A dual-antenna GNSS dynamic attitude calculation method applied to complex environment

Abstract

This application discloses a dual-antenna GNSS dynamic attitude calculation method for complex environments, relating to the field of satellite navigation and attitude measurement technology. This method is applied to a vehicle equipped with dual antennas and includes: acquiring GNSS observation data of the vehicle at the current epoch using both antennas; updating the predicted attitude angle and position covariance matrix of the current epoch by combining the attitude calculation results from the previous epoch with the GNSS observation data; calculating the initial coordinates based on the predicted attitude angle and position covariance matrix; obtaining an ambiguity vector based on the initial coordinates, GNSS observation data, and a fixed prior baseline length; and calculating the attitude calculation result of the current epoch based on the ambiguity vector. This application eliminates the need for expensive additional hardware, adapting to low-cost dual-antenna GNSS devices solely through algorithm optimization. It effectively addresses signal interruption and loss issues, significantly improves the availability of equipment in complex environments, and is suitable for scenarios such as autonomous driving.

Description

Technical Field

[0001] This application relates to the field of satellite navigation and attitude measurement technology, and in particular to a dual-antenna GNSS dynamic attitude calculation method for complex environments. Background Technology

[0002] With the rapid development of intelligent equipment fields such as autonomous driving, drone control, and tilt monitoring, high-precision attitude determination technology has become an indispensable key support. How to achieve high-precision dynamic attitude measurement has become an important research direction for expanding the large-scale commercial application of GNSS.

[0003] In GNSS attitude determination, related technologies can employ a dual-antenna attitude determination strategy. This involves calculating the baseline vector between two antennas mounted on a specific axis of the vehicle to obtain accurate heading and pitch angles. However, correctly resolving carrier phase ambiguity is the core and challenging aspect of dual-antenna attitude determination. In complex real-world vehicle driving environments (such as urban canyons, high-rise building clusters, and tree-lined roads with high obstruction), GNSS observation data is often subject to severe multipath effects and frequent cycle slips, leading to a sharp decrease in ambiguity fixation rate.

[0004] Related technologies typically introduce a fixed baseline length between two antennas as a constraint to improve the success rate of ambiguity fixation. Baseline constraint strategies include, but are not limited to: virtual observation method, which is prone to introducing additional linearization errors under short baseline conditions, thereby reducing the accuracy of the floating-point ambiguity solution and prolonging the initialization time; baseline length verification method, which only uses the known baseline length as a post-verification condition for ambiguity solution, fails to allow the baseline information to directly participate in the parameter estimation process, resulting in insufficient information utilization; and quadratic constraint integer least squares method, which strictly incorporates the baseline length information as an additional nonlinear constraint into the parameter estimation and integer least squares criterion, the effect of which is highly dependent on the coordination of the solution mode and the accuracy of the initial coordinates.

[0005] Furthermore, the most commonly used solution strategy in current vehicle attitude determination systems is the "single-epoch mode" to avoid historical data contamination caused by cycle slips. However, the single-epoch mode severs the temporal correlation between adjacent epochs and the vehicle's kinematic inertial information. In the single-epoch attitude solution process, the solution from Standard Point Positioning (SPP) is usually used as the initial coordinates. However, the positioning accuracy of SPP is usually limited to the meter level, and the error can be drastically amplified to tens of meters or more under complex environmental conditions such as satellite obstruction and signal multipath fading. The huge error in the initial coordinates will directly weaken the effectiveness of baseline constraint strategies such as CLAMBDA, causing the baseline vector search to deviate from the true solution, thereby causing serious fluctuations and divergence in the attitude solution results, and even failure to converge for a long time.

[0006] Therefore, current methods are unable to overcome the shortcomings of isolated calculations in existing single-epoch models and cannot solve the problem of insufficient initial coordinate accuracy of traditional dynamic models in complex environments. A method is needed that can synergistically improve ambiguity fixation rate and attitude calculation accuracy to achieve low-cost GNSS attitude measurement. Summary of the Invention

[0007] This application provides a dual-antenna GNSS dynamic attitude calculation method for complex environments, to solve the problem of insufficient initial coordinate accuracy of traditional dynamic models in complex environments. The technical solution is as follows: In a first aspect, this application provides a dual-antenna GNSS dynamic attitude calculation method for complex environments, applied to a vehicle equipped with dual antennas. The baseline formed by the two antennas is parallel to the longitudinal symmetry plane of the vehicle. The main antenna is configured as an attitude reference station and positioned at the rear of the vehicle, while the secondary antenna is positioned at the front of the vehicle. The method includes: The vehicle's GNSS observation data at the current epoch is collected using dual antennas. The predicted attitude angle and position covariance matrix for the current epoch are obtained by combining the attitude calculation results from the previous epoch with the updated GNSS observation data. The initial coordinates are calculated based on the predicted attitude angles and position covariance matrix. Based on the initial coordinates, the GNSS observation data, and the fixed prior baseline length, an ambiguity vector is obtained, and the attitude calculation result for the current epoch is calculated based on the ambiguity vector.

[0008] In one alternative to the first aspect, if the attitude calculation result was successfully obtained in the previous epoch, the step of combining the attitude calculation result of the previous epoch and the GNSS observation data to update the predicted attitude angle and position covariance matrix for the current epoch includes: The velocity vector angle change between the two epochs is calculated based on the GNSS observation data of the previous epoch and the GNSS observation data of the current epoch. The predicted attitude angle and position covariance matrix of the current epoch are then updated based on the velocity vector angle change. If the change in velocity vector angle cannot be calculated, the attitude calculation result of the previous epoch is used as the predicted attitude angle of the current epoch, and the position covariance matrix is ​​reset to the preset position covariance matrix.

[0009] In one alternative to the first aspect, if the attitude calculation result cannot be successfully obtained in the previous epoch, the step of combining the attitude calculation result of the previous epoch and the GNSS observation data to update the predicted attitude angle and position covariance matrix for the current epoch includes: The motion direction vector is calculated based on the GNSS observation data of the previous epoch and the GNSS observation data of the current epoch. The predicted attitude angle of the current epoch is obtained based on the direction of the motion direction vector. The position covariance matrix of the previous epoch is processed based on a magnification factor greater than 1 to obtain the position covariance matrix of the current epoch.

[0010] In one alternative to the first aspect, if the attitude calculation result cannot be successfully obtained in the previous epoch, and the motion direction vector cannot be calculated based on the GNSS observation data of the previous epoch and the GNSS observation data of the current epoch, the method further includes: Single-point positioning is performed based on GNSS observation data of the current epoch to obtain the positioning result of the single-point positioning, and the estimated baseline length is calculated based on the positioning result of the single-point positioning. If the ratio of the estimated baseline length to the prior baseline length is less than or equal to a preset ratio threshold, then the positioning result of the single-point positioning is used as the initial coordinates. Otherwise, the main antenna coordinates are used as the initial coordinates, and the position covariance matrix of the previous epoch is reset to the preset position covariance matrix.

[0011] In one alternative embodiment of the first aspect, the calculation of the initial coordinates based on the predicted attitude angle and position covariance matrix includes: Coordinate domain processing is performed using a constrained dynamic prediction model. Initial coordinates are determined based on the position covariance matrix, and constraints are added to the initial coordinates based on the prior baseline length and the predicted attitude angle. The formula is as follows: ; in, Indicates the initial coordinates of the current epoch. This represents the coordinates of the main antenna in the geocentric coordinate system. This represents the coordinate transformation matrix between the Earth-centered Earth-fixed coordinate system and the Northeast-Sky coordinate system, where t represents the epoch number and t+1 represents the current epoch. This represents the predicted heading angle at the current epoch in the predicted attitude angles. This represents the predicted pitch angle for the current epoch in the predicted attitude angles. denoted as vector transpose, and l represents the prior baseline length.

[0012] 6. In one alternative embodiment of the first aspect, the step of obtaining an ambiguity vector based on the initial coordinates, the GNSS observation data, and a fixed prior baseline length, and calculating the attitude calculation result for the current epoch based on the ambiguity vector, includes: Using the initial coordinates, the GNSS observation data of the current epoch, and the prior baseline length as inputs, the ambiguity domain constraint of the CLAMBDA model is performed to obtain the ambiguity vector; Substitute the ambiguity vector into the GNSS double-difference observation model, and combine it with the GNSS observation data of the current epoch to obtain the three-dimensional baseline vector in the geocentric-earth-fixed coordinate system. The three-dimensional baseline vector is transformed to the northeast-northeast coordinate system, and the attitude calculation result for the current epoch is calculated based on the three-dimensional baseline vector after transformation to the northeast-northeast coordinate system.

[0013] In one alternative embodiment of the first aspect, the ambiguity domain constraint of the CLAMBDA model is performed using the initial coordinates, the GNSS observation data of the current epoch, and the prior baseline length as inputs. The objective function of the CLAMBDA model is expressed as follows: ; Output the ambiguity vector when the objective function of the CLAMBDA model reaches its minimum value; in, Let represent the objective function of the CLAMBDA model, and 'a' represent the ambiguity vector to be searched. This represents the floating-point ambiguity estimate obtained based on the GNSS observation data of the current epoch. Let 'b' represent the covariance matrix of the floating-point ambiguity estimate, and 'b' represent the three-dimensional baseline vector parameters. This represents the baseline vector estimate obtained under the condition of ambiguity vector a. Represents baseline vector estimation The covariance matrix, The variance represents the measurement error of the prior baseline length; Indicates by subscript The corresponding covariance matrix defines the weighted square norm, where R³ represents the three-dimensional real vector space.

[0014] Secondly, this application also provides a dual-antenna GNSS dynamic attitude calculation device for use in complex environments, applied to a vehicle equipped with dual antennas. The baseline formed by the two antennas is parallel to the longitudinal symmetry plane of the vehicle. The main antenna is configured as an attitude reference station and is located at the rear of the vehicle, while the secondary antenna is located at the front of the vehicle. The device includes: The data acquisition unit is used to acquire GNSS observation data of the vehicle at the current epoch using dual antennas. The data processing unit is used to combine the attitude calculation results of the previous epoch with the GNSS observation data to update and obtain the predicted attitude angle and position covariance matrix of the current epoch. The data processing unit is also used to calculate the initial coordinates based on the predicted attitude angle and position covariance matrix; The attitude calculation unit is used to obtain an ambiguity vector based on the initial coordinates, the GNSS observation data, and the fixed prior baseline length, and to calculate the attitude calculation result for the current epoch based on the ambiguity vector.

[0015] Thirdly, this application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method provided by the first aspect of this application or any implementation thereof.

[0016] Fourthly, this application also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method provided by the first aspect of this application or any implementation thereof.

[0017] The beneficial effects of the technical solution provided in this application include at least the following: This application abandons the traditional mode of relying on single-point positioning to provide initial coordinates, and combines adjacent epoch attitude data to update the predicted attitude angle and position covariance matrix. It improves the accuracy of initial coordinates by relying on dynamic prediction mechanism, avoids the defects of traditional single-epoch mode that sever epoch correlation and large initial coordinate error of SPP, and eliminates attitude calculation outliers.

[0018] On the other hand, this application fully leverages the effectiveness of baseline constraints by combining dual collaborative constraints in the coordinate domain and ambiguity domain with a priori baseline length to fix the ambiguity vector, thereby significantly improving the ambiguity fixation rate in complex urban environments such as high occlusion and multipath interference, and effectively addressing the problem of low fixation rate in traditional methods.

[0019] Meanwhile, this application also optimizes the attitude update logic through continuous epoch correlation, improves the calculation accuracy and algorithm convergence speed of heading angle, pitch angle and baseline length in vehicle dynamic scenarios, reduces accumulated errors and ensures the stability of calculation under harsh observation environment.

[0020] This method does not require the addition of expensive hardware; it can be adapted to low-cost dual-antenna GNSS devices simply through algorithm optimization. It effectively addresses signal interruption and loss issues, significantly improves the availability of devices in complex environments, and is suitable for scenarios such as autonomous driving. It has strong generalization and commercial application value. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in this application or related technologies, the drawings used in the description of the embodiments or related technologies will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 This is a flowchart illustrating a dual-antenna GNSS dynamic attitude calculation method for complex environments provided in this application embodiment; Figure 2 This is a schematic diagram of the structure of a dual-antenna GNSS dynamic attitude calculation device for use in complex environments, provided in an embodiment of this application. Figure 3 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0023] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions 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.

[0024] The terms "comprising" and "having," and any variations thereof, in the specification, claims, and accompanying drawings of this application are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or modules is not limited to the steps or modules listed, but may optionally include steps or modules not listed, or may optionally include other steps or modules inherent to such process, method, product, or apparatus.

[0025] It should be noted that the terms "first" and "second" used in this application are merely to distinguish similar objects and do not represent a specific ordering of the objects. It is understood that "first" and "second" can be interchanged in a specific order or sequence where permitted. It should be understood that the objects distinguished by "first" and "second" can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in an order other than those described or illustrated herein.

[0026] The present application will now be described in detail with reference to specific embodiments.

[0027] Next, combine Figure 1 This application introduces a method for calculating the dynamic attitude of dual-antenna GNSS in complex environments, provided by an embodiment of this application. For details, please refer to... Figure 1 , Figure 1 The illustration shows a flowchart of a dual-antenna GNSS dynamic attitude calculation method for complex environments provided in an embodiment of this application.

[0028] This method is applied to vehicles equipped with dual antennas. Specifically, the vehicle is equipped with two GNSS antennas, namely a main antenna and a secondary antenna. The baseline formed by the two antennas is parallel and aligned with the longitudinal symmetry plane of the vehicle. The main antenna is located at the rear (as an attitude reference station), and the secondary antenna is located at the front. The vehicle is also equipped with a GNSS receiver terminal, which is connected to both antennas simultaneously through a power divider to receive GNSS observation data from the dual antennas. The a priori baseline length can be pre-measured based on the installation positions of the main antenna and the secondary antenna of the vehicle.

[0029] like Figure 1 As shown, the method specifically includes the following steps: S101 uses dual antennas to collect GNSS observation data of the vehicle at the current epoch.

[0030] S102, combining the attitude calculation results of the previous epoch with the GNSS observation data, the predicted attitude angle and position covariance matrix of the current epoch are updated.

[0031] Specifically, for the attitude calculation result (attitude angles of the two antennas) of the previous epoch, if the current epoch is not the first epoch after the vehicle starts, the calculation result of the previous epoch can be directly obtained through components such as the vehicle ECU.

[0032] Specifically, if the attitude calculation result was successfully obtained in the previous epoch, then S102 includes the following steps: S1021, the change in velocity vector angle between the two epochs is calculated based on the GNSS observation data of the previous epoch and the GNSS observation data of the current epoch, and the predicted attitude angle and position covariance matrix of the current epoch are updated based on the change in velocity vector angle.

[0033] Specifically, based on the GNSS observation data of the previous epoch and the GNSS observation data of the current epoch, the time-differenced carrier phase (TDCP) or Doppler calculation can be performed to obtain the change in velocity vector angle between two consecutive epochs.

[0034] S1022, If the change in velocity vector angle cannot be calculated, the attitude calculation result of the previous epoch is used as the predicted attitude angle of the current epoch, and the position covariance matrix is ​​reset to the preset position covariance matrix.

[0035] Specifically, if the change in velocity vector angle cannot be calculated through inter-epoch carrier phase differential calculation or Doppler calculation, the attitude calculation result of the previous epoch is directly inherited, and the attitude calculation result of the previous epoch is used as the predicted attitude angle of the current epoch and used for calculation in subsequent steps; the preset position covariance matrix can be understood as the empirical value of the preset position covariance matrix based on actual experience, and this application embodiment does not limit this.

[0036] Specifically, if the attitude calculation result cannot be successfully obtained in the previous epoch, then S102 includes the following steps: S1023, the motion direction vector is calculated based on the GNSS observation data of the previous epoch and the GNSS observation data of the current epoch. The predicted attitude angle of the current epoch is obtained based on the direction of the motion direction vector. The position covariance matrix of the previous epoch is processed based on the magnification factor greater than 1 to obtain the position covariance matrix of the current epoch.

[0037] Specifically, based on the GNSS observation data of the previous epoch and the GNSS observation data of the current epoch, inter-epoch carrier phase difference calculation or Doppler calculation can be performed to obtain the motion direction vector. Based on the motion direction vector, the attitude angles of the current epoch, including the heading angle and the pitch angle, can be extracted.

[0038] In some embodiments, if the attitude calculation result cannot be successfully obtained in the previous epoch, and the motion direction vector cannot be calculated based on the GNSS observation data of the previous epoch and the GNSS observation data of the current epoch, then the initial coordinates can be obtained based on the GNSS observation data of the current epoch, including the following steps: S1024, perform single-point positioning based on GNSS observation data of the current epoch to obtain the positioning result of the single-point positioning, and calculate the estimated baseline length based on the positioning result of the single-point positioning; S1025, if the ratio of the estimated baseline length to the prior baseline length is less than or equal to a preset ratio threshold, then the positioning result of the single-point positioning is used as the initial coordinates of S103 for the subsequent ambiguity fixing step of S104.

[0039] Specifically, the preset ratio threshold can be set to 3, but this application does not limit it.

[0040] S1025, otherwise, use the main antenna coordinates as the initial coordinates, reset the position covariance matrix of the previous epoch to the preset position covariance matrix, and use the main antenna coordinates as the initial coordinates to perform the subsequent ambiguity fixing step S104.

[0041] In this way, the initial coordinates are always kept within a controllable range and the initial conditions required for subsequent Kalman filtering are met.

[0042] It should be noted that if the current epoch is the first epoch after the vehicle starts, a preset attitude value can be selected as the attitude calculation result of the previous epoch and step S1022 can be executed. Alternatively, the initial coordinates can be directly calculated based on steps S1024-S1025. This embodiment of the application does not limit this approach. Furthermore, step S103 specifically includes: S103, the initial coordinates are calculated based on the predicted attitude angle and position covariance matrix.

[0043] Coordinate domain processing is performed using a constrained dynamic prediction model (C-Dynamics). Initial coordinates are determined based on the position covariance matrix, and constraints are added to the initial coordinates based on the prior baseline length and the predicted attitude angle. The formula is as follows: ; in, Indicates the initial coordinates of the current epoch. This indicates the coordinates of the main antenna in the Earth-Centered, Earth-Fixed (ECEF) coordinate system. This represents the coordinate transformation matrix between the Earth-centered Earth-fixed coordinate system and the East-North-Up (ENU) coordinate system, where t represents the epoch number and t+1 represents the current epoch. This represents the predicted heading angle at the current epoch in the predicted attitude angles. This represents the predicted pitch angle for the current epoch in the predicted attitude angles. denoted as vector transpose, and l represents the prior baseline length.

[0044] Next, the ambiguity is fixed, specifically including: S104, based on the initial coordinates, the GNSS observation data, and a fixed prior baseline length, an ambiguity vector is obtained. The attitude calculation result for the current epoch is then calculated based on the ambiguity vector, including: S1041, using the initial coordinates, the GNSS observation data of the current epoch, and the prior baseline length as inputs, perform ambiguity domain constraints on the CLAMBDA model to obtain the ambiguity vector. The objective function of the CLAMBDA model is expressed as follows: ; The ambiguity vector when the objective function of the CLAMBDA model reaches its minimum value is obtained by calculating using the above formula. in, Let represent the objective function of the CLAMBDA model, and 'a' represent the ambiguity vector to be searched. This represents the floating-point ambiguity estimate obtained based on the GNSS observation data of the current epoch. Let 'b' represent the covariance matrix of the floating-point ambiguity estimate, and 'b' represent the three-dimensional baseline vector parameters. This represents the baseline vector estimate obtained under the condition of ambiguity vector a. Represents baseline vector estimation The covariance matrix, The variance represents the measurement error of the prior baseline length; Indicates by subscript The corresponding covariance matrix defines the weighted square norm, where R³ represents the three-dimensional real vector space.

[0045] S1042, Substitute the ambiguity vector into the GNSS double-difference observation model, and combine it with the GNSS observation data of the current epoch to obtain the three-dimensional baseline vector in the geocentric-geo-fixed coordinate system.

[0046] S1043, the three-dimensional baseline vector is transformed to the northeast-northeast coordinate system to obtain the three-dimensional baseline vector after transformation to the northeast-northeast coordinate system, denoted as: ; in, This represents the eastward component of the three-dimensional baseline vector after transformation to the northeast-northeast coordinate system. This represents the northward component of the three-dimensional baseline vector after transformation to the northeast-northeast coordinate system. The celestial component of the three-dimensional baseline vector after transformation to the northeast celestial coordinate system; S1044, the attitude calculation result for the current epoch is obtained based on the three-dimensional baseline vector after transformation to the northeast-northeast coordinate system, and is expressed by the formula: ; ; in, Indicates the heading angle. Indicates the pitch angle.

[0047] The following are device embodiments of this application, which can be used to execute the method embodiments of this application. For details not disclosed in the device embodiments of this application, please refer to the method embodiments of this application.

[0048] Please see below. Figure 2 This is a schematic diagram of a dual-antenna GNSS dynamic attitude calculation device for use in complex environments, provided as an exemplary embodiment of this application. It is applied to a vehicle equipped with dual antennas. The baseline formed by the two antennas is parallel to the longitudinal symmetry plane of the vehicle. The main antenna is configured as an attitude reference station and positioned at the rear of the vehicle, while the secondary antenna is positioned at the front of the vehicle. The device includes: The data acquisition unit is used to acquire GNSS observation data of the vehicle at the current epoch using dual antennas. The data processing unit is used to combine the attitude calculation results of the previous epoch with the GNSS observation data to update and obtain the predicted attitude angle and position covariance matrix of the current epoch. The data processing unit is also used to calculate the initial coordinates based on the predicted attitude angle and position covariance matrix; The attitude calculation unit is used to obtain an ambiguity vector based on the initial coordinates, the GNSS observation data, and the fixed prior baseline length, and to calculate the attitude calculation result for the current epoch based on the ambiguity vector.

[0049] It should be noted that the apparatus provided in the above embodiments, when executing a dual-antenna GNSS dynamic attitude calculation method applied to complex environments, is only illustrated by the division of the above functional modules. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. Furthermore, the apparatus and method embodiments provided in the above embodiments belong to the same concept, and their implementation process is detailed in the method embodiments, which will not be repeated here.

[0050] This application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps of any of the methods described above.

[0051] Please see Figure 3 This is a structural block diagram of an electronic device provided in an embodiment of this application.

[0052] like Figure 3 As shown, the electronic device includes a processor and a memory.

[0053] In this embodiment, the processor is the control center of the computer system, and can be a processor of a physical machine or a processor of a virtual machine. The processor may include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor can be implemented using at least one hardware form of DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), or PLA (Programmable Logic Array).

[0054] A processor can also include a main processor and a coprocessor. The main processor is used to process data in the wake-up state and is also called the CPU (Central Processing Unit). The coprocessor is a low-power processor used to process data in the standby state.

[0055] The memory may include one or more computer-readable storage media, which may be non-transitory. The memory may also include high-speed random access memory and non-volatile memory, such as one or more disk storage devices or flash memory devices. In some embodiments of this application, the non-transitory computer-readable storage media in the memory are used to store at least one instruction, which is executed by a processor to implement the methods in the embodiments of this application.

[0056] In some embodiments, the electronic device further includes a peripheral device interface and at least one peripheral device. The processor, memory, and peripheral device interface are connected via a bus or signal line. Each peripheral device is connected to the peripheral device interface via a bus, signal line, or circuit board. Specifically, the peripheral device includes: a display screen, a camera, and audio circuitry. The peripheral device interface can be used to connect at least one I / O (Input / Output) related peripheral device to the processor and memory.

[0057] In some embodiments of this application, the processor, memory, and peripheral device interfaces are integrated on the same chip or circuit board; in other embodiments of this application, any one or two of the processor, memory, and peripheral device interfaces can be implemented on separate chips or circuit boards. This application does not specifically limit the implementation in this regard.

[0058] The electronic device structural block diagrams shown in the embodiments of this application do not constitute a limitation on the electronic device. The electronic device may include more or fewer components than shown, or combine certain components, or use different component arrangements.

[0059] This application also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the steps of the methods in any of the foregoing embodiments. The computer-readable storage medium may include, but is not limited to, any type of disk, including floppy disks, optical disks, DVDs, CD-ROMs, microdrives, as well as magneto-optical disks, ROMs, RAMs, EPROMs, EEPROMs, DRAMs, VRAMs, flash memory devices, magnetic cards or optical cards, nanosystems (including molecular memory ICs), or any type of medium or device suitable for storing instructions and / or data.

[0060] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the parts that contribute to the related technology, can be embodied in the form of software products. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0061] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A method for calculating the dynamic attitude of dual-antenna GNSS arrays in complex environments, characterized in that, Applied to vehicles equipped with dual antennas, the baseline formed by the two antennas is parallel to the longitudinal plane of symmetry of the vehicle. The main antenna is configured as an attitude reference station and positioned at the rear of the vehicle, while the secondary antenna is positioned at the front of the vehicle. The attitude calculation method includes: The vehicle's GNSS observation data at the current epoch is collected using dual antennas. The predicted attitude angle and position covariance matrix for the current epoch are obtained by combining the attitude calculation results from the previous epoch with the updated GNSS observation data. The initial coordinates are calculated based on the predicted attitude angles and position covariance matrix. Based on the initial coordinates, the GNSS observation data, and the fixed prior baseline length, an ambiguity vector is obtained, and the attitude calculation result for the current epoch is calculated based on the ambiguity vector.

2. The method for dynamic attitude calculation of dual-antenna GNSS in complex environments according to claim 1, characterized in that, If the attitude calculation result was successfully obtained in the previous epoch, the step of combining the attitude calculation result from the previous epoch with the GNSS observation data to update the predicted attitude angle and position covariance matrix for the current epoch includes: The velocity vector angle change between the two epochs is calculated based on the GNSS observation data of the previous epoch and the GNSS observation data of the current epoch. The predicted attitude angle and position covariance matrix of the current epoch are then updated based on the velocity vector angle change. If the change in velocity vector angle cannot be calculated, the attitude calculation result of the previous epoch is used as the predicted attitude angle of the current epoch, and the position covariance matrix is ​​reset to the preset position covariance matrix.

3. The method for calculating the dynamic attitude of dual-antenna GNSS in complex environments according to claim 2, characterized in that, If the attitude calculation result cannot be successfully obtained in the previous epoch, the step of combining the attitude calculation result of the previous epoch and the GNSS observation data to update the predicted attitude angle and position covariance matrix for the current epoch includes: The motion direction vector is calculated based on the GNSS observation data of the previous epoch and the GNSS observation data of the current epoch. The predicted attitude angle of the current epoch is obtained based on the direction of the motion direction vector. The position covariance matrix of the previous epoch is processed based on a magnification factor greater than 1 to obtain the position covariance matrix of the current epoch.

4. The method for dynamic attitude calculation of dual-antenna GNSS in complex environments according to claim 3, characterized in that, If the attitude calculation result cannot be successfully obtained in the previous epoch, and the motion direction vector cannot be calculated based on the GNSS observation data of the previous epoch and the GNSS observation data of the current epoch, the method further includes: Single-point positioning is performed based on GNSS observation data of the current epoch to obtain the positioning result of the single-point positioning, and the estimated baseline length is calculated based on the positioning result of the single-point positioning. If the ratio of the estimated baseline length to the prior baseline length is less than or equal to a preset ratio threshold, then the positioning result of the single-point positioning is used as the initial coordinates. Otherwise, the main antenna coordinates are used as the initial coordinates, and the position covariance matrix of the previous epoch is reset to the preset position covariance matrix.

5. The method for dynamic attitude calculation of dual-antenna GNSS in complex environments according to claim 3, characterized in that, The calculation of the initial coordinates based on the predicted attitude angle and position covariance matrix includes: Coordinate domain processing is performed using a constrained dynamic prediction model. Initial coordinates are determined based on the position covariance matrix, and constraints are added to the initial coordinates based on the prior baseline length and the predicted attitude angle. The formula is as follows: ； in, Indicates the initial coordinates of the current epoch. This represents the coordinates of the main antenna in the geocentric coordinate system. This represents the coordinate transformation matrix between the Earth-centered Earth-fixed coordinate system and the Northeast-Sky coordinate system, where t represents the epoch number and t+1 represents the current epoch. This represents the predicted heading angle at the current epoch in the predicted attitude angles. This represents the predicted pitch angle for the current epoch in the predicted attitude angles. denoted as vector transpose, and l represents the prior baseline length.

6. The method for dynamic attitude calculation of dual-antenna GNSS in complex environments according to claim 5, characterized in that, The process of obtaining an ambiguity vector based on the initial coordinates, the GNSS observation data, and a fixed prior baseline length, and then calculating the attitude result for the current epoch based on the ambiguity vector, includes: Using the initial coordinates, the GNSS observation data of the current epoch, and the prior baseline length as inputs, the ambiguity domain constraint of the CLAMBDA model is performed to obtain the ambiguity vector; Substituting the ambiguity vector into the GNSS double-difference observation model and combining it with the GNSS observation data of the current epoch, the three-dimensional baseline vector in the geocentric-earth-fixed coordinate system is obtained. The three-dimensional baseline vector is transformed to the northeast-northeast coordinate system, and the attitude calculation result for the current epoch is calculated based on the three-dimensional baseline vector after transformation to the northeast-northeast coordinate system.

7. The method for dynamic attitude calculation of dual-antenna GNSS in complex environments according to claim 6, characterized in that, The ambiguity domain constraint of the CLAMBDA model is performed using the initial coordinates, the GNSS observation data of the current epoch, and the prior baseline length as inputs. The objective function of the CLAMBDA model is expressed as follows: ； Output the ambiguity vector when the objective function of the CLAMBDA model reaches its minimum value; in, Let represent the objective function of the CLAMBDA model, and 'a' represent the ambiguity vector to be searched. This represents the floating-point ambiguity estimate obtained based on the GNSS observation data of the current epoch. Let 'b' represent the covariance matrix of the floating-point ambiguity estimate, and 'b' represent the three-dimensional baseline vector parameters. This represents the baseline vector estimate obtained under the condition of ambiguity vector a. Represents baseline vector estimation The covariance matrix, The variance represents the measurement error of the prior baseline length; Indicates by subscript The corresponding covariance matrix defines the weighted square norm, where R³ represents the three-dimensional real vector space.

8. A dual-antenna GNSS dynamic attitude calculation device for complex environments, characterized in that, The device is applied to a vehicle equipped with dual antennas, wherein the baseline formed by the two antennas is parallel to the longitudinal plane of symmetry of the vehicle. The main antenna is configured as an attitude reference station and positioned at the rear of the vehicle, and the secondary antenna is positioned at the front of the vehicle. The device includes: The data acquisition unit is used to acquire GNSS observation data of the vehicle at the current epoch using dual antennas. The data processing unit is used to combine the attitude calculation results of the previous epoch with the GNSS observation data to update and obtain the predicted attitude angle and position covariance matrix of the current epoch. The data processing unit is also used to calculate the initial coordinates based on the predicted attitude angle and position covariance matrix; The attitude calculation unit is used to obtain an ambiguity vector based on the initial coordinates, the GNSS observation data, and the fixed prior baseline length, and to calculate the attitude calculation result for the current epoch based on the ambiguity vector.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the steps of the method as described in any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 7.

Images