags, resulting in the selection of usable channel-level observations—that is, reliable observations. Finally, these usable observations are provided to the subsequent correction product generation stage.

[0030] After the corrected product is generated, it is broadcast to the user, and the trusted monitoring network monitors the broadcasted corrected product.

[0031] During the EXM-II monitoring phase, the following are included:

[0032] Step S4: Receive monitoring information of the corrected products from the trusted monitoring network and the inspection statistics of the corrected products included therein.

[0033] This EXM-II monitoring phase is a comprehensive monitoring based on the satellite clock-orbit correction product monitoring information, regional ionospheric correction product monitoring information, and regional tropospheric correction product monitoring information generated by trusted monitoring stations. Combining the EXM monitoring principle, it conducts comprehensive monitoring of correction products and makes correction product availability decisions in response to inconsistencies in the results of collaborative monitoring of correction products by multiple monitoring stations.

[0034] The PPP-RTK service platform uses correction products generated from available observables screened during the EXM-I monitoring phase. After the correction products are generated and broadcast to users, the trusted monitoring station network monitors the broadcast correction products. The EXM-II phase monitoring requires receiving various correction product monitoring information from the monitoring station network, that is, the monitoring information of satellite clock orbit correction products of each trusted monitoring station, the monitoring information of regional ionospheric correction products, and the monitoring information of regional tropospheric correction products. The monitoring information includes correction product residuals and availability indicators. The test statistics include: satellite clock orbit test statistics, regional tropospheric test statistics, and regional ionospheric test statistics. Each trusted monitoring station conducts trusted monitoring of correction products with the correction product residuals as the test statistics. The correction product residuals are expressed as satellite clock orbit residuals res Orb+Clk 、regional tropospheric residuals res Reg Tropo 、and regional ionospheric residuals res Reg Iono . The residuals of the relevant correction products are all generated at the monitoring stations and transmitted back to the PPP-RTK service platform.

[0035] Step S5, according to the minimum decision criterion of the minimum detectable bias (MDB), determine the correction product availability decision threshold of the Boolean method (also called the m + / n method), and obtain the detection threshold and minimum detectable bias MDB of the correction product integrity monitor of the monitoring station.

[0036] The minimum detectable bias MDB refers to the minimum ranging bias that can be detected by the integrity monitor under the dual constraints of the given false alarm rate and missed detection rate, which characterizes the monitoring sensitivity of the integrity monitor. The smaller the minimum detectable bias MDB, the higher the monitoring sensitivity of the integrity monitor.

[0037] [[ID=第十九]]Since the distance between each trusted monitoring station of the PPP-RTK service platform is more than 200 km, the correction product test statistics constructed by each trusted monitoring station can be regarded as independent of each other. For this, the Boolean method can be used to judge whether the correction product is available. That is, if the alarms of the same type of integrity monitors of n monitoring stations with co-viewed satellites are m (m < n) or more, it is determined that the correction product of the co-viewed satellite is unavailable, otherwise it is determined to be available. m represents the correction product availability decision threshold. The Boolean method distributes the missed detection rate and false alarm rate of the same type of integrity monitors of co-viewed satellites through the specific decision threshold m, ensuring the continuity and integrity indicators of the correction product.

[0038] For ease of description, monitoring stations are used to represent the integrity monitors of various correction products. The following explanation uses the coordinated monitoring of multiple integrity monitors for satellite clock-orbit correction products as an example. The coordinated monitoring of regional tropospheric and regional ionospheric correction products is similar, therefore, it will not be described again. The false alarm rate / missed detection rate index of the clock-orbit correction products of the shared satellite monitored by n monitoring stations is based on the availability decision threshold m and allocated using the following formula:

[0039]

[0040]

[0041] in The false alarm rate index of clock-orbit correction products for common-view satellites (S) The false negative rate index for clock-orbit correction products of common-view satellite s is provided by the positioning service system platform. m represents the decision threshold for Boolean-based satellite clock-orbit correction products. This represents the false alarm rate index of the satellite clock orbit correction product for the common-view satellite s, assigned to each monitoring station when the decision threshold m is set using the Boolean method. This represents the missed detection rate index of satellite clock-orbit correction products for the common-view satellite s, allocated to each monitoring station when the decision threshold m is used in the Boolean method. The index allocated to the monitoring station differs depending on the decision threshold m used in the Boolean method. n represents the number of monitoring stations used to monitor the common-view satellite s. (Combined operations...) The false alarm rate and false alarm rate of the clock-orbit correction products for the remaining common-view satellites at each monitoring station are calculated according to the above formula.

[0042] Each trusted monitoring station conducts trusted monitoring of satellite clock-track correction products using the residuals of the correction products as the test statistic. The residuals of the satellite clock-track correction products extracted by the trusted monitoring stations only include the correction product error and observation noise after Gaussianization of the correction product quality label, and therefore follow a Gaussian distribution. Due to differences in the geographical location and monitoring environment of the monitoring stations, the use of m... + Before using the / n method, the residuals of the satellite clock track correction product should be normalized, i.e., they should follow the following Gaussian distribution under the fault-free condition H0 and the fault condition H1:

[0043] H0:

[0044] H1:

[0045] in This represents the clock-orbit correction product residual of the common-view satellite s monitored by monitoring station k before normalization. This represents the clock-orbit correction product inspection statistic for common-view satellite s monitored by monitoring station k after normalization. The standard deviation of the clock track correction product residual is the square root of the sum of the squares of the standard deviations of the correction product quality label and the observed noise, provided by the positioning service system platform and the trusted monitoring station. This indicates the ranging domain deviation caused by the correction product malfunction. Since this article uses a satellite clock-track correction product as an example, for ease of description, subsequent test statistics and other related parameters are assumed to be the parameters of the clock-track correction product for the common-view satellite s, and the superscript s and subscript Orb+Clk are ignored in the parameter expressions.

[0046] Different decision thresholds in the Boolean method lead to different index allocations, resulting in different minimum detectable deviations (MDBs) for each monitoring station. The decision threshold is selected based on the highest monitoring sensitivity of the Boolean method. The statistical distribution of the product is corrected by satellite clock track. The minimum detectable deviation (MDB) under different decision thresholds is obtained by the Boolean method, and the smallest minimum detectable deviation (MDB) is found.

[0047]

[0048]

[0049] in, The minimum detectable deviation of the satellite clock track correction product of the monitoring station when the decision threshold is m; This indicates the normalized detection threshold for the satellite clock track correction products at the monitoring station. Q represents the mean offset of the inspection statistic for satellite clock track correction products when the products malfunction; it is calculated using a known method. -1 () denotes the inverse function of the tail probability of the standard Gaussian distribution. n represents the number of monitoring stations used to monitor the common-view satellite s. The decision threshold m is obtained by iterating through all integers from 1 to n. And compare to find the minimum value After that, the corresponding m best This is the optimal decision threshold for using the Boolean method for the clock-orbit correction product of the common-view satellite s, which will be briefly described below as the minimum MDB Boolean method decision threshold.

[0050] The normalized detection threshold of the clock-orbit correction product of the common-view satellite s at the monitoring station can be determined.

[0051] Similarly, the clock track correction products for other common-view satellites can be obtained using the Boolean method following the steps described above, such as false alarm rate and detection threshold, as well as the Boolean method clock track correction product availability decision threshold and the Boolean method decision threshold based on minimum MDB.

[0052] Similarly, the remaining correction products of a common-view satellite (i.e., regional tropospheric correction products and regional ionospheric correction products) can be obtained using the Boolean method following the steps described above, such as false alarm rate and detection threshold, as well as Boolean clock-orbit correction product availability decision threshold, Boolean decision threshold based on minimum MDB, etc.

[0053] Step S6: Combine the corrected products of the common-view satellite monitored by each trusted monitoring station, construct the test statistic of the average value of the corrected products, and determine the detection threshold of the test statistic of the average value of the corrected products.

[0054] Taking the multi-station collaborative monitoring of satellite clock-orbit correction products as an example, based on the existing method of average value monitoring of EXM monitoring multi-station coordination in ground-based augmentation systems (GBAS), the constructed average value test statistic for satellite clock-orbit correction products is as follows:

[0055]

[0056] in X is the test statistic of the average value of clock-orbit correction products monitored by multiple monitoring stations for the common-view satellite s. Subsequent steps are simply referred to as the test statistic of the average value of the correction products. n represents the number of monitoring stations used to monitor the common-view satellite s. k This is the normalized clock-track correction product test statistic for the common-view satellite s constructed by monitoring station k. Based on probability theory, it follows a Gaussian distribution N(0, 1 / n). According to the false alarm rate index P of the clock-track correction product for the common-view satellite s mentioned in step 5... FA The missed detection rate index P of clock track correction products for co-viewed satellites. MD By determining the statistical distribution of the test statistic for the corrected product mean, the detection threshold for that test statistic can be established. With minimum detectable deviation

[0057]

[0058]

[0059] in Q represents the detection threshold of the test statistic for the average value of satellite clock-track correction products, n represents the number of monitoring stations used to monitor common-view satellites, and Q represents the detection threshold. -1 () denotes the inverse function of the tail probability of the standard Gaussian distribution, P FA This refers to the false alarm rate of clock-orbit correction products for common-view satellites.

[0060] Test statistic of product average value when satellite clock track correction Less than the detection threshold When the satellite clock track correction product is available, it is available; otherwise, it is not available.

[0061] Similarly, based on the above method, the average test statistic, detection threshold, and minimum detectable deviation of the other two types (regional ionospheric and regional tropospheric) correction products of all common-view satellites within the monitoring station network are determined. When the average test statistic of the regional ionospheric correction product is less than the corresponding detection threshold, the regional ionospheric correction product is usable; otherwise, it is not usable. When the average test statistic of the regional tropospheric correction product is less than the corresponding detection threshold, the regional tropospheric correction product is usable; otherwise, it is not usable.

[0062] Step S7: Based on the principle that the false alarm rate index of the corrected product of the common-view satellite s remains unchanged, the test statistic of the corrected product obtained in step 4, the normalized detection threshold of the corrected product obtained in step 5, the test statistic of the average value of the corrected product obtained in step 6, and the detection threshold of the test statistic of the average value of the corrected product are combined in the orthogonal space of the test statistics of the multidimensional corrected product to form a new detection threshold. Based on the new detection threshold, the availability of the corrected product is judged, and the reliable monitoring information of the corrected product is obtained, that is, the availability flag of the corrected product. The availability flag records whether the corrected product is available or unavailable.

[0063] In step 5, the detection threshold obtained is preferably the detection threshold obtained after normalization of the corrected product.

[0064] Taking satellite clock-orbit correction products from multi-monitoring stations as an example, based on the Boolean method and the average method using the minimum detectable deviation (MDB), the test statistics of both methods need to be projected into a multidimensional test statistic space. The orthogonal space of the multidimensional test statistics formed by the test statistics of the clock-orbit correction products of the shared satellite s monitored by each trusted monitoring station can be expressed as:

[0065] X n ={e1,…e k ,…e n},in

[0066] Where X n Let {e1, e2, ..., e} be the orthogonal space of the n-dimensional clock orbit correction product test statistics for common-view satellite s. n} for space X n The unit orthogonal basis, e k Let n be the n×1 unit vector representing the clock track correction product inspection statistic for monitoring station k (k = 1, 2, ..., n).

[0067] In step 5, the clock track correction product inspection statistic is used in space X based on the minimum detectable deviation (MDB) using the Boolean method. nThe inner is represented as,

[0068]

[0069] in X is the normalized clock-track correction product inspection statistic of monitoring station k and monitoring satellite s. k A vector of test statistics consisting of (k = 1, 2, ..., n). For ease of description, it will be referred to as... This is simply referred to as the Boolean statistic vector. The detection threshold vector of the minimum detectable deviation (MDB) corresponding to the Boolean statistic vector can be expressed as follows:

[0070]

[0071] in Indicates that the decision threshold is m best Time test statistic vector The corresponding detection threshold vector. This represents the detection threshold of monitoring station k. The Boolean method based on minimum MDB determines the availability condition of the clock track correction product:

[0072] TP:

[0073] TF:

[0074] Where TP indicates that the test passed, meaning the clock-orbit correction product for the common-view satellite s is usable; TF indicates that the test failed, meaning the clock-orbit correction product for the common-view satellite s is unusable. Expression This indicates the number of monitoring stations whose clock-track correction product inspection statistics for the monitored common-view satellite s exceed the detection threshold. Representing vectors Each element is less than the vector Each corresponding element, Representing vectors Each element is greater than or equal to the vector Each corresponding element. For example, Boolean law in space X... 2 Availability assessment of internal satellite clock track correction products: Vector when n=2 It is Space X 2 The inner shape is parallel to the two coordinate axes e1 and e2 and has a value of The rectangular region formed by the intersection of four straight lines, vector (X1, X2). T When located outside the rectangular area, the clock orbit correction product for the common-view satellite s is unavailable; vector (X1,X2) T When located within a rectangular area, clock-orbit correction products for common-view satellites are available.

[0075] In step S6, the test statistic of the average value of the clock-orbit correction product of the shared-view satellite s, which is monitored collaboratively by multiple monitoring stations, and the corresponding detection threshold in space X... n The interior can be represented in coordinate form using a unit orthogonal basis:

[0076]

[0077]

[0078] in This represents the vector of test statistics for the average value of clock track-corrected products. This represents the set of detection threshold vectors corresponding to the test statistic of the clock track correction product's average value. The average value method in space X... n The usability assessment of the internal clock track correction product is as follows:

[0079] TP:

[0080] TF:

[0081] Where TP indicates that the test passed, meaning the clock-orbit correction product for the common-view satellite s is usable; TF indicates that the test failed, meaning the clock-orbit correction product for the common-view satellite s is unusable. Vector inequality Representing vectors Each element is less than the vector For each corresponding element, the vector inequality Representing vectors Each element is greater than or equal to the vector Each corresponding element. For example, the average method in space X... 2 Usability assessment of internal clock track correction products: Vector set when n=2 Based on constraints In space The inner lines form two parallel lines, and the vectors When located within a parallel straight line, clock-track correction products for common-view satellites s are available; When located outside a parallel straight line, the clock orbit correction product for the common-view satellite s is unavailable.

[0082] The EXM-II stage monitoring method, combining the Boolean method and the average method, can enhance fault detection capabilities and fault-free anti-interference capabilities while ensuring the integrity of the corrected product. To combine the Boolean method and the average method based on the minimum detectable deviation (MDB), this method utilizes the orthogonal space of multidimensional test statistics and combines it with the test statistic vector of the corrected product determined by the Boolean method and the average method. Based on the principle that the false alarm rate of the corrected product remains unchanged, the detection threshold vector after combining the Boolean method and the average method is determined.

[0083] To combine the detection threshold vectors of Boolean method and average method in the orthogonal space of multidimensional test statistics, and to eliminate the influence of non-satellite correction product risk sources such as excessive random measurement noise from trusted monitoring stations, it is necessary to introduce 2 n -1 -1 auxiliary inspection statistic for satellite clock track correction products:

[0084]

[0085] in

[0086] Where ΔX i Let X represent the vector of auxiliary test statistics for the i-th satellite clock track correction product, sgn() represent the sign function, and X represent the vector of auxiliary test statistics for the i-th satellite clock track correction product. k (k = 1, 2, ..., n) is the normalized clock-orbit correction product test statistic for monitoring station k and monitoring satellite s. ΔX i The corresponding auxiliary test statistic detection threshold vector is expressed as follows:

[0087]

[0088] According to probability theory, for any ΔX i Test statistic X of the corrected product average n Following the same Gaussian distribution N(0, 1 / n), the detection threshold ΔT corresponding to the auxiliary test statistic of satellite clock track correction products is the same as the detection threshold of the mean statistic. The values ​​are equal. For ease of description, ΔX will be referred to as... i This is called the vector of the i-th auxiliary test statistic, ΔT. i This is called the detection threshold vector corresponding to the i-th auxiliary test statistic vector.

[0089] Based on the principle that the false alarm rate of the correction product for common-view satellite s remains unchanged, the detection threshold vector and the average detection threshold vector based on the Boolean method using the minimum detectable deviation (MDB) and 2 n-1 -1. The auxiliary test statistic detection threshold vectors are combined to form a certain region. Then, within these regions, the probability density function of the clock track corrected product test statistic, which constitutes the three types of test statistic vectors, is integrated to obtain the corresponding integration region. The probability density function of the clock track corrected product test statistic is the n-dimensional Gaussian distribution probability density function.

[0090]

[0091] Where X = (X1, X2, ..., X...) n ) TLet Σ be the normalized satellite clock track correction product test statistic vector, Σ be the covariance matrix, and since the normalized satellite clock track correction product test statistics of each monitoring station are independent of each other, Σ be an n×n identity matrix, and exp() be the exponential function.

[0092] Generally, the false alarm rate calculated within the integration region of the combination is always greater than the false alarm rate index. To ensure that the difference between the false alarm rate and the false alarm rate index within the integration region of the combination is within the allowable range of probability error, the integration region is changed by iterating and adjusting the detection thresholds of three types of statistics, such as the Boolean method and the average method based on the minimum MDB. The adjustable range of the detection thresholds of the three types of statistics is as follows:

[0093]

[0094]

[0095] in ΔT represents the adjustable detection threshold corresponding to the Boolean statistic based on minimum MDB. FA,comb This indicates the detection threshold corresponding to the adjustable auxiliary test statistic. This represents the detection threshold corresponding to the adjustable average statistic. The upper and lower limits of the adjustment range of the detection thresholds for these three types of statistics are the result of converting the corresponding detection thresholds of the Boolean method and the average method to their respective statistics.

[0096] The method for iteratively adjusting the three types of detection thresholds within the adjustable range is as follows:

[0097] 1) As a threshold for Boolean method detection Initial value, As the average detection threshold and auxiliary test statistic detection threshold ΔT FA,comb The false alarm rate p is calculated starting from the initial value. FA,comb 2) If the false alarm rate p in the integration region FA,comb With the false alarm rate indicator P FA If the difference is within the allowable range, then the search parameters meet the requirements, and the search stops; otherwise... and ΔT FA,comb by Increase the step size and calculate the false alarm rate p FA,comb 3) If step 2) still fails to meet the requirement after traversing to the maximum value, then apply the binary search principle to... Increase the value to the midpoint of the range, repeating steps 1) to 2) until the difference between the false alarm rate and the false alarm rate index in the integration region is within the allowable range of probability error. The allowable range of probability error is generally 0.1% of the false alarm rate index.

[0098] |p FA,comb -PFA |≤P FA ×0.1%,

[0099] in

[0100] Where P FA and p FA,comb These represent the false alarm rate index of the satellite clock orbit correction product and the false alarm rate in the integration region, respectively. For ease of description of the integration region, let T be the detection threshold for the above search. comb , and ΔT comb The three corresponding detection threshold vectors in space are: and ΔT i,comb (i = 1, 2, ... 2) n-1 -1). Therefore, the integration region can be represented as follows:

[0101]

[0102] in This indicates the integration region, which is the area deemed unusable by the satellite clock orbit correction product. The area represented and and The intersection of all regions represented. Indicates in The spatial Boolean statistic vector exceeds the adjustable Boolean detection threshold vector, resulting in an area where satellite clock-orbit correction products are unusable; This indicates that the average statistic vector exceeds the adjustable average detection threshold vector. Areas where satellite clock track correction products are unusable; Indicates 2 n-1 -1 If any one of the auxiliary test statistic vectors exceeds the corresponding adjustable auxiliary test statistic detection threshold vector ΔT i,comb This results in areas where satellite clock track correction products are unusable.

[0103] When P FA With p FA,comb When the difference in the false alarm rate index is within the allowable range of probability error, it can be considered as the detection threshold of the three types of statistics. and ΔT comb If the requirements are met, the adjusted detection thresholds for the three types of statistics are the new detection thresholds mentioned in step S7. Therefore, the EXM-II stage monitoring method combining the Boolean method and the average method uses the normalized satellite clock track correction product inspection statistic vector X = (X1, X2, ..., X...). n ) T To test the statistical vector and determine the availability of satellite clock orbit correction products:

[0104] TF:

[0105] TP:

[0106] Where TF indicates that the test failed, meaning X is in the region. The clock-orbit correction product for the internal time-common satellite s is unavailable; TP indicates that the test passed, meaning that X is in the region. Clock-track correction products for internal time-coordinated satellites are available. The areas where the adjusted satellite clock track correction products are available include: The area and and The shared area is indicated. This indicates the region where the Boolean statistic vector does not exceed the corresponding detection threshold vector. Vector of average statistics The region that does not exceed the corresponding test threshold vector Denotes the auxiliary test statistic vector ΔX i (i = 1, 2, ... 2) n-1 -1) None of them exceeded their respective test threshold vectors ΔT i,comb The area.

[0107] Similarly, the monitoring of the other two types of correction products (regional ionospheric and regional tropospheric) uses the same method to determine whether the relevant correction products are available.

[0108] Therefore, step S7 ultimately yields availability indicators for various corrective products, which record whether the corrective product is available or unavailable. These availability indicators constitute the reliable monitoring information for the corrective products.

[0109] Step S8: Transmit reliable monitoring information of various correction products to the precise positioning service information generation system.

[0110] The PPP-RTK integrated monitoring platform transmits the availability flags of each satellite correction product generated in step 7 to the precise positioning service information generation subsystem. Finally, it sends the availability flags of all satellite correction products to the user, who then decides whether to use the satellite associated with the correction product for high-precision real-time positioning based on the availability flags.

[0111] Before the broadcast of the PPP-RTK corrected product, this invention implements the EXM-I stage monitoring process to eliminate or suppress non-satellite risk sources through observation. After the broadcast of the PPP-RTK corrected product, the EXM-II stage monitoring method is adopted, which combines two existing reliable monitoring methods, Boolean method and average method, to determine the availability of the corrected product and provide users with real-time reliable monitoring information for PPP-RTK.

[0112] The above description, in conjunction with specific embodiments, provides a further detailed explanation of the present invention. It should not be construed that the specific implementation of the present invention is limited to these descriptions. For those skilled in the art, several simple deductions or substitutions can be made without departing from the concept of the present invention, and all such deductions or substitutions should be considered to fall within the scope of protection defined by the claims submitted herein.

Claims

1. A comprehensive monitoring method for the reliability of PPP-RTK correction products, comprising: Correct the EXM-I monitoring phase before product broadcast and the EXM-II monitoring phase after broadcast, including: The EXM-I monitoring phase includes: Step S1: Summarize the trusted monitoring information from the trusted monitoring network before the corrected product is broadcast, classify the trusted monitoring information according to the propagation process of the navigation information, and extract the fault information recorded in the trusted monitoring information; Step S2: Based on the magnitude of the impact of the faults obtained from the trusted monitoring information on the original observations involved in generating residuals of the corrected products, the faults reflected in the trusted monitoring information are divided into two levels: satellite channel level and satellite level. Step S3: Based on the smallest original satellite observation unit, select reliable observations in sequence according to the "satellite level - channel level" priority criterion, and provide the reliable observations to the subsequent correction product generation stage; During the EXM-II monitoring phase, the following are included: Step S4: Receive monitoring information of the corrected products from the trusted monitoring network and the inspection statistics of the corrected products contained therein; Step S5: Based on the minimum detectable deviation decision criterion, determine the Boolean method correction product availability decision threshold, and obtain the detection threshold and minimum detectable deviation of the monitoring station's correction product integrity monitor; Step S6: Combine the corrected products of the common-view satellite monitored by each trusted monitoring station, construct the test statistic of the average value of the corrected products, and determine the detection threshold of the test statistic of the average value of the corrected products; Step S7: Based on the principle that the false alarm rate index of the correction product of the common-view satellite remains unchanged, the correction product test statistic obtained in step 4, the correction product detection threshold obtained in step 5, and the correction product average test statistic obtained in step 6, along with the detection threshold of the correction product average test statistic, are combined in the orthogonal space of the multidimensional correction product test statistics to form a new detection threshold, thereby determining the availability of the correction product and obtaining reliable monitoring information of the correction product; Step S8: Transmit reliable monitoring information of various correction products to the precise positioning service information generation system.

2. The method for comprehensive monitoring of the reliability of PPP-RTK corrected products according to claim 1, wherein: The reliable monitoring information is divided into three categories: satellite signal, satellite broadcast ephemeris, and atmospheric gradient. The fault information records that the availability flags of satellite signal, satellite broadcast ephemeris, and atmospheric gradient are set to unavailable.

3. The method for comprehensive monitoring of the reliability of PPP-RTK correction products according to claim 1, wherein: The monitoring information of the correction products includes: monitoring information of satellite clock-orbit correction products, monitoring information of regional ionospheric correction products, and monitoring information of regional tropospheric correction products; the verification statistics include: satellite clock-orbit verification statistics, regional tropospheric verification statistics, and regional ionospheric verification statistics.

4. The method for comprehensive monitoring of the reliability of PPP-RTK correction products according to claim 1, wherein: In step S5, the method for obtaining the detection threshold of the correction product integrity monitor is as follows: The normalized detection thresholds of the satellite clock-orbit correction product, the regional tropospheric correction product, and the regional ionospheric correction product are obtained respectively. The method for obtaining the normalized detection threshold of the satellite clock-orbit correction product is as follows: ； in The minimum detectable deviation of the satellite clock track correction product of the monitoring station when the decision threshold is m; This indicates the normalized detection threshold of the satellite clock track correction product at the monitoring station. This indicates the mean shift of the inspection statistic for satellite clock track correction products when a product malfunctions. The above method was used to obtain the normalized detection thresholds of the regional tropospheric correction product and the regional ionospheric correction product of the monitoring station.

5. A comprehensive monitoring method for the reliability of PPP-RTK correction products according to claim 4, wherein: In step S6, the method for constructing the test statistic for the corrected product mean is as follows: construct test statistics for the satellite clock-orbit corrected product mean, test statistics for the regional tropospheric corrected product mean, and test statistics for the regional ionospheric corrected product mean, respectively, wherein: The method for constructing the test statistic for the average value of satellite clock track correction products is as follows: ； in It is the test statistic of the average clock-orbit correction products of multiple monitoring stations monitoring common-view satellites, where n represents the number of monitoring stations used to monitor common-view satellites. It is the normalized clock-orbit correction product test statistic of the common-view satellite s constructed by monitoring station k, which follows a Gaussian distribution. ; The above methods were used to obtain the test statistics for the average value of the regional tropospheric corrected products and the test statistics for the average value of the regional ionospheric corrected products.

6. A comprehensive monitoring method for the reliability of PPP-RTK correction products according to claim 5, wherein: In step S6, the method for determining the detection threshold of the test statistic for the corrected product mean is to separately determine the detection thresholds for the test statistic for the satellite clock-orbit corrected product mean, the test statistic for the regional tropospheric corrected product mean, and the test statistic for the regional ionospheric corrected product mean, wherein: The method for determining the detection threshold of the test statistic for the average value of satellite clock track correction products is as follows: ； in The threshold value represents the test statistic for the average value of satellite clock-track correction products, and n represents the number of monitoring stations used to monitor common-view satellites. This represents the inverse function of the tail probability of the standard Gaussian distribution. This indicates the false alarm rate of clock-orbit correction products for common-view satellites. The above methods were used to determine the detection thresholds for the regional tropospheric corrected product mean test statistic and the regional ionospheric corrected product mean test statistic, respectively.

7. A comprehensive monitoring method for the reliability of PPP-RTK correction products according to claim 6, wherein: In step S7, the method for determining the usability of the corrected product is: The method for determining the availability of satellite clock track correction products is as follows: ； in Let TF represent the normalized satellite clock orbit correction product test statistic vector, where TF indicates that the test failed. In the region The clock track correction product for the internal time-common satellite is unavailable. The satellite clock track correction product has been identified as an unavailable area. The area represented and and The intersection of all regions represented; Indicates in When the Boolean statistic vector in space exceeds the corresponding detection threshold vector This results in areas where satellite clock track correction products are unusable. This indicates that the average statistic vector exceeds the corresponding detection threshold vector. This results in areas where satellite clock track correction products are unusable. express If any one of the auxiliary test statistic vectors exceeds the corresponding detection threshold vector... This results in areas where satellite clock track correction products are unusable. TP indicates that the test passed, that is... In the region Clock-track correction products for domestically operated common-view satellites (CRTs) are available. The areas where the adjusted satellite clock track correction products are available include: The area and and The shared area is indicated. This indicates that the Boolean statistic vector has not exceeded the corresponding detection threshold vector. The area Vector of average statistics The corresponding test threshold vector was not exceeded. The area Represents the vector of auxiliary test statistics None of them exceeded their respective test threshold vectors The area; Similarly, the above judgment method can be used to determine the availability of regional ionospheric correction products and regional tropospheric correction products respectively.

8. A comprehensive monitoring method for the reliability of PPP-RTK correction products according to claim 7, wherein: Adjusting the Boolean detection threshold vector based on minimum detectable bias Average detection threshold vector Auxiliary test statistic detection threshold vector The method is to iteratively adjust the detection threshold of the Boolean method based on the minimum detectable deviation, the detection threshold of the average value, and the detection threshold of the auxiliary test statistic within the adjustable range, so that the difference between the false alarm rate and the false alarm rate index in the integration region is within the allowable range of probability error. The adjustable range is: ； in This represents the detection threshold corresponding to the adjustable Boolean statistic based on minimum MDB. This indicates the detection threshold corresponding to the adjustable auxiliary test statistic. This indicates the detection threshold corresponding to the adjustable average statistic; The method for traversing and adjusting within the adjustable range is: 1) As a threshold for Boolean method detection Initial value, As the average detection threshold and auxiliary test statistic detection threshold Calculate the false alarm rate starting from the initial value. ; 2) If the false alarm rate in the integration region With false alarm rate If the difference is within the allowable range, then the search parameters meet the requirements, and the search stops; otherwise... and by Increase step size and calculate false alarm rate 3) If step 2) still fails to meet the requirement after traversing to the maximum value, then apply the binary search principle to... Increase to the midpoint of the value range, and repeat steps 1) to 2) until the difference between the false alarm rate and the false alarm rate index in the integration region is within the allowable range of probability error; The integration region is: ； in The region of integration is... The area represented and and The intersection of all regions represented; Indicates in When the spatial Boolean statistic vector exceeds the adjustable Boolean detection threshold vector, it results in an area where satellite clock-orbit correction products are unusable. This indicates the region where the average statistic vector exceeds the adjustable average detection threshold vector, rendering the satellite clock-orbit correction product unusable. express If any one of the auxiliary test statistic vectors exceeds the corresponding adjustable auxiliary test statistic detection threshold vector, the satellite clock track correction product becomes unusable.

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