Positioning method and device

Abstract

The present invention provides a positioning method and device, belonging to the field of satellite positioning and navigation technology; the method performs fault processing on the observation vector of the receiver based on the new information vector, and improves the accuracy of the observation vector of the receiver by eliminating the vector with faults in the observation vector, thereby improving the accuracy of the GNSS positioning.

Description

Technical Field

[0001] The present invention relates to the field of satellite positioning and navigation technology, and in particular to a positioning method and device. Background Art

[0002] The Global Navigation Satellite System (GNSS), a space-based radio navigation and positioning system, can accurately locate most user devices on the Earth's surface or in near-Earth space. Specifically, user devices use their built-in receivers to observe navigation satellites in the GNSS, obtaining observation values ​​(also called observation vectors) to achieve positioning.

[0003] However, since the observation values ​​of the receiver built into the user equipment are extremely susceptible to hardware failures, satellite errors, signal propagation errors and receiver errors, the receiver's observation values ​​may be erroneous, which will undermine the accuracy and reliability of GNSS positioning, and thus make GNSS positioning inaccurate. Summary of the Invention

[0004] The present invention proposes a positioning method and device, which performs fault detection on the observation vector of the receiver based on the new information vector and eliminates the vectors with faults in the observation vectors, thereby protecting the accuracy and reliability of GNSS positioning, improving the accuracy of the receiver's observation vectors, and thus improving the accuracy of GNSS positioning.

[0005] In order to achieve the above object, the present invention adopts the following technical solutions:

[0006] In a first aspect, the present invention provides a positioning method, comprising:

[0007] S101. Determine the new information vector of the current epoch receiver based on the observation vector of the current epoch receiver, the observation equation of the receiver, and the state prediction model; wherein, the observation equation is used to describe the relationship between the observation vector and the state vector of the receiver, and the state prediction model is used to predict the state vector of the current epoch receiver; the new information vector is the difference between the observation vector of the current epoch receiver and the predicted value of the receiver's state vector.

[0008] S102: Perform fault determination on the observation vector of the current epoch receiver according to the innovation vector of the current epoch receiver.

[0009] S103 . When it is determined that there is a fault in the observation vector of the current epoch receiver, remove the vectors in the observation vector of the current epoch receiver whose fault identification verification value is greater than the fault verification threshold; otherwise, execute S105 .

[0010] S104. Determine the maximum number of failures of the current epoch receiver based on the preset integrity risk and prior failure probability; when the number of vectors eliminated in the observation vector of the current epoch receiver is less than the maximum number of failures of the current epoch, update the observation vector of the current epoch receiver to the observation vector of the receiver after the vectors are eliminated, and then return to execute S101-S104; otherwise, execute S105.

[0011] S105 : Determine the positioning result of the receiver using the state update model and the new information vector of the receiver at the current epoch.

[0012] In a positioning method provided by the present invention, the observation vector, observation equation and state prediction model of the current epoch receiver are first used to calculate the new information vector of the current epoch receiver, and then the observation vector of the current epoch receiver is analyzed for faults through the new information vector of the current epoch receiver; when it is determined that the observation vector of the current epoch receiver has a fault, the fault identification test value is used as a test index, and then the vectors in the observation vector whose fault identification test value is greater than the fault test threshold are eliminated, and after the vectors are eliminated, the number of eliminated vectors is limited by the maximum number of faults, so that the vectors finally retained in the observation vector not only have a certain accuracy, but also retain the redundancy of the observation vector, thereby improving the accuracy of GNSS positioning of the receiver through the observation vector.

[0013] In an implementation of the first aspect, the observation equation satisfies the following formula:

[0014] z=H·X+v

[0015] Where z represents the observation vector, and f represents frequency, S represents satellite, represents the pseudorange of satellite S at frequency f, represents the carrier observation value of satellite S at frequency f, Indicates the geometric distance between the receiver and the navigation satellite calculated based on the receiver's approximate coordinates. represents the ionospheric delay, T S represents the tropospheric delay, D orb represents the satellite orbit error;

[0016] H represents the observation matrix, and represents the symbol of partial derivative, λ f represents the wavelength of the carrier observation at frequency f;

[0017] X represents the state vector, and X r Indicates the coordinate of the receiver on the x-axis of the ECEF coordinate system, Yr Indicates the coordinate of the receiver on the y-axis of the ECEF coordinate system, Z r represents the coordinate of the receiver on the z-axis of the ECEF coordinate system, Δt r represents the receiver clock error, c represents the speed of light, represents the whole-cycle ambiguity;

[0018] v represents the observation noise vector, and is the measurement noise of pseudorange, is the measurement noise of the carrier.

[0019] In an implementation of the first aspect, the state prediction model satisfies the following formula:

[0020]

[0021] Among them, k represents the current epoch, k-1 represents the epoch before the current epoch, represents the predicted value of the change between the state vector of the receiver at time k-1 and the state vector of the receiver at time k, Φ k|k-1 represents the state transfer matrix of the receiver from k-1 to k, represents the observation value of the receiver's state vector at time k-1, P k|k-1 represents the predicted value of the state covariance matrix of the receiver at time k, P k-1 represents the state covariance matrix of the receiver at k-1, Q k represents the covariance matrix of the receiver process noise at time k.

[0022] The innovation vector satisfies the following formula:

[0023]

[0024] Among them, r k represents the receiver's innovation vector at time k, z k represents the observed value of the receiver's state vector at time k, H k represents the observation matrix of the receiver at time k, represents the predicted value of the receiver's state vector at time k.

[0025] In an implementation of the first aspect, performing fault determination on an observation vector of a current epoch receiver according to an innovation vector of the current epoch receiver includes:

[0026] The fault detection test quantity of the current epoch receiver is calculated based on the innovation vector of the current epoch receiver; the fault detection test quantity of the receiver satisfies the following formula:

[0027]

[0028] Among them, T g represents the fault detection test quantity of the receiver, and T g Obeys chi-square distribution; k represents the current epoch, r k represents the receiver’s innovation vector at time k, Represents r k The transposed matrix of : H k represents the observation matrix of the receiver at time k, P k|k-1 represents the predicted value of the state covariance matrix of the receiver at time k, Indicates H k The transposed matrix, R k represents the measurement noise of the observation value of the receiver at time k.

[0029] When the fault detection check value is greater than the fault detection threshold, it is determined that there is a fault in the observation vector of the current epoch receiver; otherwise, it is determined that there is no fault in the observation vector of the current epoch receiver.

[0030] In an implementation of the first aspect, the fault identification verification quantity satisfies the following formula:

[0031]

[0032] Where k represents the current epoch, i represents the i-th vector in the observation vector of the current epoch receiver, T i represents the fault identification test quantity of vector i; c i is a vector whose elements are all equal to 0 except the i-th element which is equal to 1. Indicates c i The transposed matrix, R k represents the measurement noise of the receiver's observation value at time k, Represents R k The inverse vector, r k represents the receiver's innovation vector at time k; P k|k-1 represents the predicted value of the state covariance matrix of the receiver at time k, Indicates H k The transposed matrix of .

[0033] In an implementation of the first aspect, the state update model satisfies the following formula:

[0034]

[0035] P k =(IK k H k)P k|k-1

[0036] Among them, k represents the current epoch, k-1 represents the epoch before the current epoch, and K k represents the receiver gain matrix at time k, P k|k-1 represents the predicted value of the receiver's state covariance matrix at time k, H k represents the observation matrix of the receiver at time k, Indicates H k The transposed matrix of R k represents the measurement noise of the observation value of the receiver at time k; represents the state vector of the receiver at time k after update, represents the predicted value of the change between the state vector of the receiver at time k-1 and the state vector of the receiver at time k, r k represents the receiver's innovation vector at time k; P k represents the state covariance matrix of the receiver at time k after update.

[0037] In an implementation of the first aspect, the method also includes: S106, constructing an observation equation based on the pseudorange and carrier observation value of the receiver; wherein the pseudorange is the pseudorange between the receiver and each navigation satellite in the multiple navigation satellites; the carrier observation value is the carrier observation value between the receiver and each navigation satellite in the multiple navigation satellites.

[0038] In a second aspect, the present invention provides a positioning device, comprising an innovation vector determination module, a fault determination module, a rejection module, a rejection quantity determination module, and a positioning module.

[0039] The innovation vector determination module is used to determine the innovation vector of the current epoch receiver based on the observation vector of the current epoch receiver, the observation equation of the receiver and the state prediction model; wherein, the observation equation is used to describe the relationship between the observation vector and the state vector of the receiver, and the state prediction model is used to predict the state vector of the current epoch receiver; the innovation vector is the difference between the observation vector of the current epoch receiver and the predicted value of the receiver's state vector.

[0040] The fault determination module is used to perform fault determination on the observation vector of the current epoch receiver according to the innovation vector of the current epoch receiver.

[0041] The elimination module is used to eliminate the vectors in the observation vector of the current epoch receiver whose fault identification verification value is greater than the fault verification threshold when it is determined that there is a fault in the observation vector of the current epoch receiver; otherwise, execute the processing steps of the positioning module.

[0042] The elimination number determination module is used to determine the maximum number of faults of the current epoch receiver based on the preset integrity risk and prior fault probability; when the number of vectors eliminated in the observation vector of the current epoch receiver is less than the maximum number of faults of the current epoch, the observation vector of the current epoch receiver is updated to the observation vector of the receiver after the elimination vector, and then the processing steps of the new information vector determination module, the fault determination module, the elimination module and the elimination number determination module are executed in sequence; otherwise, the processing steps of the positioning module are executed.

[0043] The positioning module is used to determine the positioning result of the receiver using the state update model and the new information vector of the current epoch receiver.

[0044] In an implementation of the second aspect, the positioning device also includes an observation equation determination module; the observation equation determination module is used to construct an observation equation based on the pseudorange and carrier observation value of the receiver; wherein the pseudorange is the pseudorange between the receiver and each of the multiple navigation satellites; the carrier observation value is the carrier observation value between the receiver and each of the multiple navigation satellites.

[0045] In a third aspect, the present invention provides an electronic device comprising a processor and a memory coupled to the processor; the memory is used to store computer instructions, and when the electronic device is running, the processor executes the computer instructions stored in the memory, so that the electronic device executes the method as described in the first aspect or any one of its implementations.

[0046] In a fourth aspect, the present invention provides a computer-readable storage medium comprising computer program instructions, which, when executed by a computer, enable the computer to execute the method according to the first aspect or any one of its implementations.

[0047] In a fifth aspect, the present invention provides a computer program product comprising computer program instructions, which, when executed on a computer, enable the computer to execute the method in the first aspect or any one of its implementations.

[0048] The technical effects corresponding to the above-mentioned second to fifth aspects and their possible implementation methods can refer to the above-mentioned description of the technical effects of the first aspect and its possible implementation methods, and will not be repeated here.

[0049] Compared with the prior art, the present invention has the following beneficial effects:

[0050] The present invention can significantly improve the integrity and reliability of the observation vectors of user devices during the precise positioning process, and is applicable to various positioning scenarios such as standard single point positioning (SPP), precise single point positioning (PPP) and real-time kinematic positioning (RTK). In the process of fault detection and fault elimination of the observation vectors, the covariance information of the new information vector is fully considered, which reduces the false alarm rate. At the same time, through the independent and real-time algorithm design, it meets the next generation of accurate and reliable high-performance requirements, providing user devices with an efficient and reliable positioning solution. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 This is one of the schematic diagrams of a positioning method provided in an embodiment of the present application;

[0052] Figure 2 It is a structural diagram of a positioning device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0053] In the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations, or descriptions; any embodiment or design scheme described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being preferred or advantageous over other embodiments or designs; rather, the use of words such as "exemplary" or "for example" is intended to present the relevant concepts in a concrete manner;

[0054] In the description of the present invention, unless otherwise specified, the meaning of "multiple" refers to two or more than two; for example, multiple navigation satellites refers to two or more navigation satellites;

[0055] The method and apparatus provided in the embodiments of the present application relate to the field of satellite positioning and navigation technology, and can be used to locate a user device using the Global Navigation Satellite System (GNSS). Specifically, the GNSS includes multiple navigation satellites, and the user device uses its built-in receiver to observe multiple navigation satellites in the GNSS to obtain observation values ​​(also called observation vectors) to achieve positioning of the user device. It is understood that the user device includes mobile phones, drones, smart wearable devices, and other devices.

[0056] In order to solve the problem in the background technology that the observation values ​​of the receiver built into the user equipment are easily affected by hardware failures, satellite end, signal propagation end and receiver end errors, resulting in errors in the observation values ​​of the receiver, destroying the accuracy and reliability of GNSS positioning, and thus leading to insufficient accuracy of GNSS positioning, the embodiment of the present application provides a positioning method and device, which first uses the observation vector, observation equation and state prediction model of the current epoch receiver to calculate the innovation vector of the current epoch receiver, and then uses the innovation vector of the current epoch receiver to perform fault analysis on the observation vector of the current epoch receiver; when it is determined that the observation vector of the current epoch receiver has a fault, the fault identification test amount is used as a test index, and then the vectors in the observation vector whose fault identification test amount is greater than the fault test threshold are eliminated, and after the vectors are eliminated, the number of eliminated vectors is limited by the maximum number of faults, so that the vectors finally retained in the observation vector not only have a certain accuracy, but also retain the redundancy of the observation vector, thereby improving the accuracy of GNSS positioning of the receiver through the observation vector;

[0057] It should be understood that in the embodiments of the present application, the process of fault detection and fault elimination for the receiver's observation vector belongs to user-level integrity monitoring (ULIM). ULIM is an independent algorithm based on hypothesis testing theory at the user end (e.g., receiver). It does not rely on external equipment, is highly flexible, and is suitable for real-time applications, meeting the urgent needs of reality and GNSS development.

[0058] For example, a positioning method provided in an embodiment of the present invention may be performed by an electronic device having a processing function, such as a computer, a server, etc.; taking the electronic device as a computer as an example, the hardware components of the computer may include: a processor, a memory, a network interface, a user interface, a communication bus, etc.;

[0059] The processor is used to control the electronic device to perform related processing and computing tasks, such as determining an innovation vector, fault determination, elimination vectors, and determining a positioning result of a receiver. The processor may include a central processing unit (CPU) or other processors. The processor may be single-core or multi-core, for example, the processor may include multiple CPUs.

[0060] The memory is used to store computer instructions and related data, for example, the observation vector, innovation vector, fault identification test value, maximum fault number, and positioning result of the receiver at the current epoch. The memory can be a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, or an optical memory, a disk storage medium or other magnetic storage device, or any other medium capable of storing program code or data accessible by a computer. Optionally, the memory can be integrated into the processor, or the memory can be independent of the processor.

[0061] The network interface is used for the computer to communicate with other devices or communication networks. The network interface can be a transceiver with transceiver functions; optionally, the network interface can include a standard wired interface or a wireless interface (such as a Wi-Fi interface, a Bluetooth interface, or a 5G interface);

[0062] The communication bus is used to realize the connection and communication between different components. For example, the processor, memory, network interface and user interface mentioned above can be interconnected through the communication bus;

[0063] The user interface may include a display screen, an input unit (such as a keyboard), and optionally, a standard wired interface or a wireless interface;

[0064] Those skilled in the art will appreciate that the computer may include more or fewer components, or combine certain components, or arrange components differently, which is not limited in the embodiments of the present application.

[0065] For example, Figure 1 As shown, a positioning method provided in an embodiment of the present application includes S101-S105;

[0066] S101, determining an innovation vector of the current epoch receiver based on the observation vector of the current epoch receiver, the observation equation of the receiver, and the state prediction model;

[0067] It can be understood that the embodiment of the present application is used to locate the user equipment in an actual application scenario; the receiver in the above S101 is set inside the user equipment, and positioning the receiver is equivalent to positioning the user equipment, and the positioning result of the receiver is the positioning result of the user equipment;

[0068] The observation vector of the receiver at the current epoch includes multiple vectors, each of which corresponds to an observation value of the receiver on a navigation satellite included in the GNSS. The observation equation is used to describe the relationship between the observation vector and the state vector of the receiver. The state prediction model is used to predict the state vector of the receiver at the current epoch. The innovation vector is the difference between the observation vector of the receiver at the current epoch and the predicted value of the receiver's state vector.

[0069] Optionally, the state prediction model may be a time update module of a Kalman filter. Since the Kalman filter is a commonly used related technology in this technical field, the embodiment of the present application does not further describe the time update module of the Kalman filter.

[0070] In one implementation, the observation equation satisfies the following formula:

[0071] z=H·X+v

[0072] Where z represents the observation vector, and f represents frequency, S represents satellite, represents the pseudorange of satellite S at frequency f, represents the carrier observation value of satellite S at frequency f, Indicates the geometric distance between the receiver and the navigation satellite calculated based on the receiver's approximate coordinates. represents the ionospheric delay, T S represents the tropospheric delay, D orb represents the satellite orbit error;

[0073] H represents the observation matrix, and represents the symbol of partial derivative, λ f represents the wavelength of the wave observation at frequency f;

[0074] X represents the state vector, and X r Indicates the coordinate of the receiver on the x-axis of the ECEF coordinate system, Y r Indicates the coordinate of the receiver on the y-axis of the ECEF coordinate system, Z r represents the coordinate of the receiver on the z-axis of the ECEF coordinate system, Δt r represents the receiver clock error, c represents the speed of light, represents the integer ambiguity; it can be understood that the above-mentioned ECEF coordinate system (Earth-Centered, Earth-Fixed coordinate system), also known as the Earth-centered Earth-fixed rectangular coordinate system, is a Cartesian coordinate system with the Earth's center of mass as its origin, and is commonly used to describe the position and motion of objects on or near the Earth; since the ECEF coordinate system is a common coordinate system in the technical field, it will not be further described in this embodiment of the present application;

[0075] v represents the observation noise vector, and is the measurement noise of pseudorange, is the measurement noise of the carrier;

[0076] It should be noted that the above observation equation is a matrix-form observation equation obtained by linearizing the receiver's pseudorange and carrier observation equations; the receiver's pseudorange and carrier observation equations satisfy the following formula:

[0077]

[0078] Among them, ρ S The geometric distance from the receiver to the satellite is ρ S The table contains the following formula:

[0079]

[0080] Among them, (X r , Y r , Z r ) and (X S , Y S , Z S ) represent the spatial position coordinates of the receiver and the satellite respectively;

[0081] The above state prediction model satisfies the following formula:

[0082]

[0083] Among them, k represents the current epoch, k-1 represents the epoch before the current epoch, represents the predicted value of the change between the state vector of the receiver at time k-1 and the state vector of the receiver at time k, Φ k|k- 1 represents the state transfer matrix of the receiver from k-1 to k, represents the observation value of the receiver's state vector at time k-1, P k|k-1 represents the predicted value of the state covariance matrix of the receiver at time k, P k-1 represents the state covariance matrix of the receiver at k-1, Q krepresents the covariance matrix of the receiver process noise at time k;

[0084] The above innovation vector satisfies the following formula:

[0085]

[0086] Among them, r k represents the receiver's innovation vector at time k, z k represents the observed value of the receiver's state vector at time k, H k represents the observation matrix of the receiver at time k, represents the predicted value of the receiver's state vector at time k;

[0087] S102, performing a fault determination on the observation vector of the current epoch receiver according to the innovation vector of the current epoch receiver;

[0088] Optionally, the above S102 includes S1021-S1022;

[0089] S1021. Calculate the fault detection verification quantity of the current epoch receiver according to the innovation vector of the current epoch receiver;

[0090] In the embodiment of the present application, the above-mentioned fault determination refers to a global test of whether all observation values ​​in the current epoch have fault values ​​through a chi-square test, and the sign of whether a fault exists is whether the fault detection test value exceeds the fault detection threshold;

[0091] In one implementation, the fault detection check quantity of the current epoch receiver is calculated by the covariance matrix of the innovation vector of the current epoch receiver; the fault detection check quantity of the receiver satisfies the following formula:

[0092]

[0093] Among them, T g represents the fault detection test quantity of the receiver, and T g Obey the chi-square distribution, specifically, T g It obeys the chi-square distribution with q degrees of freedom (DOF), where q is the number of measurements; k represents the current epoch, and r k represents the receiver’s innovation vector at time k, Represents r k The transposed matrix of W k represents the covariance matrix of the receiver’s innovation vector at time k, H k represents the observation matrix of the receiver at time k, P k|k-1 represents the predicted value of the state covariance matrix of the receiver at time k, Indicates H kThe transposed matrix, R k represents the measurement noise of the observation value of the receiver at time k;

[0094] S1022. When the fault detection verification amount is greater than the fault detection threshold, it is determined that a fault exists in the observation vector of the current epoch receiver; otherwise, it is determined that no fault exists in the observation vector of the current epoch receiver;

[0095] Optionally, the fault detection threshold may be determined based on the false alarm rate in the preset integrity risk requirement, or may be set or selected in other reasonable ways. The embodiment of the present application does not limit the setting method and selection range of the fault detection threshold.

[0096] In one implementation, the fault detection threshold is determined based on the false alarm rate in the preset integrity risk requirement and the number of vectors in the observation vector; wherein the false alarm rate satisfies the following formula:

[0097]

[0098] Among them, P fa Indicates the false alarm rate in the preset integrity risk; Represents the alternative hypothesis. Specifically, each faulty vector in the observation vector of the current epoch receiver corresponds to a fault mode. If the i-th vector in the observation vector of the current epoch receiver fails, the hypothesis is called the alternative hypothesis. represents the probability of each failure mode occurring, and m is the number of measurements; It can be given by a preset method or calculated by an average distribution method It is the identification threshold under different fault modes and can be set according to actual conditions;

[0099] S103, when it is determined that there is a fault in the observation vector of the current epoch receiver, the vectors in the observation vector of the current epoch receiver whose fault identification verification value is greater than the fault verification threshold are eliminated; otherwise, executing S105;

[0100] Exemplarily, the fault identification test quantity of each vector in the observation vector of the current epoch receiver is calculated by using the Barda data snooping method and the covariance matrix of the innovation vector of the current epoch receiver; the fault identification test quantity satisfies the following formula:

[0101]

[0102] Where k represents the current epoch, i represents the i-th vector in the observation vector of the current epoch receiver, T irepresents the fault identification test quantity of vector i; c i is a vector whose elements are all equal to 0 except the i-th element which is equal to 1. Indicates c i The transposed matrix, R k represents the measurement noise of the receiver's observation value at time k, Represents R k The inverse vector, r k represents the receiver's innovation vector at time k; P k|k-1 represents the predicted value of the state covariance matrix of the receiver at time k, Indicates H k The transposed matrix of :

[0103] It should be understood that the above obstacle recognition test quantity takes into account the covariance information of the innovation vector, and is therefore applicable to high-precision positioning models such as Real-Time Kinematic (RTK), Precise Point Positioning (PPP), and PPP-RTK.

[0104] S104. Determine the maximum number of faults for the receiver in the current epoch based on the preset integrity risk and the priori fault probability. If the number of vectors removed from the observation vector of the receiver in the current epoch is less than the maximum number of faults for the current epoch, update the observation vector of the receiver in the current epoch to the observation vector of the receiver after removing the vectors, and then return to executing S101-S104. Otherwise, execute S105.

[0105] Specifically, the above S104 includes S1041-S1044;

[0106] S1041. Determine multiple failure modes of the current epoch receiver;

[0107] Specifically, each failure of a vector in the observation vector of the current epoch receiver is corresponded to a failure mode; a failure of a vector means that the receiver fails to observe the navigation satellite corresponding to the vector, resulting in an observation error of the vector;

[0108] S1042. Under a preset integrity risk, allocate risk to each of the multiple failure modes to obtain a priori probability of occurrence of each of the multiple failure modes.

[0109] In one implementation, the prior probability of occurrence satisfies the following formula:

[0110]

[0111] Among them, P ap，irepresents the prior probability of occurrence of the i-th fault mode vector in the receiver’s observation vector, P obs，j represents the prior failure probability of the jth vector (i.e., the jth failure mode) in the receiver's observation vector; P obs，j Satisfy the following formula;

[0112]

[0113] Among them, P ap,sat N represents the prior failure probability of the navigation satellite corresponding to the jth vector in the receiver's observation vector, f 、N t Respectively represent the frequency number and observation type number of the navigation satellite;

[0114] S1043. Calculate the maximum number of failures of the receiver at the current epoch based on the a priori probability of occurrence of each failure mode among the multiple failure modes;

[0115] In one application scenario, the maximum number of faults satisfies the following formula:

[0116]

[0117] Among them, N max,fault represents the maximum number of failures, P i，thres represents the integrity risk threshold of the i-th failure mode that is not monitored;

[0118] In the embodiment of the present application, the above-mentioned prior failure probability and the above-mentioned integrity risk threshold are provided by the Integrity Support Message (ISM) proposed and published by the GPS Lab team of Stanford University, which is generally recognized in the art;

[0119] S1044. When the number of vectors removed from the observation vector of the current epoch receiver is less than the maximum number of faults in the current epoch, the observation vector of the current epoch receiver is updated to the observation vector of the receiver after the vectors are removed, and then the process returns to S101-S104; otherwise, the process proceeds to S105.

[0120] S105, using the state update model and the innovation vector of the current epoch receiver to determine the positioning result of the receiver;

[0121] Optionally, the state update model may be a measurement update module corresponding to a Kalman filter. Since the Kalman filter is a commonly used related technology in this technical field, the embodiment of the present application does not further describe the measurement update module of the Kalman filter.

[0122] Specifically, the above state update model satisfies the following formula:

[0123]

[0124] P k =(IK k H k )P k|k-1

[0125] Among them, k represents the current epoch, k-1 represents the epoch before the current epoch, and K k represents the receiver gain matrix at time k, P k|k-1 represents the predicted value of the receiver's state covariance matrix at time k, H k represents the observation matrix of the receiver at time k, Indicates H k The transposed matrix of R k represents the measurement noise of the observation value of the receiver at time k; represents the state vector of the receiver at time k after update, represents the predicted value of the change between the state vector of the receiver at time k-1 and the state vector of the receiver at time k, r k represents the receiver's innovation vector at time k; P k represents the state covariance matrix of the receiver at time k after update;

[0126] It can be understood that the state vector of the current epoch receiver obtained by the state update model is The input of the observation vector after integrity monitoring fault processing is obtained, so the reliability is increased. This process balances the information of the prior estimation and the actual observation, making the state vector of the current epoch receiver More reliable; specifically, the receiver's state vector gives the receiver's precise location, which can give the user equipment's precise location, thereby achieving precise positioning of the user equipment;

[0127] In summary, in a positioning method provided by an embodiment of the present application, the observation vector, observation equation and state prediction model of the current epoch receiver are first used to calculate the new information vector of the current epoch receiver, and then the observation vector of the current epoch receiver is subjected to fault analysis through the new information vector of the current epoch receiver; when it is determined that there is a fault in the observation vector of the current epoch receiver, the fault identification test value is used as a test index, and then the vectors in the observation vector whose fault identification test value is greater than the fault test threshold are eliminated, and after the vectors are eliminated, the number of eliminated vectors is limited by the maximum number of faults, so that the vectors finally retained in the observation vector not only have a certain accuracy, but also retain the redundancy of the observation vector, thereby improving the accuracy of GNSS positioning of the receiver through the observation vector.

[0128] In an application scenario, before S101, the above positioning method further includes S106.

[0129] S106: Construct an observation equation based on the pseudorange and carrier observation values ​​of the receiver.

[0130] The pseudorange is the pseudorange between the receiver and each of the multiple navigation satellites; and the carrier observation value is the carrier observation value between the receiver and each of the multiple navigation satellites.

[0131] Specifically, in one application scenario, the receiver samples the observation vector at a time interval of 1s (i.e., 1s is an epoch), and the recommended satellite cutoff elevation angle is 10° when constructing the observation equation. The constructed observation equation is suitable for multiple positioning services such as multi-frequency and multi-mode standard single point positioning (SPP), precise single point positioning (PPP), and real-time kinematic positioning (RTK).

[0132] Accordingly, the embodiment of the present application provides a positioning device, such as Figure 2 As shown, it includes an innovation vector determination module 501, a fault determination module 502, a removal module 503, a removal quantity determination module 504 and a positioning module 505.

[0133] Innovation vector determination module 501 is configured to determine the receiver innovation vector for the current epoch based on the receiver's observation vector, the receiver's observation equation, and a state prediction model. The observation equation describes the relationship between the receiver's observation vector and state vector, and the state prediction model predicts the receiver's state vector for the current epoch. The innovation vector is the difference between the receiver's observation vector for the current epoch and the predicted value of the receiver's state vector. For example, innovation vector determination module 501 is configured to implement step S101 of the aforementioned positioning method.

[0134] The fault determination module 502 is used to perform fault determination on the observation vector of the current epoch receiver according to the innovation vector of the current epoch receiver. For example, the fault determination module 502 is used to implement S102 of the above positioning method.

[0135] The elimination module 503 is configured to, if it is determined that a fault exists in the observation vectors of the current epoch receiver, eliminate vectors in the observation vectors of the current epoch receiver whose fault identification verification value exceeds the fault verification threshold; otherwise, the processing steps of the positioning module are executed. For example, the elimination module 503 is configured to implement S103 of the above-mentioned positioning method.

[0136] The rejection number determination module 504 is used to determine the maximum number of faults for the receiver in the current epoch based on a preset integrity risk and a priori fault probability. If the number of vectors to be rejected from the observation vector of the receiver in the current epoch is less than the maximum number of faults for the current epoch, the observation vector of the receiver in the current epoch is updated to the observation vector of the receiver after the rejection of the vectors. The processing steps of the innovation vector determination module, the fault determination module, the rejection module, and the rejection number determination module are then executed in sequence. Otherwise, the processing steps of the positioning module are executed. For example, the rejection number determination module 504 is used to implement S104 of the positioning method described above.

[0137] The positioning module 505 is used to determine the positioning result of the receiver using the state update model and the innovation vector of the receiver at the current epoch. For example, the positioning module 505 is used to implement S105 of the above positioning method.

[0138] Optionally, the fault determination module 502 is specifically configured to calculate a fault detection check value for the current epoch receiver based on the innovation vector of the current epoch receiver. When the fault detection check value is greater than a fault detection threshold, it is determined that a fault exists in the observation vector of the current epoch receiver; otherwise, it is determined that no fault exists in the observation vector of the current epoch receiver. For example, the fault determination module 502 is specifically configured to implement S1021-S1022 of the aforementioned positioning method.

[0139] In one implementation, the positioning device further includes an observation equation determination module 506 .

[0140] The observation equation determination module 506 is configured to construct an observation equation based on the pseudorange and carrier observation values ​​of the receiver. The pseudorange is the pseudorange between the receiver and each of the plurality of navigation satellites, and the carrier observation value is the carrier observation value between the receiver and each of the plurality of navigation satellites. For example, the observation equation determination module 506 is configured to implement step S106 of the positioning method described above.

[0141] Each module of the positioning device can also be used to execute other steps in the method embodiment. All relevant contents involved in the method embodiment can be referred to the functional description of the corresponding functional module and will not be repeated here.

[0142] The present application also provides an electronic device, including: a processor and a memory coupled to the processor; the memory is used to store computer instructions, and when the electronic device is running, the processor executes the computer instructions stored in the memory, so that the electronic device performs the method described in the above embodiment. The processor can implement the above-mentioned innovation vector determination module 501, fault determination module 502, elimination module 503, elimination quantity determination module 504, positioning module 505, and observation equation determination module 506; the above-mentioned memory can also be used to store the observation vector, innovation vector, fault identification verification value, maximum fault number, and positioning result of the receiver at the current epoch.

[0143] An embodiment of the present application further provides a computer-readable storage medium, which includes a computer program. When the computer program runs on a computer, the method described in the above embodiment is executed.

[0144] An embodiment of the present application further provides a computer program product, which includes computer program instructions. When the computer program instructions are run on a computer, the method described in the above embodiment is executed.

[0145] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments.

[0146] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A positioning method, characterized in that: include: S101. Determine an innovation vector of the receiver at the current epoch based on an observation vector of the receiver at the current epoch, an observation equation of the receiver, and a state prediction model; wherein the observation equation is used to describe the relationship between the observation vector and the state vector of the receiver, and the state prediction model is used to predict the state vector of the receiver at the current epoch; and the innovation vector is the difference between the observation vector of the receiver at the current epoch and the predicted value of the state vector of the receiver; The observation equation satisfies the following formula: z=H·X+v Where z represents the observation vector, and f represents frequency, S represents satellite, represents the pseudorange of satellite S at frequency f, represents the carrier observation value of satellite S at frequency f, represents the geometric distance between the receiver and the navigation satellite calculated based on the approximate coordinates of the receiver, represents the ionospheric delay, T S represents the tropospheric delay, D orb represents the satellite orbit error; H represents the observation matrix, and represents the symbol of partial derivative, λ f represents the wavelength of the carrier observation at frequency f; X represents the state vector, and X r represents the coordinate of the receiver on the x-axis of the ECEF coordinate system, Y r represents the coordinate of the receiver on the y-axis of the ECEF coordinate system, Z r represents the coordinate of the receiver on the z-axis of the ECEF coordinate system, Δt r represents the receiver clock error, c represents the speed of light, represents the whole-cycle ambiguity; v represents the observation noise vector, and is the measurement noise of pseudorange, is the measured noise of the carrier S102, performing a fault determination on the observation vector of the receiver at the current epoch according to the innovation vector of the receiver at the current epoch; S103, when it is determined that there is a fault in the observation vector of the receiver in the current epoch, removing the vectors in the observation vector of the receiver in the current epoch whose fault identification verification value is greater than the fault verification threshold; otherwise, executing S105; The fault identification test quantity satisfies the following formula: Where k represents the current epoch, i represents the i-th vector in the observation vector of the receiver at the current epoch, T i represents the fault identification test quantity of vector i; c i is a vector whose elements are all equal to 0 except the i-th element which is equal to 1. Indicates c i The transposed matrix, R k represents the measurement noise of the observation value of the receiver at time k, Represents R k The inverse vector, r k represents the innovation vector of the receiver at time k; P k|k-1 represents the predicted value of the state covariance matrix of the receiver at time k, Indicates H k The transposed matrix of S104. Determine the maximum number of failures of the receiver in the current epoch based on the preset integrity risk and the prior failure probability. If the number of vectors removed from the observation vector of the receiver in the current epoch is less than the maximum number of failures in the current epoch, update the observation vector of the receiver in the current epoch to the observation vector of the receiver after removing the vectors, and then return to S101-S104. Otherwise, execute S105. S105 : Determine a positioning result of the receiver using a state update model and an innovation vector of the receiver at a current epoch.

2. The method according to claim 1, wherein The state prediction model satisfies the following formula: Among them, k represents the current epoch, k-1 represents the epoch before the current epoch, represents the predicted value of the change between the state vector of the receiver at time k-1 and the state vector of the receiver at time k, Φ k|k-1 represents the state transition matrix of the receiver from k-1 to k, represents the observation value of the state vector of the receiver at time k-1, P k|k-1 represents the predicted value of the state covariance matrix of the receiver at time k, P k-1 represents the state covariance matrix of the receiver at time k-1, Q k represents the covariance matrix of the process noise of the receiver at time k; The innovation vector satisfies the following formula: Among them, r k represents the receiver's innovation vector at time k, z k represents the observed value of the state vector of the receiver at time k, H k represents the observation matrix of the receiver at time k, represents the predicted value of the receiver's state vector at time k.

3. The method according to claim 1, wherein The performing fault determination on the observation vector of the receiver at the current epoch according to the innovation vector of the receiver at the current epoch includes: Calculate the fault detection test quantity of the receiver in the current epoch according to the innovation vector of the receiver in the current epoch; the fault detection test quantity of the receiver satisfies the following formula; Among them, T g represents the fault detection verification quantity of the receiver, and T g Obeys chi-square distribution; k represents the current epoch, r k represents the receiver's innovation vector at time k, Represents r k The transposed matrix of H k represents the observation matrix of the receiver at time k, P k|k-1 represents the predicted value of the state covariance matrix of the receiver at time k, Indicates H k The transposed matrix, R k represents the measurement noise of the observation value of the receiver at time k; When the fault detection check value is greater than the fault detection threshold, it is determined that a fault exists in the observation vector of the receiver in the current epoch; otherwise, it is determined that no fault exists in the observation vector of the receiver in the current epoch.

4. The method according to claim 1, wherein The state update model satisfies the following formula: P k =(I-K k H k )P k|k -1 Among them, k represents the current epoch, k-1 represents the epoch before the current epoch, and K k represents the gain matrix of the receiver at time k, P k|k-1 represents the predicted value of the state covariance matrix of the receiver at time k, H k represents the observation matrix of the receiver at time k, Indicates H k The transposed matrix of R k represents the measurement noise of the observation value of the receiver at time k; represents the state vector of the receiver at time k after update, represents the predicted value of the change between the state vector of the receiver at time k-1 and the state vector of the receiver at time k, r k represents the receiver's innovation vector at time k; P k represents the state covariance matrix of the receiver at time k after update.

5. The method according to claim 1, wherein Before S101, the method further includes: S106. Construct an observation equation based on the pseudorange and carrier observation value of the receiver; wherein the pseudorange is the pseudorange between the receiver and each navigation satellite in the multiple navigation satellites; and the carrier observation value is the carrier observation value between the receiver and each navigation satellite in the multiple navigation satellites.

6. A positioning device for implementing the method according to claim 1, characterized in that: It includes an innovation vector determination module, a fault determination module, a rejection module, a rejection quantity determination module, and a positioning module; The innovation vector determination module is configured to determine an innovation vector of the receiver at the current epoch based on an observation vector of the receiver at the current epoch, an observation equation of the receiver, and a state prediction model; wherein the observation equation is configured to describe a relationship between the observation vector and the state vector of the receiver, and the state prediction model is configured to predict the state vector of the receiver at the current epoch; and the innovation vector is a difference between the observation vector of the receiver at the current epoch and a predicted value of the state vector of the receiver; The fault determination module is configured to perform fault determination on the observation vector of the receiver at the current epoch based on the innovation vector of the receiver at the current epoch; The elimination module is configured to, if it is determined that a fault exists in the observation vector of the receiver in the current epoch, eliminate vectors in the observation vector of the receiver in the current epoch whose fault identification verification value is greater than a fault verification threshold; otherwise, execute the processing steps of the positioning module; The elimination number determination module is configured to determine the maximum number of failures of the receiver in the current epoch based on a preset integrity risk and a priori failure probability; when the number of vectors eliminated in the observation vector of the receiver in the current epoch is less than the maximum number of failures in the current epoch, update the observation vector of the receiver in the current epoch to the observation vector of the receiver after the elimination of the vector, and then sequentially execute the processing steps of the innovation vector determination module, the fault determination module, the elimination module, and the elimination number determination module; otherwise, execute the processing steps of the positioning module; The positioning module is used to determine the positioning result of the receiver by using a state update model and an innovation vector of the receiver at a current epoch.

7. An electronic device, characterized in that: The electronic device comprises a processor and a memory coupled to the processor; the memory is used to store computer instructions, and when the electronic device is running, the processor executes the computer instructions stored in the memory, so that the electronic device executes the method as claimed in claim 1.

8. A computer-readable storage medium, characterized in that The method comprises computer program instructions which, when executed by a computer, cause the computer to perform the method as claimed in claim 1 .

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