Single point positioning method, electronic device, readable storage medium and chip

Abstract

The application provides a single point positioning method, an electronic device, a readable storage medium and a chip. The single point positioning method first obtains observation data of multiple satellites at multiple frequency points, and respectively performs non-combination single point positioning calculation operation and ionosphere-free combination single point positioning calculation operation to obtain different calculation results and the corresponding post-processing residual error of each observation data. Secondly, the respective post-processing residual error is clustered to accurately identify and classify error sources, and the optimal target residual error group is selected. Finally, based on the optimal first target residual error group corresponding to the non-combination single point positioning calculation operation and the optimal second target residual error group corresponding to the ionosphere-free combination single point positioning calculation operation, the target position of the receiver is determined, so that in the complex environment where the ionosphere is active or the multipath effect is significant, high-precision positioning results can still be output. The method improves the accuracy of positioning, has significant practical value and popularization significance.

Description

Technical Field

[0001] This application relates to the field of positioning technology, and in particular to a single-point positioning method, electronic device, readable storage medium, and chip. Background Technology

[0002] The BeiDou Navigation Satellite System (BDS) is a global navigation satellite system (GNSS) independently developed by my country. With the completion of its global network, the BDS has been widely applied across various industries. Compared to multi-system fusion positioning, single-BDS positioning offers independence and autonomy while significantly reducing computational load. Therefore, the widespread adoption of single-BDS positioning is crucial in important scenarios and facilities such as national defense, power, and communications.

[0003] In related technologies, when performing pseudorange point positioning based on a single BeiDou system, ionospheric errors are typically handled in two ways: one is to use ionospheric model correction to correct the pseudorange for ionospheric effects, and the other is to use dual-frequency observation data for ionospheric-free combination to eliminate the influence of the ionosphere. However, when the ionosphere is highly active, the ionospheric model correction cannot accurately match the actual ionospheric correction, resulting in a large ionospheric correction error in the pseudorange, ultimately leading to a large point positioning error. When the observation environment is poor, there will be a large multipath error in the pseudorange, and the ionospheric-free combination will further amplify the multipath error, resulting in a large point positioning error. Therefore, it can be seen that existing pseudorange point positioning based on a single BeiDou system suffers from large positioning errors in both of these situations. Summary of the Invention

[0004] This application provides a single-point positioning method, electronic device, readable storage medium, and chip to solve the problem of large positioning errors in existing pseudorange single-point positioning based on BeiDou.

[0005] In a first aspect, this application provides a single-point positioning method, comprising: acquiring multiple observation data; wherein, the multiple observation data includes observation data obtained by a receiver measuring carrier signals transmitted by multiple satellites at multiple frequency points respectively;

[0006] Based on the multiple observation data, a non-combined single-point positioning solution operation is performed to obtain the first position and the first receiver clock error;

[0007] Based on the first position, the first receiver clock error, and the plurality of observation data, a first posterior residual calculation operation is performed to obtain a plurality of first posterior residuals; wherein, the plurality of first posterior residuals correspond one-to-one with the plurality of observation data;

[0008] Based on the multiple observation data, perform an ionospherically-free combined single-point positioning calculation to obtain the second position and the second receiver clock difference;

[0009] Based on the second position, the second receiver clock error, and the plurality of observation data, a second posterior residual calculation operation is performed to obtain a plurality of second posterior residuals; wherein, the plurality of second posterior residuals correspond one-to-one with the plurality of observation data;

[0010] Data clustering is performed on the plurality of first posterior residuals to obtain a plurality of first residual groups, and a first target residual group is determined based on the cluster centers of the plurality of first residual groups;

[0011] Data clustering is performed on the plurality of second posterior residuals to obtain a plurality of second residual groups, and a second target residual group is determined based on the cluster centers of the plurality of second residual groups;

[0012] The target position of the receiver is determined based on the first target residual group and the second target residual group; wherein the target position is either the first position or the second position.

[0013] In one possible design, determining the target location of the receiver based on the first target residual group and the second target residual group includes:

[0014] The number of first posterior residuals, the mean of first distances, and the variance of first distances corresponding to the first target residual group are determined; wherein, the mean of first distances is the average of the first distances corresponding to the first posterior residuals in the first target residual group; the variance of first distances is the variance of the first distances corresponding to the first posterior residuals in the first target residual group; and the first distance corresponding to the first posterior residual is the sum of the absolute values ​​of the differences between the first posterior residual and other first posterior residuals among the plurality of first posterior residuals.

[0015] Determine the number of second posterior residuals, the mean of second distances, and the variance of second distances corresponding to the second target residual group; wherein, the mean of second distances is the average of the second distances corresponding to the second posterior residuals in the second target residual group; the variance of second distances is the variance of the second distances corresponding to the second posterior residuals in the second target residual group; and the second distance corresponding to the second posterior residual is the sum of the absolute values ​​of the differences between the second posterior residual and the other second posterior residuals among the plurality of second posterior residuals.

[0016] If the ratio of the number of second posterior residuals corresponding to the second target residual group to the number of first posterior residuals corresponding to the first target residual group is greater than a preset ratio, the second distance mean is less than the first distance mean, and the second distance variance is less than the first distance variance, then the second position is determined to be the target position of the receiver.

[0017] If at least one of the following conditions is met: the ratio of the number of second posterior residuals corresponding to the second target residual group to the number of first posterior residuals corresponding to the first target residual group is less than or equal to the preset ratio; the second distance mean is greater than or equal to the first distance mean; and the second distance variance is greater than or equal to the first distance variance, the first position is determined to be the target position of the receiver.

[0018] In one possible design, the step of performing a non-combined single-point localization calculation based on the multiple observation data to obtain a first position and a first receiver clock error includes:

[0019] For each of the plurality of observation data, a non-combined single-point positioning observation equation is established corresponding to the observation data; wherein, the non-combined single-point positioning observation equation satisfies:

[0020]

[0021] i represents the sequence number of the observed data among the multiple observed data, P i Let (X) represent the pseudorange corresponding to the i-th observation data. i S ,Y i S Z i S (x1, y1, z1) represents the coordinates of the satellite corresponding to the i-th observation data, (x1, y1, z1) represents the first position, and t r1 t represents the clock bias of the first receiver. si I represents the distance correction caused by the satellite clock error of the satellite corresponding to the i-th observation data. i T represents the ionospheric delay correction corresponding to the i-th observation data. i ε represents the tropospheric delay correction corresponding to the i-th observation data. i This represents the noise value and the error term caused by multipath error of the i-th observation data;

[0022] The Kalman filter algorithm or the least squares method is used to process the multiple non-combined single-point positioning observation equations corresponding to the multiple observation data to obtain the first position and the first receiver clock error.

[0023] In one possible design, the first posterior residual calculation operation is performed based on the first position, the first receiver clock error, and the plurality of observation data to obtain a plurality of first posterior residuals, including:

[0024] For each of the plurality of observation data, based on the first position, the first receiver clock error and the observation data, the first posterior residual corresponding to the observation data is obtained using the non-combined pseudorange posterior residual calculation formula, and then the plurality of first posterior residuals corresponding to the plurality of observation data are obtained.

[0025] The formula for calculating the posterior residual of the non-combined pseudorange is as follows:

[0026]

[0027] res i It represents the first posterior residual corresponding to the i-th observation data.

[0028] In one possible design, the step of performing an ionospherically-free combined single-point localization calculation based on the multiple observation data to obtain a second position and a second receiver clock error includes:

[0029] For the observation data of the same satellite at two frequency points from the multiple observation data, establish the ionosphere-free combined single-point positioning observation equation corresponding to the observation data at the two frequency points; wherein, the ionosphere-free combined single-point positioning observation equation is:

[0030]

[0031] i and j represent the sequence numbers of the observation data at the two frequency points in the plurality of observation data, P LC ( i,j (X) represents the pseudorange calculated based on the i-th and j-th observation data through a combination without an ionosphere. i S ,Y i S Z i S (x2, y2, z2) represents the coordinates of the satellite corresponding to the i-th observation data, (x2, y2, z2) represents the second position, and t r2 t represents the clock bias of the second receiver. si T represents the distance correction caused by the satellite clock error of the satellite corresponding to the i-th observation data. i ε represents the tropospheric delay correction corresponding to the i-th observation data. i This represents the noise value and the error term caused by multipath error of the i-th observation data;

[0032] The Kalman filter algorithm or the least squares method is used to process the multiple single-point positioning observation equations corresponding to the multiple observation data to obtain the second position and the second receiver clock error.

[0033] In one possible design, the second posterior residual calculation operation based on the second position, the second receiver clock error, and the plurality of observation data, to obtain a plurality of second posterior residuals, includes:

[0034] For each of the multiple observation data, based on the second position, the second receiver clock error and the observation data, the second posterior residual corresponding to the observation data is obtained using the formula for calculating the posterior residual of the ionosphere-free combined pseudorange, and then multiple second posterior residuals corresponding to the multiple observation data are obtained.

[0035] The formula for calculating the posterior residual of the pseudo-range of the ionosphere-free combination is as follows:

[0036]

[0037] res LCi It represents the second posterior residual corresponding to the i-th observation data.

[0038] In one possible design, data clustering is performed on the posterior residuals of multiple objectives to obtain multiple objective residual groups, including:

[0039] For each target posterior residual, determine the target distance corresponding to the target posterior residual; wherein, the target posterior residual is the first posterior residual, and the target distance is the first distance corresponding to the first posterior residual; or, the target posterior residual is the second posterior residual, and the target distance is the second distance corresponding to the second posterior residual; the first distance is the sum of the absolute values ​​of the differences between the first posterior residual and other first posterior residuals; the second distance is the sum of the absolute values ​​of the differences between the second posterior residual and other second posterior residuals;

[0040] Multiple target cluster centers are determined based on the multiple target posterior residuals; wherein, the target cluster center is either a first cluster center or a second cluster center;

[0041] Clustering is performed on the distances between the multiple targets based on the multiple target cluster centers to obtain the target clustering results;

[0042] The plurality of target cluster centers are updated according to the target clustering results, and the clustering of the plurality of target distances based on the plurality of target cluster centers is returned. The process is iterated until the clustering convergence condition is met, and a plurality of target residual groups are obtained; wherein the target residual group is either the first residual group or the second residual group.

[0043] In a second aspect, this application provides an electronic device, including: a memory and a processor;

[0044] The memory is configured to store computer program instructions;

[0045] The processor is configured to execute the computer program instructions, causing the electronic device to implement the single-point positioning method described in any of the first aspects above.

[0046] Thirdly, this application provides a computer-readable storage medium, including: computer program instructions;

[0047] At least one processor of the electronic device executes the computer program instructions, causing the electronic device to implement the single-point positioning method described in any of the first aspects above.

[0048] Fourthly, this application provides a chip, including: an interface circuit and a logic circuit, wherein the interface circuit is used to receive signals from other chips outside the chip and transmit them to the logic circuit, or to send signals from the logic circuit to other chips outside the chip, and the logic circuit is used to implement the single-point positioning method described in any of the first aspects above.

[0049] In this embodiment, firstly, observation data from multiple satellites at multiple frequency points are acquired, and non-combined single-point positioning calculation operations and ionospherically-free combined single-point positioning calculation operations are performed respectively to obtain different calculation results and their corresponding posterior residuals for each observation data point. Secondly, by clustering the respective posterior residuals, error sources are accurately identified and classified, and the optimal target residual group is selected. Finally, based on the optimal first target residual group corresponding to the non-combined single-point positioning calculation operation and the optimal second target residual group corresponding to the ionospherically-free combined single-point positioning calculation operation, the target position of the receiver is determined, thereby ensuring that high-precision positioning results can still be output even in complex environments with active ionosphere or significant multipath effects. This single-point positioning method improves positioning accuracy and has significant practical value and promotional significance. Attached Figure Description

[0050] Figure 1 A flowchart illustrating a single-point positioning method provided in an embodiment of this application;

[0051] Figure 2A flowchart illustrating another single-point positioning method provided in an embodiment of this application;

[0052] Figure 3 This is a schematic diagram of the structure of a single-point positioning device provided in an embodiment of this application;

[0053] Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0054] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0055] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the terminology used herein in the specification of the application is for the purpose of describing particular embodiments only and is not intended to limit the application; the terms “comprising” and “having”, and any variations thereof, in the specification, claims and drawings of this application are intended to cover non-exclusive inclusion.

[0056] The term "embodiment" as used herein means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of the phrase "embodiment" in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0057] In this article, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can mean: A exists, A and B exist simultaneously, or B exists. Additionally, the character " / " in this article generally indicates that the preceding and following related objects have an "or" relationship.

[0058] Furthermore, the terms "first," "second," etc., in the specification and claims of this application or in the aforementioned drawings are used to distinguish different objects rather than to describe a specific order, and may explicitly or implicitly include one or more of the features.

[0059] In the description of this application, unless otherwise stated, "multiple" means two or more (including two), and similarly, "multiple groups" means two or more (including two groups).

[0060] Multi-GNSS Integration Positioning refers to a method of positioning using satellite signals from multiple Global Navigation Satellite Systems (GNSS). Major GNSS systems include the US Global Positioning System (GPS), Russia's Global Navigation Satellite System (GNSS), Europe's Global Navigation Satellite System (GNSS), and China's BeiDou Navigation Satellite System (BDS). By integrating signals from multiple GNSS systems, multi-GNSS integration positioning significantly improves positioning accuracy, reliability, and availability.

[0061] With the completion of the BeiDou Navigation Satellite System (BDS) global network, BDS has been widely applied across various industries. The promotion of BDS is crucial in important scenarios and facilities such as national defense, power, and communications, providing more independent and secure positioning and timing services. Compared to multi-system fusion positioning, BDS significantly reduces computational load, providing a foundation for the operation of dual filters.

[0062] When performing pseudorange point positioning based on the BeiDou Navigation Satellite System (BDS), ionospheric errors are generally handled in two ways: one is to use ionospheric model correction to correct the pseudorange for ionospheric effects, and the other is to use dual-frequency observation data for ionospheric-free combination to eliminate the influence of the ionosphere. Each method has its advantages and disadvantages. When the ionosphere is active, the ionospheric model correction cannot accurately match the actual ionospheric correction, resulting in a large ionospheric correction error in the pseudorange, ultimately leading to a large point positioning error. Furthermore, when the observation environment is poor, there will be a large multipath error in the pseudorange. Ionospheric-free combination will further amplify this multipath error. Also, when one frequency has a smaller error than the other, in non-combined mode, the observation data from one frequency can be used for positioning, while the other frequency is discarded through quality control. However, in combined mode, the observation data from both frequencies are unusable, resulting in a smaller number of usable observation data points, which significantly impacts the positioning results.

[0063] Multipath error refers to the positioning error introduced when the BDS signal is reflected or refracted by the ground, buildings, water surfaces, etc., before reaching the receiver antenna, causing changes in the BDS signal path. Multipath error is one of the main factors affecting BDS positioning accuracy, especially in urban environments, high mountains and canyons, and other scenarios with many reflective surfaces.

[0064] It's important to note that the ionosphere, a region in Earth's atmosphere rich in ions and free electrons, causes a delay in BDS signals passing through it. This delay becomes particularly pronounced during periods of high solar activity due to significant variations in the ionosphere's electron density. The basic principle of ionospheric model correction is to use a pre-built ionospheric model to calculate and correct for the delay error caused by the ionosphere in the BDS signal. However, when the ionosphere is highly active, ionospheric model correction cannot accurately match the actual ionospheric correction, resulting in larger ionospheric correction errors in the pseudorange and ultimately, larger single-point positioning errors.

[0065] The ionosphere affects BDS signals at different frequencies differently. Ionosphere-free combination, through linear combination of dual-frequency observation data, eliminates the delay effect of the ionosphere on the BDS signal, thereby offsetting ionospheric delay errors and improving positioning accuracy, making it suitable for high-precision positioning requirements. In environments with significant multipath effects, multipath errors are amplified after dual-frequency combination, affecting positioning accuracy. Furthermore, when the error at one of the two frequencies is large, the quality of the combined observation data is affected, impacting the positioning results.

[0066] In summary, multipath error and ionospheric error are the two main sources of error in BDS positioning, especially in complex environments and when ionospheric activity is frequent, significantly impacting positioning accuracy. Common methods for addressing ionospheric error include ionospheric model correction and dual-frequency ionospheric-free combination. Ionospheric model correction is simple and easy to implement, but its accuracy is low when the ionosphere is active. Dual-frequency ionospheric-free combination can effectively eliminate ionospheric error, but it requires dual-frequency receivers, and the combined error may be amplified when multipath effects are significant. Therefore, in practical applications, selecting an appropriate ionospheric error handling method based on the current environment is crucial.

[0067] Chinese invention patent application number 202310886370.9, entitled "Positioning Method, Device, Equipment and Storage Medium Based on Dual-Frequency Signals," proposes a simple and easy-to-implement method for determining ionospheric activity. During periods of ionospheric activity, the method automatically enters either an ionospheric-free combined positioning mode or an ionospheric-free combined positioning mode plus L1 combined positioning mode to improve positioning accuracy. The steps are as follows: Based on the current positioning environment, a target positioning mode is determined from multiple positioning modes; according to the target positioning mode, the first calculated frequency point position observation and the first calculated frequency point clock difference clk1, as well as the second calculated frequency point position observation and the second calculated frequency point clock difference clk2, are determined; based on the first calculated frequency point position observation and the first calculated frequency point clock difference clk1, the second calculated frequency point position observation and the second calculated frequency point clock difference clk2, positioning calculation is performed to obtain the positioning result.

[0068] It should be noted that the aforementioned patent judges ionospheric activity by statistically analyzing the proportion of times the difference between pseudoranges of two frequencies of the same satellite exceeds different thresholds. However, in some obstructed scenarios, the environmental influence on pseudoranges of different frequencies may be inconsistent, making it easy to misjudge a scenario as an ionospherically active one. In such cases, incorrectly performing positioning calculations without ionospheric combinations will only further worsen the positioning results.

[0069] To address the problems existing in related technologies, this application designs a dual-filter architecture. It simultaneously performs positioning calculations on observation data from multiple satellites at multiple frequency points using both non-combined single-point positioning and ionospherically-free combined single-point positioning operations. Each positioning result is used to inversely calculate all pseudorange posterior residuals, and then a clustering algorithm is applied to cluster all posterior residuals. The quality of the two results is judged by comparing the cluster with the highest aggregation degree, ultimately outputting a better positioning result. This application directly determines whether the non-combined or ionospherically-free combined positioning result is better by comparing the positioning results, avoiding misjudgments of ionospheric activity in obstructed scenarios, and has significant practical value and promotional significance.

[0070] Figure 1 This is a flowchart illustrating a single-point positioning method provided in an embodiment of this application. The single-point positioning method in this embodiment can be executed by a controller. Figure 1 As shown, the single-point positioning method includes S101 to S108, and S101 to S108 will be described in detail below.

[0071] S101, the controller acquires multiple observation data.

[0072] The controller acquires multiple observation data, which are obtained by the receiver measuring carrier signals transmitted by multiple satellites at multiple frequency points in one epoch.

[0073] An epoch refers to the moment when the controller acquires observation data.

[0074] For any one of the multiple satellites, the receiver can obtain multiple observation data by measuring the carrier signals transmitted by the satellite at multiple frequency points, and the multiple observation data correspond one-to-one with the multiple frequency points.

[0075] It should be noted that any observation data may include: pseudorange observation data, carrier phase observation data, Doppler observation data, and signal-to-noise ratio data calculated by the receiver based on the received satellite signals.

[0076] Pseudorange observation data refers to the distance between a receiver and a satellite calculated by measuring the propagation time of the satellite signal from the satellite to the receiver. Because this measurement includes various errors (such as satellite clock error, receiver clock error, atmospheric delay, etc.), it is not a true geometric distance.

[0077] Carrier phase observation data is precise distance information obtained by the receiver by measuring the phase change of the BDS signal carrier. Since the wavelength of the carrier signal is shorter than that of the pseudorange signal, carrier phase observation can provide higher positioning accuracy.

[0078] Doppler observation data is the relative velocity information between the receiver and the satellite obtained by measuring the Doppler effect at the frequency of the BDS signal. The Doppler effect is the change in signal frequency caused by the relative motion between the satellite and the receiver.

[0079] The controller acquires multiple observation data and also acquires the ephemeris data of each satellite in the current epoch.

[0080] It should be noted that for any given satellite among multiple satellites, its ephemeris data is a set of parameters broadcast by the satellite regarding its position in space. Based on these parameters, the satellite's precise position in space over a given period can be calculated, i.e., its exact satellite position. Furthermore, the satellite's clock bias can also be calculated using these parameters.

[0081] Satellite clock bias refers to the time deviation between the satellite clock and a reference clock. The reference clock is usually an atomic clock at the ground control center. Since BDS positioning calculates distance (pseudorange) by measuring the propagation time of the signal from the satellite to the receiver, the existence of satellite clock bias will cause errors in pseudorange measurement, thus affecting positioning accuracy.

[0082] S102, The controller performs a non-combined single-point positioning calculation operation based on multiple observation data to obtain the first position and the first receiver clock error.

[0083] Non-combined single-point positioning solution refers to positioning solution using observation data from a single frequency band without multi-frequency combination or differential processing.

[0084] It should be noted that the controller performs non-combined single-point positioning calculation based on multiple observation data, which can obtain the receiver's first position and first receiver clock error, laying the foundation for subsequent more accurate positioning processing and providing a positioning result for the receiver.

[0085] S103, the controller performs a first posterior residual calculation operation based on the first position, the first receiver clock error and multiple observation data to obtain multiple first posterior residuals.

[0086] Among them, multiple first posterior residuals correspond one-to-one with multiple observation data.

[0087] For each observation data in the multiple observation data, the first theoretical pseudorange between the receiver and the satellite corresponding to the observation data is calculated based on the first position and the satellite position of the satellite corresponding to the observation data; and based on the first theoretical pseudorange between the receiver and the satellite corresponding to the observation data, and the actual pseudorange corresponding to the observation data, the difference between the first theoretical pseudorange and the actual pseudorange corresponding to the observation data is obtained.

[0088] It should be noted that the actual pseudorange corresponding to the observed data is the pseudorange represented by the pseudorange observed data included in the observed data. The difference between the first theoretical pseudorange and the actual pseudorange corresponding to each observed data is the first posterior residual of each observed data.

[0089] S104. The controller performs a single-point positioning calculation operation without ionosphere based on multiple observation data to obtain the second position and the second receiver clock difference.

[0090] Among them, the ionospheric-free combined single-point positioning solution uses observation data from any one of multiple satellites at two different frequency points to eliminate ionospheric errors, which can effectively reduce the influence of the ionosphere on the BDS signal and improve positioning accuracy.

[0091] It should be noted that the controller performs a single-point positioning calculation operation without ionosphere based on multiple observation data, which can obtain the receiver's second position and second receiver clock error, laying the foundation for more accurate positioning processing and providing an alternative positioning result for the receiver.

[0092] S105, the controller performs a second posterior residual calculation operation based on the second position, the second receiver clock error and multiple observation data to obtain multiple second posterior residuals.

[0093] Among them, multiple second posterior residuals correspond one-to-one with multiple observation data.

[0094] For each observation data in the multiple observation data, the second theoretical pseudorange between the receiver and the satellite corresponding to the observation data is calculated based on the second position and the satellite position of the satellite corresponding to the observation data; and based on the second theoretical pseudorange between the receiver and the satellite corresponding to the observation data, and the actual pseudorange corresponding to the observation data, the difference between the second theoretical pseudorange and the actual pseudorange corresponding to the observation data is obtained.

[0095] It should be noted that the actual pseudorange corresponding to the observed data is the pseudorange represented by the pseudorange observed data included in the observed data. The difference between the second theoretical pseudorange and the actual pseudorange corresponding to each observed data is the second posterior residual of each observed data.

[0096] S106. The controller performs data clustering processing on multiple first posterior residuals to obtain multiple first residual groups, and determines the first target residual group based on the cluster centers of the multiple first residual groups.

[0097] The controller divides the multiple first posterior residuals into multiple first residual groups based on the characteristics of the multiple first posterior residuals, and determines the first target residual group from the multiple first residual groups by using the typical values ​​of the multiple first residual groups.

[0098] It should be noted that the number of the first residual groups can be set by the system developer, and this embodiment does not impose any specific limitations on this.

[0099] For example, the number of the first residual groups can be two.

[0100] It should be noted that the typical value of the first residual group is the cluster center of the first residual group. The first target residual group is the first residual group with the smallest cluster center among multiple first residual groups.

[0101] S107. The controller performs data clustering processing on multiple second posterior residuals to obtain multiple second residual groups, and determines the second target residual group based on the cluster centers of the multiple second residual groups.

[0102] The controller divides the multiple second posterior residuals into multiple second residual groups based on the characteristics of the multiple second posterior residuals, and determines the second target residual group from the multiple second residual groups by using the typical values ​​of the multiple second residual groups.

[0103] It should be noted that the number of the second residual groups can be set by the system developer, and this embodiment does not impose any specific limitations on this.

[0104] For example, the number of second residual groups can be two.

[0105] It should be noted that the typical value of the second residual group is the cluster center of the second residual group. The second target residual group is the second residual group with the smallest cluster center among multiple second residual groups.

[0106] S108, The controller determines the target position of the receiver based on the first target residual group and the second target residual group.

[0107] The target position is either the first position or the second position.

[0108] It should be noted that when executing this single-point positioning method, the steps can be executed in the order described above, or after S101, S104 and S105 can be executed sequentially first, followed by S102 and S103; or S104, S105 and S107 can be executed sequentially first, followed by S102, S103 and S106. This embodiment does not impose specific limitations on these steps.

[0109] In this embodiment, firstly, observation data from multiple satellites at multiple frequency points are acquired, and non-combined single-point positioning calculation operations and ionospherically-free combined single-point positioning calculation operations are performed respectively to obtain different calculation results and their posterior residuals. Secondly, by clustering the respective posterior residuals, error sources are accurately identified and classified, and the optimal target residual group is selected. Finally, based on the optimal first target residual group corresponding to the non-combined single-point positioning calculation operation and the optimal second target residual group corresponding to the ionospherically-free combined single-point positioning calculation operation, the target position of the receiver is determined, thereby ensuring that high-precision positioning results can still be output even in complex environments with active ionosphere or significant multipath effects. This single-point positioning method improves positioning accuracy and has significant practical value and promotional significance.

[0110] In the above embodiments, the controller needs to determine the target position of the receiver based on the first target residual group and the second target residual group. The specific process by which the controller determines the target position of the receiver based on the first target residual group and the second target residual group will be described in detail below.

[0111] Figure 2 This is a flowchart illustrating another single-point positioning method provided in an embodiment of this application. Figure 2 As shown, in one possible embodiment, S108, the controller determines the target position of the receiver based on the first target residual group and the second target residual group, which can be implemented by S1081 to S1084 in this embodiment. S1081 to S1084 are described in detail below.

[0112] S1081, The controller determines the number of first posterior residuals, the first distance mean, and the first distance variance corresponding to the first target residual group.

[0113] Wherein, the first distance mean is the average of the first distances corresponding to the first posterior residuals in the first target residual group; the first distance variance is the variance of the first distances corresponding to the first posterior residuals in the first target residual group.

[0114] The first distance corresponding to the first posterior residual is the sum of the absolute values ​​of the differences between the first posterior residual and the other first posterior residuals among the multiple first posterior residuals.

[0115] It should be noted that, for the i-th first posterior residual among multiple first posterior residuals in the first objective residual group, the first distance corresponding to the i-th first posterior residual is sum. i .

[0116] sum i =|res i -res1|+…+|res i -res i-1 |+|res i -res i+1 |+…+|res i -res n |. Where i and n are both positive integers, and 1≤i≤n, n is the total number of first posterior residuals; 1≤n≤M, M is the total number of observation data.

[0117] It should be noted that the first distance mean is the average of all first distances corresponding to all first posterior residuals in the first target residual group. The first distance variance is the variance of all first distances corresponding to all first posterior residuals in the first target residual group. The calculation methods for the first distance mean and the first distance variance are existing methods, and will not be described in detail in this embodiment.

[0118] S1082, The controller determines the number of second posterior residuals, the second distance mean, and the second distance variance corresponding to the second target residual group.

[0119] Wherein, the mean of the second distance is the average of the second distances corresponding to the second posterior residuals in the second target residual group; the variance of the second distance is the variance of the second distances corresponding to the second posterior residuals in the second target residual group.

[0120] The second distance corresponding to the second posterior residual is the sum of the absolute values ​​of the differences between the second posterior residual and the other second posterior residuals among the multiple second posterior residuals.

[0121] It should be noted that the mean of the second distance is the average of all second distances corresponding to all second posterior residuals in the second objective residual group. The variance of the second distance is the variance of all second distances corresponding to all second posterior residuals in the second objective residual group.

[0122] In this embodiment, the calculation method of the second distance corresponding to the second posterior residual is similar to the calculation method of the first distance corresponding to the first posterior residual in S1081. The calculation method of the mean of the second distance is similar to the calculation method of the mean of the first distance. The calculation method of the variance of the second distance is similar to the calculation method of the variance of the first distance. This embodiment will not repeat the details.

[0123] It should be noted that after the controller determines the number of first posterior residuals, the first distance mean, and the first distance variance corresponding to the first target residual group, as well as the number of second posterior residuals, the second distance mean, and the second distance variance corresponding to the second target residual group, the controller determines whether the ratio of the number of second posterior residuals corresponding to the second target residual group to the number of first posterior residuals corresponding to the first target residual group is greater than a preset ratio, whether the second distance mean is less than the first distance mean, and whether the second distance variance is less than the first distance variance. If the controller's determination result is yes, the method embodiment shown in S1083 is used; if the controller's determination result is no, the method embodiment shown in S1084 is used.

[0124] S1083. If the ratio of the number of second posterior residuals corresponding to the second target residual group to the number of first posterior residuals corresponding to the first target residual group is greater than a preset ratio, the second distance mean is less than the first distance mean, and the second distance variance is less than the first distance variance, the controller determines the second position as the target position of the receiver.

[0125] Specifically, if the ratio of the number of second posterior residuals in the second target residual group to the number of first posterior residuals in the first target residual group is greater than a preset ratio, it indicates that the second target residual group contains more observation data and has higher statistical significance and reliability. The distance mean reflects the average error of the posterior residuals; a second distance mean less than a first distance mean indicates that the overall error of the second target residual group is smaller and the data quality is higher. The distance variance reflects the distribution of the posterior residuals; a second distance variance less than a first distance variance indicates that the data in the second target residual group is more concentrated and stable, with smaller error fluctuations. Therefore, when the ratio of the number of second posterior residuals corresponding to the second target residual group to the number of first posterior residuals corresponding to the first target residual group is greater than a preset ratio, the second distance mean is less than the first distance mean, and the second distance variance is less than the first distance variance, the controller determines the second position corresponding to the second target residual group as the target position of the receiver.

[0126] It should be noted that the preset ratio depends on the number of observation data corresponding to each satellite in the multiple observation data.

[0127] When multiple observation data sets are available, including observation data from each satellite at two frequencies, each satellite's observation data at each frequency corresponds to a non-combined single-point positioning observation equation, while the observation data from each satellite at both frequencies corresponds to an ionospherically uncombined single-point positioning observation equation. In this case, the number of ionospherically uncombined single-point positioning observation equations corresponding to multiple observation data sets is half the number of non-combined single-point positioning observation equations corresponding to multiple observation data sets. Therefore, when multiple observation data sets are available, including observation data from each satellite at two frequencies, the preset ratio can be one-half.

[0128] When multiple observation data points are available, including observation data from each satellite at three frequencies, each satellite's observation data at each frequency corresponds to one non-combined single-point positioning observation equation, while the observation data from each satellite at the three frequencies corresponds to two ionospherically-free combined single-point positioning observation equations. In this case, the number of ionospherically-free combined single-point positioning observation equations corresponding to multiple observation data points is two-thirds of the number of non-combined single-point positioning observation equations corresponding to multiple observation data points. Therefore, when multiple observation data points are available, including observation data from each satellite at three frequencies, the preset ratio can be one-half.

[0129] Based on the aforementioned principle of setting the preset ratio, the preset ratio can be set to (H-1) / H when there are multiple observation data, including observation data of each satellite at H frequency points. In actual use, the preset ratio can be adjusted based on actual conditions and empirical data, and this embodiment does not impose specific limitations on it.

[0130] S1084. The controller determines the first position as the target position of the receiver if at least one of the following conditions is met: the ratio of the number of second posterior residuals corresponding to the second target residual group to the number of first posterior residuals corresponding to the first target residual group is less than or equal to a preset ratio; the second distance mean is greater than or equal to the first distance mean; and the second distance variance is greater than or equal to the first distance variance.

[0131] It should be noted that if the ratio of the number of second posterior residuals in the second target residual group to the number of first posterior residuals in the first target residual group is less than or equal to a preset ratio, it indicates that the data volume of the second target residual group is insufficient to guarantee its statistical significance and reliability. If the second distance mean is greater than or equal to the first distance mean, it indicates that the overall error of the second target residual group is large and the data quality is poor. If the second distance variance is large, it indicates that the data distribution of the second target residual group is not concentrated, the error fluctuates greatly, and the stability is poor. Therefore, the controller determines the first position corresponding to the first target residual group as the target position of the receiver if at least one of the following conditions is met: the ratio of the number of second posterior residuals corresponding to the second target residual group to the number of first posterior residuals corresponding to the first target residual group is less than or equal to a preset ratio; the second distance mean is greater than or equal to the first distance mean; or the second distance variance is greater than or equal to the first distance variance.

[0132] In this embodiment, by comparing the number of posterior residuals, the mean distance, and the variance of the distance corresponding to the posterior residuals in the first target residual group and the second target residual group, the positioning result with the highest data quality and the smallest error is selected as the target position of the receiver, which effectively improves the positioning accuracy and data reliability. At the same time, the error correction process is optimized, enhancing the robustness and real-time performance of the single-point positioning method, ensuring that high-precision positioning services can be provided in various environments.

[0133] In the above embodiments, the controller needs to perform a non-combined single-point positioning calculation operation based on multiple observation data to obtain a first position and a first receiver clock error. The specific process by which the controller performs the non-combined single-point positioning calculation operation based on multiple observation data to obtain the first position and the first receiver clock error will be described in detail below.

[0134] In one possible embodiment, S102, the controller performs a non-combined single-point positioning calculation operation based on multiple observation data to obtain a first position and a first receiver clock error. This can be achieved through S1021 and S1022 in this embodiment. S1021 and S1022 are described in detail below.

[0135] S1021. For each observation data in multiple observation data sets, the controller establishes a non-combined single-point positioning observation equation corresponding to the observation data.

[0136] Among them, the non-combined single-point positioning observation equation satisfies:

[0137]

[0138] i represents the sequence number of the observed data in multiple observations, P i Let (X) represent the pseudorange corresponding to the i-th observation data. iS ,Y i S Z i S (x1, y1, z1) represents the coordinates of the satellite corresponding to the i-th observation data, (x1, y1, z1) represents the first position, and t r1 t represents the clock bias of the first receiver. si I represents the distance correction caused by the satellite clock error of the satellite corresponding to the i-th observation data. i T represents the ionospheric delay correction corresponding to the i-th observation data. i ε represents the tropospheric delay correction corresponding to the i-th observation data. i This represents the noise value of the i-th observation data and the error term caused by multipath error.

[0139] It should be noted that the controller establishes multiple non-combined single-point positioning observation equations based on multiple observation data; each of the multiple non-combined single-point positioning observation equations corresponds one-to-one with the multiple observation data.

[0140] For the non-combined single-point localization observation equation corresponding to the i-th observation data in a plurality of observation data, P i I i and T i It can be obtained from the i-th observation data, (X) i S ,Y i S Z i S ) and t si It can be obtained from the ephemeris data of the satellite to which the i-th observation data belongs; ε i They are ignored in the calculation. i is a positive integer, and 1≤i≤M; M is the total number of observations.

[0141] In this embodiment, multiple non-combined single-point positioning observation equations are established using multiple observation data. This facilitates the extraction of more effective data from the multiple observation data, increases the amount of usable observation information, and helps improve the accuracy of the positioning solution. Furthermore, since the multiple observation data come from different satellites, each observation data may contain different errors (such as ionospheric delay, tropospheric delay, multipath effects, etc.). Establishing multiple non-combined single-point positioning observation equations can disperse these errors, reducing the impact of errors from a single observation data point on the final result during the solution process, thereby improving the accuracy of the positioning result. In addition, when some observation data is subject to large errors or interference, solving the problem by combining multiple non-combined single-point positioning observation equations can reduce the impact of some observation data on the positioning result, improving the robustness and stability of the non-combined single-point positioning solution.

[0142] It should be noted that each non-combined single-point positioning observation equation includes the receiver clock bias. By comprehensively solving multiple non-combined single-point positioning observation equations, the receiver clock bias can be estimated and corrected more accurately, resulting in a more accurate first receiver clock bias, which helps to improve positioning accuracy and time synchronization accuracy.

[0143] S1022. The controller uses the Kalman filter algorithm or the least squares method to process multiple non-combined single-point positioning observation equations corresponding to multiple observation data to obtain the first position and the first receiver clock error.

[0144] After obtaining multiple non-combined single-point positioning observation equations corresponding to multiple observation data, these equations are constructed into a linear system of equations. The system is then iteratively solved using the Kalman filter algorithm or the least squares method to obtain the first position (X1, Y1, Z1) and the first receiver clock error t. r1 .

[0145] It should be noted that the first position (X1, Y1, Z1) and the first receiver clock error t are obtained by iteratively solving the linear equation system using the Kalman filter algorithm or the least squares method. r1 The method described is existing technology, and this embodiment does not impose any specific limitations on it.

[0146] In this embodiment, multiple non-combined single-point positioning observation equations are iteratively solved by algorithms such as least squares method or Kalman filtering, which can effectively minimize the impact of measurement error and random noise on the positioning results, and obtain the first position and the first receiver clock error.

[0147] In this embodiment, by establishing multiple non-combined single-point positioning observation equations that correspond one-to-one with multiple observation data, and by iteratively solving the multiple non-combined single-point positioning observation equations using algorithms such as least squares method or Kalman filtering, it is possible to comprehensively utilize observation data from multiple satellites at multiple frequency points, effectively reduce the impact of measurement errors and random noise, and significantly improve the accuracy and stability of receiver positioning and clock error correction.

[0148] In the above embodiments, the controller needs to perform a first posterior residual calculation operation based on the first position, the first receiver clock error, and multiple observation data to obtain multiple first posterior residuals. Next, the specific process by which the controller performs the first posterior residual calculation operation based on the first position, the first receiver clock error, and multiple observation data to obtain multiple first posterior residuals will be described in detail.

[0149] In one possible embodiment, S103, the controller performs a first posterior residual calculation operation based on the first position, the first receiver clock error, and multiple observation data to obtain multiple first posterior residuals. This can be achieved through step a in this embodiment, and step a is described in detail below.

[0150] Step a: For each observation data in the multiple observation data, the controller uses the non-combined pseudorange posterior residual calculation formula based on the first position, the first receiver clock error and the observation data to obtain the first posterior residual corresponding to the observation data, and then obtains multiple first posterior residuals corresponding to multiple observation data.

[0151] The method for calculating multiple first posterior residuals corresponding to multiple observation data using the non-combined pseudorange posterior residual calculation formula is the same. For the i-th observation data among multiple observation data, the non-combined pseudorange posterior residual calculation formula is used. The first posterior residual res corresponding to the i-th observation can then be calculated. i .

[0152] In this embodiment, by calculating the first posterior residual corresponding to each observation data point, the accuracy of the solution results of the non-combined single-point positioning operation can be evaluated. This helps identify and analyze error sources in the positioning process, such as satellite clock errors, atmospheric delay errors, and multipath effects, facilitating subsequent corrective measures. Furthermore, by analyzing the first posterior residual, poor-quality observation data can be identified among multiple observation data points. For observation data with large errors, their weight can be reduced or they can be removed in subsequent solutions, further improving the reliability and accuracy of the positioning results.

[0153] In the above embodiments, the controller needs to perform an ionospherically-free combined single-point positioning calculation operation based on multiple observation data to obtain the second position and the second receiver clock error. Next, the specific process by which the controller performs the ionospherically-free combined single-point positioning calculation operation based on multiple observation data to obtain the second position and the second receiver clock error will be described in detail.

[0154] In one possible embodiment, S104, the controller performs a single-point positioning calculation operation without ionosphere based on multiple observation data to obtain the second position and the second receiver clock difference. This can be achieved through S1041 and S1042 in this embodiment. S1041 and S1042 are described in detail below.

[0155] S1041. For observation data of the same satellite at two frequency points in multiple observation data, the controller establishes the ionosphere-free combined single-point positioning observation equation corresponding to the observation data at the two frequency points.

[0156] The equation for single-point localization observation of the non-ionospheric combination is as follows:

[0157]

[0158] i and j represent the sequence numbers of the observation data at two frequency points in multiple observation data, P LC(i,j) This represents the pseudorange calculated based on the i-th and j-th observation data through a combination without an ionosphere, (X) i S ,Y i S Z i S (x2, y2, z2) represents the coordinates of the satellite corresponding to the i-th observation data, (x2, y2, z2) represents the second position, and t r2 t represents the clock bias of the second receiver. si T represents the distance correction caused by the satellite clock error of the satellite corresponding to the i-th observation data. i ε represents the tropospheric delay correction corresponding to the i-th observation data. i This represents the noise value of the i-th observation data and the error term caused by multipath error.

[0159] Specifically, for observation data from two different frequency points corresponding to each of multiple satellites, the controller can establish an ionospheric-free combined single-point positioning observation equation. The number of multiple ionospheric-free combined single-point positioning observation equations established by the controller based on multiple observation data is less than the number of multiple observation data.

[0160] It should be noted that, for any one of multiple satellites, when establishing the ionospheric combined single-point positioning observation equation for multiple observation data corresponding to that satellite, any one of the multiple observation data corresponding to that satellite is used as the first observation data. The ionospheric combined single-point positioning observation equation is then established using the first observation data and the second observation data. This yields the multiple ionospheric combined single-point positioning observation equations corresponding to that satellite. The second observation data consists of all other observation data besides the first observation data among the multiple observation data corresponding to that satellite.

[0161] For example, the multiple observation data corresponding to satellite A include the observation data of satellite A at frequency B1, the observation data of satellite A at frequency B2, the observation data of satellite A at frequency B3, the observation data of satellite A at frequency B4, and the observation data of satellite A at frequency B5.

[0162] When establishing the ionospheric-free combined single-point positioning observation equations for satellite A, the observation data of satellite A at frequency B1 is used as the first observation data, and the observation data of satellite A at frequencies B2, B3, B4, and B5 are used as the second observation data. It is necessary to establish the ionospheric-free combined single-point positioning observation equations for satellite A at frequencies B1 and B2, B3 and B4, and B5, respectively. This completes the establishment of the ionospheric-free combined single-point positioning observation equations for satellite A.

[0163] Since the single-point localization observation equation for the ionosphere combined with the two first and second observation data can be obtained from the single-point localization observation equation for the ionosphere combined with the two second observation data, it is unnecessary to establish a single-point localization observation equation for the ionosphere combined with the two second observation data.

[0164] For example, by using the ionospheric combined single-point positioning observation equations of satellite A at frequency B1 and B3, and the ionospheric combined single-point positioning observation equations of satellite A at frequency B1 and B5, we can obtain the ionospheric combined single-point positioning observation equations of satellite A at frequency B2 and B5. Therefore, it is not necessary to directly establish the ionospheric combined single-point positioning observation equations of satellite A at frequency B2 and B5.

[0165] In this embodiment, by selecting observation data at a single frequency point as a reference, the number of single-point positioning observation equations for ionospheric combination that need to be established is reduced, simplifying the calculation process.

[0166] It should be noted that for the single-point localization observation equation for the ionosphere-free combination of the i-th and j-th observations among multiple observation data, P LC(i,j) t si and T i It can be obtained from the i-th observation data, or it can be obtained from the j-th observation data; (X) i S ,Y i S Z i S ) and t siIt can be obtained from the ephemeris data of the satellite to which the i-th observation data belongs; ε i They are ignored in the calculation. i and j are both positive integers, and 1≤i≤M, 1≤j≤M; M is the total number of observations.

[0167] S1042. The Kalman filter algorithm or the least squares method is used to process the multiple ionosphere-free combination single-point positioning observation equations corresponding to multiple observation data to obtain the second position and the second receiver clock error.

[0168] After obtaining multiple ionospheric-free combined single-point positioning observation equations corresponding to multiple observation data, these equations are constructed into a linear equation system. The system is then iteratively solved using the Kalman filter algorithm or the least squares method to obtain the second position (X2, Y2, Z2) and the second receiver clock error t. r2 .

[0169] It should be noted that the second position (X2, Y2, Z2) and the second receiver clock error t are obtained by iteratively solving the linear equations using the Kalman filter algorithm or the least squares method. r2 The method described is existing technology, and this embodiment does not impose any specific limitations on it.

[0170] In this embodiment, the least squares method or Kalman filtering algorithm is used to iteratively solve the single-point positioning observation equations of multiple ionosphere-free combinations, which can effectively minimize the impact of measurement error and random noise on the positioning results and obtain the second position and the second receiver clock error.

[0171] In this embodiment, by establishing multiple ionosphere-free combined single-point positioning observation equations corresponding to multiple observation data, and iteratively solving the multiple ionosphere-free combined single-point positioning observation equations using algorithms such as least squares method or Kalman filtering, the second position of the receiver and the clock error of the second receiver are obtained, which significantly improves the positioning accuracy and system robustness. Especially in complex ionospheric environments, by eliminating the delay error caused by the ionosphere, the reliability and accuracy of the positioning results are ensured.

[0172] In the above embodiments, the controller needs to perform a second posterior residual calculation operation based on the second position, the second receiver clock error, and multiple observation data to obtain multiple second posterior residuals. Next, the specific process by which the controller performs the second posterior residual calculation operation based on the second position, the second receiver clock error, and multiple observation data to obtain multiple second posterior residuals will be described in detail.

[0173] In one possible embodiment, S105, based on the second position, the second receiver clock error, and multiple observation data, a second posterior residual calculation operation is performed to obtain multiple second posterior residuals. This can be achieved through step b in this embodiment, and step b will be described in detail below.

[0174] Step b: For each observation data in the multiple observation data, based on the second position, the second receiver clock error and the observation data, the second posterior residual corresponding to the observation data is obtained using the formula for calculating the posterior residual of the pseudorange without ionosphere, and thus multiple second posterior residuals corresponding to multiple observation data are obtained.

[0175] The method for calculating multiple second posterior residuals corresponding to multiple observation data points using the formula for calculating the posterior residuals of pseudoranges without ionosphere is the same. For the i-th observation data point among multiple observation data points, the posterior residuals of pseudoranges without ionosphere are calculated using the formula for calculating the posterior residuals of pseudoranges without ionosphere. The second posterior residual res corresponding to the i-th observation data can then be calculated. LCii .

[0176] In this embodiment, by calculating the second posterior residual corresponding to each observation data point, the accuracy of the solution results for the ionospherically unbound single-point positioning operation can be evaluated. This helps identify and analyze error sources in the positioning process, such as satellite clock errors, atmospheric delay errors, and multipath effects, facilitating subsequent corrective measures. Furthermore, by analyzing the second posterior residual, lower-quality observation data can be identified among multiple observation data points. Observation data with significant errors can be removed in subsequent solutions, further improving the reliability and accuracy of the positioning results.

[0177] In the above embodiments, the controller needs to perform data clustering processing on multiple first posterior residuals to obtain multiple first residual groups. Simultaneously, it also needs to perform data clustering processing on multiple second posterior residuals to obtain multiple second residual groups. The specific processes by which the controller performs data clustering processing on multiple first posterior residuals to obtain multiple first residual groups, and on multiple second posterior residuals to obtain multiple second residual groups, will be described in detail below.

[0178] It should be noted that the controller needs to perform data clustering processing on multiple first posterior residuals to obtain multiple first residual grouping methods, and the controller needs to perform data clustering processing on multiple second posterior residuals to obtain multiple second residual grouping methods. This embodiment takes the controller performing data clustering processing on multiple target posterior residuals to obtain multiple target residual grouping methods as an example to illustrate the controller's methods for performing data clustering processing on multiple first posterior residuals to obtain multiple first residual grouping methods, and the controller's methods for performing data clustering processing on multiple second posterior residuals to obtain multiple second residual grouping methods.

[0179] The target posterior residual is either the first posterior residual or the second posterior residual. The target residual group is either the first residual group corresponding to the first posterior residual, or the second residual group corresponding to the second posterior residual.

[0180] In one possible embodiment, the method by which the controller performs data clustering processing on multiple target posterior residuals to obtain multiple target residual groups can be implemented through steps c1 to c4, which are described in detail below.

[0181] Step c1: For each target posterior residual, the controller determines the target distance corresponding to the target posterior residual.

[0182] Wherein, the target posterior residual is the first posterior residual, and the target distance is the first distance corresponding to the first posterior residual. Alternatively, the target posterior residual is the second posterior residual, and the target distance is the second distance corresponding to the second posterior residual.

[0183] The first distance is the sum of the absolute values ​​of the differences between the first posterior residual and other first posterior residuals.

[0184] The second distance is the sum of the absolute values ​​of the differences between the second posterior residual and other second posterior residuals.

[0185] It should be noted that the specific calculation methods for the first distance and the second distance can refer to the calculation method for the first distance in the above embodiment S1081, and will not be repeated in this embodiment.

[0186] Step c2: The controller determines multiple target cluster centers based on the posterior residuals of multiple targets.

[0187] The target cluster center is either the first cluster center or the second cluster center.

[0188] It should be noted that for multiple first posterior residuals, multiple first cluster centers are determined; for multiple second posterior residuals, multiple second cluster centers are determined. The number of first cluster centers and the number of second cluster centers are equal.

[0189] The number of the first cluster centers and the number of the second cluster centers can be set by the system developer, and this embodiment does not impose a specific limitation on this.

[0190] For example, there can be two cluster centers for the first cluster and two cluster centers for the second cluster.

[0191] When there are two first cluster centers, the two first cluster centers can be the largest and smallest first distances among multiple first distances, or other values. This embodiment does not specifically limit this.

[0192] When there are two second cluster centers, the two second cluster centers can be the largest and smallest second distances among multiple second distances, or other values. This embodiment does not specifically limit this.

[0193] Step c3: The controller clusters multiple target distances based on multiple target cluster centers to obtain the target clustering results.

[0194] Specifically, the controller clusters multiple first distances based on two first cluster centers to obtain two first residual groups. The controller also clusters multiple second distances based on two second cluster centers to obtain two second residual groups.

[0195] Step c4: The controller updates multiple target cluster centers based on the target clustering results and returns to execute the clustering of multiple target distances based on the multiple target cluster centers. The execution is iterated until the clustering convergence condition is met, and multiple target residual groups are obtained.

[0196] The target residual group is either the first residual group or the second residual group.

[0197] It should be noted that after the controller clusters multiple first distances based on two first cluster centers to obtain two first residual groups, for each of the two first residual groups, the distance between each first distance in the first residual group and the first cluster center of the first residual group is calculated, and each first distance is reclassified to obtain two new first residual groups. The new first cluster centers corresponding to the two new first residual groups are then recalculated. Afterwards, the new first cluster centers are considered as the first cluster centers in step c3, and steps c3 and c4 are executed iteratively until the two first cluster centers no longer change, or the controller no longer reclassifies any first distance, satisfying the clustering convergence condition.

[0198] After the controller clusters multiple second distances based on two second cluster centers to obtain two second residual groups, for each second residual group, the distance between each second distance in that second residual group and the second cluster center of that second residual group is calculated. Each second distance is then reclassified to obtain two new second residual groups, and the new second cluster centers corresponding to these two new second residual groups are recalculated. Then, the new second cluster centers are considered as the second cluster centers in step c3, and steps c3 and c4 are executed iteratively until the two second cluster centers no longer change, or the controller no longer reclassifies any second distance, satisfying the clustering convergence condition.

[0199] It should be noted that steps c1 to c4 above describe the specific process by which the controller performs data clustering processing on the posterior residuals of multiple targets based on the k-means clustering algorithm to obtain multiple target residual groups. Furthermore, the controller can also perform data clustering processing on the posterior residuals of multiple targets based on other clustering algorithms such as hierarchical clustering to obtain multiple target residual groups; this embodiment does not specifically limit this approach.

[0200] Figure 3 This is a schematic diagram of a single-point positioning device provided in an embodiment of this application. The single-point positioning device 300 provided in this embodiment can exist independently or be integrated into other devices to implement the operation corresponding to the controller in the above method embodiments.

[0201] The single-point positioning device may include: an acquisition module 301, a first calculation module 302, a second calculation module 303, a third calculation module 304, a fourth calculation module 305, a first processing module 306, a second processing module 307, and a determination module 308.

[0202] The acquisition module 301 is used to acquire multiple observation data; wherein, the multiple observation data includes observation data obtained by the receiver measuring the carrier signals transmitted by multiple satellites at multiple frequency points respectively.

[0203] The first calculation module 302 is used to perform non-combined single-point positioning calculation operations based on multiple observation data to obtain the first position and the first receiver clock error.

[0204] The second calculation module 303 is used to perform a first posterior residual calculation operation based on the first position, the first receiver clock error and multiple observation data to obtain multiple first posterior residuals; wherein, the multiple first posterior residuals correspond one-to-one with the multiple observation data.

[0205] The third calculation module 304 is used to perform a single-point positioning calculation operation without ionosphere based on multiple observation data to obtain the second position and the second receiver clock difference.

[0206] The fourth calculation module 305 is used to perform a second posterior residual calculation operation based on the second position, the second receiver clock error and multiple observation data to obtain multiple second posterior residuals; wherein, the multiple second posterior residuals correspond one-to-one with the multiple observation data.

[0207] The first processing module 306 is used to perform data clustering processing on multiple first posterior residuals to obtain multiple first residual groups, and to determine the first target residual group based on the cluster centers of the multiple first residual groups.

[0208] The second processing module 307 is used to perform data clustering processing on multiple second posterior residuals to obtain multiple second residual groups, and to determine the second target residual group based on the cluster centers of the multiple second residual groups.

[0209] The determination module 308 is used to determine the target position of the receiver based on the first target residual group and the second target residual group; wherein the target position is the first position or the second position.

[0210] It should be understood that the corresponding processes performed by each module have been described in detail in the above method embodiments, and will not be repeated here for the sake of brevity.

[0211] Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Figure 4 As shown, the electronic device 400 provided in this embodiment includes a memory 401 and a processor 402.

[0212] The memory 401 can be a separate physical unit, connected to the processor 402 via a bus 403. Alternatively, the memory 401 and processor 402 can be integrated and implemented in hardware. The memory 401 stores program instructions, which the processor 402 calls to execute the operations performed by the controller in any of the above method embodiments.

[0213] Optionally, when some or all of the methods in the above embodiments are implemented by software, the electronic device 400 may also include only the processor 402. A memory 401 for storing programs is located outside the electronic device 400, and the processor 402 is connected to the memory via circuitry / wires to read and execute the programs stored in the memory. The processor 402 may be a central processing unit (CPU), a network processor (NP), or a combination of a CPU and an NP. The processor 402 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The PLD may be a complex programmable logic device (CPLD), a field-programmable gate array (FPGA), a generic array logic (GAL), or any combination thereof.

[0214] Memory 401 may include volatile memory, such as random-access memory (RAM); memory may also include non-volatile memory, such as flash memory, hard disk drive (HDD) or solid-state drive (SSD); memory may also include combinations of the above types of memory.

[0215] For example, this application provides a chip including: an interface circuit and a logic circuit. The interface circuit is used to receive signals from other chips outside the chip and transmit them to the logic circuit, or to send signals from the logic circuit to other chips outside the chip. The logic circuit is used to perform the operations performed by the controller in any of the above method embodiments.

[0216] For example, this application provides a readable storage medium having computer program instructions stored thereon, which, when executed by a processor of an electronic device, cause the electronic device to perform the operations executed by the controller in any of the above method embodiments.

[0217] For example, this application provides a computer program product that, when run on an electronic device, causes the electronic device to perform the operations executed by the controller in any of the above method embodiments.

[0218] The above description is merely a specific embodiment of this application, enabling those skilled in the art to understand or implement this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments described herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A single-point positioning method, characterized in that, The method includes: Acquire multiple observation data; wherein, the multiple observation data includes observation data obtained by the receiver measuring carrier signals transmitted by multiple satellites at multiple frequency points respectively; Based on the multiple observation data, a non-combined single-point positioning solution operation is performed to obtain the first position and the first receiver clock error; Based on the first position, the first receiver clock error, and the plurality of observation data, a first posterior residual calculation operation is performed to obtain a plurality of first posterior residuals; wherein, the plurality of first posterior residuals correspond one-to-one with the plurality of observation data; Based on the multiple observation data, perform an ionospherically-free combined single-point positioning calculation to obtain the second position and the second receiver clock difference; Based on the second position, the second receiver clock error, and the plurality of observation data, a second posterior residual calculation operation is performed to obtain a plurality of second posterior residuals; wherein, the plurality of second posterior residuals correspond one-to-one with the plurality of observation data; Data clustering is performed on the plurality of first posterior residuals to obtain a plurality of first residual groups, and a first target residual group is determined based on the cluster centers of the plurality of first residual groups; Data clustering is performed on the plurality of second posterior residuals to obtain a plurality of second residual groups, and a second target residual group is determined based on the cluster centers of the plurality of second residual groups; The target position of the receiver is determined based on the first target residual group and the second target residual group; wherein the target position is either the first position or the second position.

2. The method according to claim 1, characterized in that, Determining the target location of the receiver based on the first target residual group and the second target residual group includes: The number of first posterior residuals, the mean of first distances, and the variance of first distances corresponding to the first target residual group are determined; wherein, the mean of first distances is the average of the first distances corresponding to the first posterior residuals in the first target residual group; the variance of first distances is the variance of the first distances corresponding to the first posterior residuals in the first target residual group; and the first distance corresponding to the first posterior residual is the sum of the absolute values ​​of the differences between the first posterior residual and other first posterior residuals among the plurality of first posterior residuals. Determine the number of second posterior residuals, the mean of second distances, and the variance of second distances corresponding to the second target residual group; wherein, the mean of second distances is the average of the second distances corresponding to the second posterior residuals in the second target residual group; the variance of second distances is the variance of the second distances corresponding to the second posterior residuals in the second target residual group; and the second distance corresponding to the second posterior residual is the sum of the absolute values ​​of the differences between the second posterior residual and the other second posterior residuals among the plurality of second posterior residuals. If the ratio of the number of second posterior residuals corresponding to the second target residual group to the number of first posterior residuals corresponding to the first target residual group is greater than a preset ratio, the second distance mean is less than the first distance mean, and the second distance variance is less than the first distance variance, then the second position is determined to be the target position of the receiver. If at least one of the following conditions is met: the ratio of the number of second posterior residuals corresponding to the second target residual group to the number of first posterior residuals corresponding to the first target residual group is less than or equal to the preset ratio; the second distance mean is greater than or equal to the first distance mean; and the second distance variance is greater than or equal to the first distance variance, the first position is determined to be the target position of the receiver.

3. The method according to claim 1, characterized in that, The step of performing a non-combined single-point positioning calculation based on the multiple observation data to obtain a first position and a first receiver clock error includes: For each of the plurality of observation data, a non-combined single-point positioning observation equation is established corresponding to the observation data; wherein, the non-combined single-point positioning observation equation satisfies: ； This indicates the sequence number of the observed data among the multiple observed data. Indicates the first The observation pseudorange corresponding to each observation data point Indicates the first The coordinates of the satellite corresponding to each observation data point. Indicates the first position. Indicates the clock bias of the first receiver. Indicates the first Distance correction caused by satellite clock bias of the satellite corresponding to each observation data point. Indicates the first Ionospheric delay correction for each observation data point Indicates the first Tropospheric delay correction for each observation data point Indicates the first The noise value of each observation data and the error term caused by multipath error; The Kalman filter algorithm or the least squares method is used to process the multiple non-combined single-point positioning observation equations corresponding to the multiple observation data to obtain the first position and the first receiver clock error.

4. The method according to claim 3, characterized in that, The first posterior residual calculation operation is performed based on the first position, the first receiver clock error, and the multiple observation data to obtain multiple first posterior residuals, including: For each of the plurality of observation data, based on the first position, the first receiver clock error and the observation data, the first posterior residual corresponding to the observation data is obtained using the non-combined pseudorange posterior residual calculation formula, and then the plurality of first posterior residuals corresponding to the plurality of observation data are obtained. The formula for calculating the posterior residual of the non-combined pseudorange is as follows: ； Indicates the first The first posterior residual corresponding to each observation data point.

5. The method according to claim 1, characterized in that, The step of performing a single-point localization calculation based on the multiple observation data to obtain the second position and the second receiver clock error includes: For the observation data of the same satellite at two frequency points from the multiple observation data, establish the ionosphere-free combined single-point positioning observation equation corresponding to the observation data at the two frequency points; wherein, the ionosphere-free combined single-point positioning observation equation is: ； and This indicates the sequence number of the observation data at the two frequency points among the multiple observation data. Indicates based on the first The first observation data and the first The observation pseudorange was calculated from the observation data using an ionosphere-free combination. Indicates the first The coordinates of the satellite corresponding to each observation data point. Indicates the second position. This indicates the clock bias of the second receiver. Indicates the first Distance correction caused by satellite clock bias of the satellite corresponding to each observation data point. Indicates the first Tropospheric delay correction for each observation data point Indicates the first The noise value of each observation data and the error term caused by multipath error; The Kalman filter algorithm or the least squares method is used to process the multiple single-point positioning observation equations corresponding to the multiple observation data to obtain the second position and the second receiver clock error.

6. The method according to claim 5, characterized in that, The second posterior residual calculation operation based on the second position, the second receiver clock error, and the multiple observation data yields multiple second posterior residuals, including: For each of the multiple observation data, based on the second position, the second receiver clock error and the observation data, the second posterior residual corresponding to the observation data is obtained using the formula for calculating the posterior residual of the ionosphere-free combined pseudorange, and then multiple second posterior residuals corresponding to the multiple observation data are obtained. The formula for calculating the posterior residual of the pseudo-range of the ionosphere-free combination is as follows: ； Indicates the first The second posterior residual corresponding to each observation data point.

7. The method according to claim 1, characterized in that, Data clustering was performed on the posterior residuals of multiple targets to obtain multiple target residual groups, including: For each target posterior residual, determine the target distance corresponding to the target posterior residual; wherein, the target posterior residual is the first posterior residual, and the target distance is the first distance corresponding to the first posterior residual; or, the target posterior residual is the second posterior residual, and the target distance is the second distance corresponding to the second posterior residual; the first distance is the sum of the absolute values ​​of the differences between the first posterior residual and other first posterior residuals; the second distance is the sum of the absolute values ​​of the differences between the second posterior residual and other second posterior residuals; Multiple target cluster centers are determined based on the multiple target posterior residuals; wherein, the target cluster center is either a first cluster center or a second cluster center; Clustering is performed on the distances between the multiple targets based on the multiple target cluster centers to obtain the target clustering results; The plurality of target cluster centers are updated according to the target clustering results, and the clustering of the plurality of target distances based on the plurality of target cluster centers is returned. The process is iterated until the clustering convergence condition is met, and a plurality of target residual groups are obtained; wherein the target residual group is either the first residual group or the second residual group.

8. An electronic device, characterized in that, include: Memory and processor; The memory is configured to store computer program instructions; The processor is configured to execute the computer program instructions, causing the electronic device to implement the single-point positioning method as described in any one of claims 1 to 7.

9. A computer-readable storage medium, characterized in that, include: Computer program instructions; At least one processor of the electronic device executes the computer program instructions, causing the electronic device to implement the single-point positioning method as described in any one of claims 1 to 7.

10. A chip, characterized in that, include: An interface circuit and a logic circuit, wherein the interface circuit is used to receive signals from other chips outside the chip and transmit them to the logic circuit, or to send signals from the logic circuit to other chips outside the chip, and the logic circuit is used to implement the single-point positioning method as described in any one of claims 1 to 7.

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