Direct position estimation navigation positioning method based on satellite geometry and signal intensity

Abstract

The invention belongs to the technical field of navigation, and particularly discloses a direct position estimation navigation positioning method based on satellite geometry and signal intensity. The method comprises the following steps: performing direct position estimation analysis according to a received navigation signal of each visible satellite, and determining a state correlation model between each visible satellite and a receiver; correcting the state correlation model by using a preset weight model, and determining a corrected state correlation model; the preset weight model is determined based on space angle coordinates and signal carrier-to-noise ratios of the visible satellites; and resolving the corrected state correlation model, and determining a navigation positioning result of the receiver. According to the invention, the satellite navigation positioning precision can be greatly improved.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of navigation, in particular to the technical field of high-precision positioning, and more particularly to a direct position estimation navigation positioning method based on satellite geometry and signal strength. BACKGROUND

[0002] At present, Global Navigation Satellite System (GNSS) positioning usually adopts a "two-step method", that is, first estimating intermediate parameters such as pseudorange and Doppler frequency shift between the receiver and the satellite, and then solving the receiver position based on least squares or Kalman filtering algorithm.

[0003] However, since the existing "two-step method" needs to process observation data in steps, the error of intermediate parameter estimation is transmitted to the positioning result step by step, and the overall positioning accuracy is not high. Therefore, how to better realize satellite navigation positioning has become a technical problem to be solved in the industry. SUMMARY

[0004] In view of the defects of the prior art, the purpose of the present application is to better realize satellite navigation positioning, and to solve the problem of low positioning accuracy existing in the prior art satellite navigation positioning technology.

[0005] To achieve the above purpose, in a first aspect, the present application provides a direct position estimation navigation positioning method based on satellite geometry and signal strength, comprising: performing direct position estimation analysis according to the received navigation signal of each visible satellite, and determining the state-related model between each of the visible satellites and the receiver; correcting the state-related model using a preset weight model to determine the corrected state-related model; the preset weight model is determined based on the spatial angular coordinates and signal carrier-to-noise ratio of each of the visible satellites; solving the corrected state-related model to determine the navigation positioning result of the receiver.

[0006] Optionally, the step of correcting the state-related model using a preset weight model to determine the corrected state-related model comprises: determining the weight factor corresponding to each of the visible satellites based on the preset weight model; determining the correlation value corresponding to each of the visible satellites based on the state-related model; jointly accumulating the weight factor and the correlation value corresponding to each of the visible satellites to obtain the corrected state-related model.

[0007] Optionally, the step of solving the corrected state-related model to determine the navigation positioning result of the receiver comprises: solving the modified state-related model by using the state update result of the receiver to obtain a correlation value corresponding to each state update of the receiver; determining a maximum correlation peak value from the correlation value corresponding to each state update of the receiver; obtaining a PVT navigation solution of the receiver according to the maximum correlation peak value to obtain a navigation positioning result of the receiver.

[0008] Optionally, before the step of modifying the state-related model by using the preset weight model to determine the modified state-related model, the method further comprises: determining a first spatial position precision factor associated with all the visible satellites based on the spatial angular coordinates of the visible satellites; determining a quantitative index for representing the contribution of each of the visible satellites to the spatial position precision based on the spatial angular coordinates of the visible satellites and the first spatial position precision factor; determining the preset weight model based on the quantitative index corresponding to each of the visible satellites and the signal carrier-to-noise ratio of each of the visible satellites.

[0009] Optionally, the step of determining the quantitative index for representing the contribution of each of the visible satellites to the spatial position precision based on the spatial angular coordinates of the visible satellites and the first spatial position precision factor comprises: determining a second spatial position precision factor corresponding to each of the visible satellites after excluding itself according to the spatial angular coordinates of the visible satellites; performing ratio calculation on the second spatial position precision factor corresponding to each of the visible satellites and the first spatial position precision factor associated with all the visible satellites to obtain a spatial position precision factor ratio corresponding to each of the visible satellites; determining the quantitative index corresponding to each of the visible satellites based on a preset amplification factor, a preset weight threshold and the spatial position precision factor ratio corresponding to each of the visible satellites; the preset amplification factor is determined based on a satellite altitude distribution dispersion and a satellite azimuth distribution dispersion.

[0010] Optionally, the step of determining the quantitative index corresponding to each of the visible satellites based on the preset amplification factor, the preset weight threshold and the spatial position precision factor ratio corresponding to each of the visible satellites comprises: when the spatial position precision factor ratio corresponding to each of the visible satellites is not greater than the preset weight threshold, determining a first quantitative index based on the preset amplification factor and the spatial position precision factor ratio corresponding to each of the visible satellites; when the ratio of the space position accuracy factor corresponding to each of the visible satellites is greater than the preset weight threshold, obtaining a second quantization index according to the preset weight threshold; According to the first quantization index and the second quantization index, a quantization index corresponding to each of the visible satellites is obtained.

[0011] In a second aspect, the present application provides a satellite geometry and signal strength based direct position estimation navigation positioning device, comprising: An analysis module is configured to perform direct position estimation analysis according to the received navigation signals of each visible satellite, and determine a state-related model between each of the visible satellites and the receiver; A correction module is configured to correct the state-related model by using a preset weight model, and determine a corrected state-related model; the preset weight model is determined based on the space angular coordinates and the signal carrier-to-noise ratio of each of the visible satellites; A positioning module is configured to solve the corrected state-related model, and determine a navigation positioning result of the receiver.

[0012] In a third aspect, the present application provides an electronic device, comprising: at least one memory configured to store a program; and at least one processor configured to execute the program stored in the memory, and when the program stored in the memory is executed, the processor is configured to execute the method described in the first aspect or any possible implementation manner of the first aspect.

[0013] In a fourth aspect, the present application provides a computer readable storage medium, and the computer readable storage medium stores a computer program, and when the computer program is run on a processor, the processor is caused to execute the method described in the first aspect or any possible implementation manner of the first aspect.

[0014] In a fifth aspect, the present application provides a computer program product, and when the computer program product is run on a processor, the processor is caused to execute the method described in the first aspect or any possible implementation manner of the first aspect.

[0015] It can be understood that the beneficial effects of the above-mentioned second aspect to fifth aspect can be referred to the related description in the first aspect, and will not be repeated here.

[0016] In general, compared with the prior art, the above technical solutions conceived by the present application have the following beneficial effects: This application provides a direct position estimation navigation and positioning method based on satellite geometry and signal strength. By introducing an improved direct position estimation method, it comprehensively considers the signal strength and spatial geometric distribution differences of each visible satellite, integrates these observation conditions into a preset weight model, and corrects the state correlation model between each visible satellite and the receiver under the direct position estimation analysis. This enables direct position estimation with dynamic weight allocation, maximizes the use of key satellite signals for positioning, and greatly improves the accuracy of satellite navigation and positioning. Attached Figure Description

[0017] Figure 1 This is one of the flowcharts illustrating the direct position estimation navigation and positioning method based on satellite geometry and signal strength provided in this application embodiment; Figure 2 This is the second flowchart of the direct position estimation navigation and positioning method based on satellite geometry and signal strength provided in the embodiments of this application; Figure 3 (a) is a schematic diagram showing the comparison of positioning errors of various positioning methods provided in the embodiments of this application under one observation condition; (b) is a schematic diagram showing the comparison of positioning errors of various positioning methods provided in the embodiments of this application under one observation condition in the ENU direction. Figure 4 (a) is a schematic diagram showing the comparison of positioning errors of various positioning methods provided in the embodiments of this application under another observation condition; (b) is a schematic diagram showing the comparison of positioning errors of various positioning methods provided in the embodiments of this application under another observation condition in the ENU direction. Figure 5 This is a schematic diagram of the structure of the direct position estimation navigation and positioning device based on satellite geometry and signal strength provided in the embodiments of this application; Figure 6 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0019] The terms "first" and "second," etc., used in the specification and claims of this application are used to distinguish different objects, not to describe a specific order of objects. For example, "first quantitative indicator" and "second quantitative indicator," etc., are used to distinguish different quantitative indicators, not to describe a specific order of quantitative indicators.

[0020] In the embodiments of the present application, the word "exemplary" or "for example" is used to mean serving as an example, instance, or illustration, and not necessarily to imply any preference or superiority. In fact, an "exemplary" or "for example" embodiment should not necessarily be considered to have any advantage over other embodiments.

[0021] In the description of the embodiments of the present application, unless otherwise specified, "a plurality of" means two or more, for example, a plurality of processing units means two or more processing units, and the like; a plurality of elements means two or more elements, and the like.

[0022] In the prior art, direct position estimation (DPE) as a new one-step positioning method has been widely concerned. DPE discards the intermediate parameter estimation step of the "two-step method", directly combines all visible satellite signals, and solves the positioning by maximizing the likelihood function. In a weak signal environment, it can still maintain good positioning performance and improve the robustness of positioning.

[0023] However, DPE also has its defects: the joint of DPE on satellite signals is based on equal weight processing, which does not consider the difference of different satellite signal strengths, which is easy to amplify the influence of satellite signals with poor signal quality on the positioning result, and its positioning accuracy still needs to be improved.

[0024] Therefore, the present application provides a direct position estimation navigation positioning method based on satellite geometry and signal strength.

[0025] It should be noted that the various defects of the above prior art technical solutions are the results obtained by the inventors after careful practice and research, therefore, the discovery process of the above problems and the solutions proposed by the embodiments of the present application to the above problems should be the contributions made by the inventors to the present application in the implementation process of the present application.

[0026] The embodiments of the present application will be described below in conjunction with the drawings in the embodiments of the present application.

[0027] Figure 1 The flowchart of the direct position estimation navigation positioning method based on satellite geometry and signal strength provided by the embodiments of the present application is shown in FIG. 1, which includes: Figure 1 Step S1: performing DPE analysis according to the received navigation signal of each visible satellite to determine the state-related model between each visible satellite and the receiver; ​Step S2: The state-related model is modified using a preset weight model to determine the modified state-related model; the preset weight model is determined based on the spatial angular coordinates and signal-to-noise ratio of each visible satellite. Step S3: Solve the corrected state-related model to determine the navigation and positioning results of the receiver.

[0028] Specifically, the state-related model described in the embodiments of this application refers to the objective function model associated with the PVT state of the receiver.

[0029] In the embodiments of this application, in step S1, DPE analysis is performed based on the navigation signals received from each visible satellite. Here, the DPE method does not require signal acquisition and tracking; it directly estimates the receiver's position, velocity, and time (PVT) state from the signal parameters of the visible satellites, making fuller use of the satellite signals.

[0030] More specifically, suppose that at a certain moment the antenna receives... M The navigation signal of the satellite, which is a mixed signal with a known structure, is represented as: (1) in, Indicates the first One visible satellite, and These represent the pseudo-random noise code transmitted by the satellite and the corresponding signal amplitude, respectively. and These represent the time delay and Doppler shift corresponding to the satellite, respectively. The variance is Zero-mean additive white Gaussian noise.

[0031] If the receiver collects If there are 1 observed signal, then the matrix form of the received signal can be expressed as: (2) in, yes The received signal vector, yes The signal amplitude vector of the visible satellite, yes The additive white Gaussian noise vector yes A local replica matrix, where each element is a synchronization parameter. and The function is specifically represented as:

[0032] The receiver in the two-step positioning (2SP) method processes each satellite signal independently, and the time delay and Doppler parameters can be estimated from the cross ambiguity function (CAF) of the received signal and the local signal: (4) where , is the signal synchronization parameter matrix containing the code delay and Doppler shift of each satellite, denotes the parameters to be estimated, denotes the norm of a vector, denotes the conjugate transpose operation.

[0033] After obtaining the measurement parameters, the traditional 2SP receiver calculates its position by trilateration. The DPE converts the intermediate estimated synchronization parameters into the receiver's PVT parameters by relating the code delay and Doppler shift to the receiver's motion parameters through: (5) (6) where is the pseudo-code rate; is the carrier frequency, which can be different for different signals; is the speed of light; , , , denotes the three-dimensional position, clock error, three-dimensional velocity, and clock drift of the th visible satellite.

[0034] Similarly, , , , denote the receiver's three-dimensional position, clock error, three-dimensional velocity, and clock drift, respectively, which can be denoted as . The position and velocity are defined in the Earth-fixed coordinate system centered on the Earth.

[0035] Thus, the received signal model using the receiver's PVT parameters is: (7) Now consider the Maximum Likelihood Estimation (MLE) of the signal parameters, the MLE of the PVT state of the receiver directly related to the DPE, which is determined by the CAF of each satellite signal, that is: (8) Let the candidate value of the parameter be denoted as The objective function associated with the PVT state of the receiver, that is, the state-related model between each visible satellite and the receiver can be expressed as: (9) The objective function obtained in the DPE method is the incoherent superposition of the CAFs from M satellites. Through joint accumulation of signals, the DPE can directly obtain the navigation solution of the PVT parameters of the receiver.

[0036] It should be noted that the elevation angle of the satellite and the signal carrier-to-noise ratio are two commonly used indicators to reflect the signal quality, so the error can be suppressed by reducing the weight of the weak signal or low-elevation satellite. However, the elevation angle can only reflect the height information of the satellite and cannot highlight the spatial geometric distribution characteristics of the satellite. The carrier-to-noise ratio can reflect abnormal situations such as shielding and reflection during signal propagation, but when the satellites are unevenly distributed or the geometric redundancy is insufficient, even if the signal strength is high, it can still lead to a decrease in positioning accuracy.

[0037] Further, in the embodiments of the present application, by considering the satellite signal strength and the spatial geometric distribution of the satellite, the influence of these observation conditions is taken into account in the DPE model as a correction. Specifically, the spatial angular coordinates (including the elevation angle and the azimuth angle) and the signal carrier-to-noise ratio of each visible satellite can be used to build a model to obtain a preset weight model. Among them, the spatial angular coordinates of each visible satellite can represent the spatial geometric distribution characteristics of the satellite, and the signal carrier-to-noise ratio can represent the signal strength of the satellite.

[0038] In the embodiments of the present application, in step S2, by means of weight distribution, the above-mentioned preset weight model can be used to correct the state-related model in the DPE method, and a corrected state-related model can be obtained.

[0039] Further, in the embodiments of the present application, in step S3, by using the corrected DPE state-related model for calculation, the navigation and positioning result of the receiver can be accurately obtained.

[0040] The direct position estimation navigation positioning method based on satellite geometry and signal strength of the embodiment of the application is improved by introducing a direct position estimation method, comprehensively considers the signal strength and spatial geometry distribution difference of each visible satellite, fuses these observation conditions into a preset weight model, corrects the state related model between each visible satellite and the receiver under the direct position estimation analysis, can realize dynamic weight distribution of the direct position estimation, maximizes the use of key satellite signals for positioning, and greatly improves the satellite navigation positioning precision.

[0041] Based on the content of the above embodiment, as an optional embodiment, before the step S2, the state related model is corrected by using the preset weight model to determine the corrected state related model, the method further comprises: determining a first spatial position precision factor associated with all visible satellites based on the spatial angular coordinates of each visible satellite; determining a quantitative index for characterizing the contribution of each visible satellite to the spatial position precision based on the spatial angular coordinates of each visible satellite and the first spatial position precision factor; determining a preset weight model based on the quantitative index corresponding to each visible satellite and the signal carrier-to-noise ratio of each visible satellite.

[0042] Specifically, the spatial angular coordinates described in the embodiment of the application specifically include an elevation angle and an azimuth angle.

[0043] The first spatial position precision factor (Position Dilution of Precision, PDOP) described in the embodiment of the application refers to the PDOP determined based on the spatial angular coordinates of all visible satellites.

[0044] In the embodiment of the application, before the step S2, the state related model is corrected by using the preset weight model to determine the corrected state related model, the preset weight model also needs to be constructed.

[0045] In order to more fully use the received signal and more accurately obtain the positioning result, the application proposes a dynamic weight distribution method, uses a PDOP model, and considers the current PDOP value, the number of visible satellites, the satellite elevation angle and azimuth angle factors, comprehensively judges the geometric distribution of the satellite at the current positioning time from a more macro level, and accordingly adaptively sets the amplification coefficient and the threshold value to obtain a more reasonable weight distribution.

[0046] In addition, the satellite signal strength is included in the weight model as a factor affecting the weight. By comprehensively considering the satellite geometry and signal strength at the time of positioning, the joint weighting method is applied to the DPE framework for improvement, the key satellite signals can be maximized for positioning, and the robustness of the improved DPE positioning method in complex environments is further ensured.

[0047] More specifically, in the embodiments of the present application, at the actual DOP value, the station-centered coordinate system is often used instead of the geocentric and geodetic coordinate system, in which the expression of the geometric matrix and the weight coefficient matrix can be directly obtained through coordinate transformation, i.e.: (10) (11) wherein and are the elevation and azimuth of the i-th visible satellite, respectively; m is the symmetric matrix of , and the DOP value can be calculated after obtaining the weight coefficient matrix, i.e.: (12) (13) wherein is the geometric dilution of precision, is the spatial dilution of precision, is the diagonal element of the weight coefficient matrix .

[0048] In the embodiments of the present application, based on the above formulas (10)-(13), the first PDOP associated with all visible satellites can be calculated using the elevation and azimuth of each visible satellite.

[0049] Further, using the spatial angular coordinates of each visible satellite again, the PDOP corresponding to each visible satellite is calculated after excluding one visible satellite, and the ratio calculation is performed with the first PDOP associated with all visible satellites, so that a quantitative index for representing the contribution of each visible satellite to the spatial dilution of precision can be obtained.

[0050] Based on the content of the above embodiments, as an optional embodiment, the quantitative index for representing the contribution of each visible satellite to the spatial dilution of precision is determined based on the spatial angular coordinates of each visible satellite and the first spatial dilution of precision, comprising: performing spatial dilution of precision calculation according to the spatial angular coordinates of each visible satellite to determine the second spatial dilution of precision corresponding to each visible satellite after excluding itself; performing ratio calculation according to the second spatial dilution of precision corresponding to each visible satellite and the first spatial dilution of precision associated with all visible satellites to obtain the spatial dilution of precision ratio corresponding to each visible satellite; ​The quantification index corresponding to each visible satellite is determined based on a preset amplification factor, a preset weight threshold, and a spatial position accuracy factor ratio corresponding to each visible satellite. The preset amplification factor is determined based on a satellite height distribution dispersion and a satellite azimuth distribution dispersion.

[0051] Specifically, in the embodiment of the present application, for the contribution of a certain visible satellite to the overall PDOP value, the PDOP value is first calculated considering all currently visible satellites, and then the observation data of the satellite is removed, and the PDOP value is recalculated using the data of the remaining visible satellites; comparison is made between the two, the greater the difference between the two PDOP values, the greater the contribution of the satellite to improving the spatial distribution. The specific calculation process is as follows: Step one, according to formula (13), the PDOP value obtained by using all satellites is calculated, denoted as ; Step two, the PDOP value is recalculated using all satellites except the first visible satellite, denoted as , that is, the second PDOP after removing each visible satellite.

[0052] Step three, according to the corresponding to each visible satellite and the first PDOP associated with all visible satellites, the PDOP ratio corresponding to each visible satellite is calculated , that is, the ratio of and is calculated to obtain , and its expression is as follows: (14) Further, in the embodiment of the present application, the preset amplification factor and the preset weight threshold are used in combination with the PDOP ratio corresponding to each visible satellite to calculate the quantification index corresponding to each visible satellite. Here, the preset amplification factor can be determined based on the satellite height distribution dispersion and the satellite azimuth distribution dispersion of all visible satellites.

[0053] In the embodiment of the present application, it is assumed that the preset amplification factor is , and the preset weight threshold is , and the two parameters can be dynamically modulated based on the current satellite geometry strength, by deeply fusing the elevation angle and azimuth angle statistics, analyzing the concentration and dispersion of satellite distribution, and further dynamically optimizing the values obtained.

[0054] The method of the embodiments of the present application introduces an amplification factor and a weight threshold value, combines the spatial position accuracy factor ratio corresponding to each visible satellite, quantifies the positioning accuracy contribution of each visible satellite to its spatial geometric distribution, and fuses the satellite distribution geometric intensity characteristics into the DPE navigation positioning, which is beneficial to improving the satellite navigation positioning accuracy and ensuring the robustness in the environment with poor satellite spatial geometric distribution.

[0055] Based on the content of the above embodiments, as an optional embodiment, based on the preset amplification factor, the preset weight threshold value and the spatial position accuracy factor ratio corresponding to each visible satellite, a quantization index corresponding to each visible satellite is determined, including: When the spatial position accuracy factor ratio corresponding to each visible satellite is not greater than the preset weight threshold value, a first quantization index is determined based on the preset amplification factor and the spatial position accuracy factor ratio corresponding to each visible satellite; When the spatial position accuracy factor ratio corresponding to each visible satellite is greater than the preset weight threshold value, a second quantization index is obtained according to the preset weight threshold value; According to the first quantization index and the second quantization index, a quantization index corresponding to each visible satellite is obtained.

[0056] Specifically, in the embodiments of the present application, the preset amplification factor and the preset weight threshold value The following adjustment strategy can be used, that is: (15) (16) In the formula, the number of visible satellites reflects the geometric redundancy; the hyperbolic tangent function is used to obtain a nonlinear correction factor which reflects the current geometric structure intensity; the elevation angle dispersion reflects the satellite height distribution dispersion, is the standard deviation of the visible satellite elevation angle; the azimuth circle variance reflects the satellite azimuth distribution dispersion.

[0057] Here, the values of and can be adaptively adjusted according to the actual positioning scene. For example, in a good satellite geometric positioning environment, a smaller amplification factor can be selected; and in a challenging environment with poor geometry, the weight of the key satellite is more sensitive, and a suitable threshold value needs to be set to truncate the abnormal prominent value while amplifying the weight.

[0058] Further, a weight factor based on PDOP can be obtained Pwhich represents a reasonable quantification value of the contribution of each visible satellite to the spatial distribution, is positively correlated with the contribution of each satellite to the spatial distribution, and the quantification index corresponding to each visible satellite may be expressed as: (17) In the formula, As the first quantification index, As the second quantification index.

[0059] wherein the preset amplification factor may be used for sensitivity control.

[0060] The method of the embodiments of the present application further dynamically optimizes the values of the amplification factor and the weight threshold value, optimizes the quantification index of the contribution of each visible satellite to the spatial distribution, and corrects and optimizes the state-dependent model under the DPE, which is conducive to further improving the robustness of the DPE in complex environments.

[0061] Further, in the embodiments of the present application, based on the quantification index corresponding to each visible satellite and the signal carrier-to-noise ratio of each visible satellite, a preset weight model can be determined.

[0062] Specifically, in the embodiments of the present application, in addition to considering the geometric intensity of the satellite spatial distribution during positioning, the satellite signal strength is also an important factor to be considered. The signal carrier-to-noise ratio can well reflect the attenuation and other influences suffered by the satellite signal during propagation, and the combination of the two can provide a more reasonable weight scheme. Therefore, the PDOP model and the CN0M based on the carrier-to-noise ratio are comprehensively considered to obtain a joint PDOP-CN0M model weight function, i.e., the preset weight model, which can be expressed as: (18) The method of the embodiments of the present application constructs the preset weight model by combining the geometric intensity of the satellite spatial distribution and the satellite signal strength, which is used to correct the state-dependent model under the DPE, so that the key geometric satellites and satellite signals with higher intensity can be focused on during positioning, thereby improving the satellite navigation and positioning accuracy.

[0063] Based on the content of the above embodiments, as an optional embodiment, step S2, the state-dependent model is corrected by using the preset weight model to determine the corrected state-dependent model, which includes: determining the weight factor corresponding to each visible satellite based on the preset weight model; determining the correlation value corresponding to each visible satellite based on the state-dependent model; jointly accumulating the weight factor and the correlation value corresponding to each visible satellite to obtain the corrected state-dependent model.

[0064] Specifically, in the embodiments of this application, a preset weight model is applied to the DPE method, and the state-related model under DPE is modified using the preset weight model. For the DPE state-related model represented by equation (9) Determine the correlation values ​​corresponding to each visible satellite. ,Right now .

[0065] Furthermore, in the embodiments of this application, the corrected state correlation model is obtained by jointly accumulating the weighting factors and correlation values ​​corresponding to each visible satellite. It can be represented as: (19) In the formula, Indicates the first m The weighting factor corresponding to each visible satellite Indicates the first m The correlation values ​​corresponding to each visible satellite.

[0066] The method in this application uses PDOP and signal-to-noise ratio as indicators to evaluate satellite signal weights, and jointly accumulates the correlation values ​​of different satellite signals to obtain a DPE objective function that integrates a weighted model. By correcting the state-related model under DPE, it can effectively realize dynamic weight allocation DPE, avoid amplifying the impact of poor-quality satellite signals on positioning results, and improve navigation and positioning accuracy.

[0067] Based on the above embodiments, as an optional embodiment, step S3, solving the corrected state-related model to determine the navigation and positioning results of the receiver, includes: The corrected state correlation model is solved using the receiver's state update results to obtain the correlation value corresponding to each receiver state update; The maximum correlation peak value is determined from the correlation value corresponding to each state update of the receiver; Based on the maximum correlation peak value, the PVT navigation solution of the receiver is obtained to obtain the navigation and positioning result of the receiver.

[0068] Specifically, in the embodiments of the present application, after obtaining the modified state-dependent model, the modified state-dependent model can be solved by using the state update result of the receiver. Specifically, the maximum state-dependent model output value after DPE correction is taken as the target, and on the basis of obtaining a correlation value output by the modified state-dependent model, the state of the receiver is constantly updated, i.e., the PVT parameters of the receiver, including the three-dimensional position, the clock error, the three-dimensional velocity and the clock drift, are re-updated, and then the correlation value output by the modified state-dependent model is calculated in the manner as described above in combination with the navigation signals of each visible satellite, and this iterative optimization process is constantly performed, so that the correlation value corresponding to each state update of the receiver can be obtained.

[0069] Further, the maximum correlation value corresponding to each state update of the receiver can be determined from the correlation value, and the maximum correlation peak value is taken as the maximum correlation peak value, so that the receiver state that makes the joint cumulative correlation value of the navigation domain maximum can be selected, the PVT navigation solution of the receiver is obtained, and the positioning information of the receiver can be determined from the PVT navigation solution, so that the navigation and positioning result of the receiver is obtained.

[0070] The method of the embodiments of the present application uses the modified state-dependent model for navigation and positioning calculation, adopts joint accumulation of different visible satellite signals and maximum correlation peak value search, obtains the PVT navigation solution of the receiver, and can accurately output the navigation and positioning result of the receiver.

[0071] Therefore, the DPE process of the joint PDOP-CNOM weighting method can be obtained, and the implementation process is as shown in Figure 2 Through the A-GPS running mode, the initial position information of the receiver (including the three-dimensional position, the clock error, the three-dimensional velocity and the clock drift of the receiver, etc.) and the satellite navigation signals of different visible satellites, including ephemeris information (such as the three-dimensional position, the clock error, the three-dimensional velocity and the clock drift of the satellite, etc.), are received, and are input into the correlator corresponding to each visible satellite for operation, and are subjected to weighting operation through the preset weighting model. The whole operation process can be referred to the calculation processes of the foregoing formulas (1) to (19). Through joint accumulation of the correlation values of different satellite signals, the correlation value output by the modified state-dependent model is obtained. Further, by constantly updating the state of the receiver, the maximum correlation value corresponding to each state update of the receiver is determined from the correlation value, which is taken as the maximum correlation peak value, the receiver state that makes the joint cumulative correlation value of the navigation domain maximum is selected, the PVT navigation solution of the receiver is obtained, and accurate navigation and positioning of the receiver is realized.

[0072] In one specific embodiment of the present application, a specific application of the direct position estimation navigation and positioning method based on satellite geometry and signal strength proposed in the foregoing embodiments is given.

[0073] Specifically, the simulation is based on the MATLAB R2024a platform in the Windows 10 operating system. The GNSS signal is a GPS L1 C / A signal sampled at a sampling rate of 8.184 MHz for a duration of 10 s. The satellite simulation uses GPS ephemeris based on the RINEX format to calculate the state information of the satellite, and the process of signal transmission adds path attenuation, ionospheric and tropospheric delays according to the distance between the satellite and the receiver, and uses the Klobuchar and Hopfield models to correct ionospheric and tropospheric errors.

[0074] The setting of the positioning scene includes an open environment with good geometry and a challenging environment with poor geometry: Scene 1 simulates an open sky with uniformly distributed satellites; Scene 2 simulates a city canyon with satellite blocking on both sides.

[0075] In Scene 1, , the elevation gradient of the 10 visible satellites is continuously distributed, covering the range of 15°-75°, and the azimuth is uniformly distributed in the 0°-360° interval, representing the spatial distribution characteristics of the ideal geometric configuration. Regarding signal strength, the signal strength of each satellite in this open environment is stable, with a carrier-to-noise ratio of more than 37 dB-Hz. Due to the small atmospheric attenuation of high-elevation satellites, the signal strength is stable at more than 42 dB-Hz; in Scene 2, , the receiver is located in a city canyon blocked by high-rise buildings on both sides, and almost all satellites on both sides are blocked, leaving only 5 usable satellites distributed in the narrow northwest-southeast region. On the other hand, in the city canyon, due to the influence of non-line-of-sight transmission and multipath effects, the signal strength decreases, and high-elevation satellites such as PRN 9 and 23 have relatively stable signals, but their carrier-to-noise ratio levels are still lower than those of satellites of the same height in the open environment. Low-elevation satellites are affected by building reflection and diffraction attenuation, resulting in a decrease in signal strength, which poses a greater challenge to positioning.

[0076] In the above scenarios, the positioning performance of different methods is compared, including the existing least squares parameter estimation method of dual-frequency observations (i.e., the LS method of 2SP), the equal-weight DPE method, and the weighted DPE (WDPE) method proposed in this application. The positioning performance is evaluated by the root mean square error (RMSE) of the receiver's position estimation in the northeast ENU three-dimensional direction and the overall position estimation. As shown in Figure 3 and Figure 4 , the positioning error comparison of the three positioning methods under the above two different observation scene conditions is given, including the comparison of planar positioning error and ENU (coordinate system) direction positioning error.

[0077] The positioning result of scenario 1 shows that due to the asymmetry of satellite geometry in the vertical direction, the positioning error of each method in the vertical direction is generally higher than that in the horizontal direction. In this open sky positioning scenario, the positioning performance of the DPE method is superior to that of the LS method, and the WDPE method provided in the present application achieves the best positioning effect.

[0078] The positioning result of scenario 2 shows that due to weak signals and poor geometry, which can affect the accuracy of the acquisition and tracking process, the positioning performance of the LS method deteriorates sharply in this scenario, while the DPE method maintains its robustness and the overall positioning error is superior to that of the LS method. Compared with the equal-weight DPE, the WDPE method using the weighted model can focus on using key geometric satellites and satellite signals with higher intensity by considering the difference between PDOP and carrier-to-noise ratio, so as to improve the positioning performance of the existing method. Especially in the zenith direction, the positioning performance in the U direction is improved more greatly due to the consideration of the elevation information in the geometry.

[0079] Table 1

[0080] Among them, Table 1 shows the positioning error of different methods in different scenarios, and the positioning performance improvement of WDPE relative to LS and DPE methods.

[0081] Due to the consideration of satellite geometry distribution and signal strength, the positioning effect of the WDPE method based on the PDOP-CN0M weighted model is improved: under the good observation condition of scenario 1, the positioning performance of WDPE relative to LS and DPE is improved by 36.7% and 28.5% respectively; in the poor observation environment of scenario 2, the positioning performance of WDPE relative to LS and DPE is improved by 57.6% and 45.7% respectively. It can be seen that the advantage of WDPE in challenging environment is more prominent.

[0082] The satellite geometry and signal strength based direct position estimation navigation positioning device provided in the present application is described below, and the satellite geometry and signal strength based direct position estimation navigation positioning device described below can be correspondingly referred to the satellite geometry and signal strength based direct position estimation navigation positioning method described above.

[0083] Figure 5 is a structural schematic diagram of the satellite geometry and signal strength based direct position estimation navigation positioning device provided in the embodiments of the present application, as Figure 5 shown, the device comprises: An analysis module 10 is configured to perform direct position estimation analysis according to the received navigation signal of each visible satellite, determine the state-related model between each visible satellite and the receiver; The correction module 20 is configured to correct the state-related model by using a preset weight model to determine a corrected state-related model, wherein the preset weight model is determined based on the spatial angular coordinates and the signal carrier-to-noise ratio of each visible satellite. The positioning module 30 is configured to solve the corrected state-related model to determine the navigation positioning result of the receiver.

[0084] It can be understood that the detailed function implementation of each unit / module described above can refer to the description in the foregoing method embodiments, which will not be repeated here.

[0085] It should be understood that the above device is used to execute the method in the above embodiments, and the corresponding program modules in the device have similar implementation principles and technical effects to those described in the above method. The working process of the device can refer to the corresponding process in the above method, which will not be repeated here.

[0086] The direct position estimation navigation positioning device based on satellite geometry and signal strength in the embodiment of the application is improved by introducing the direct position estimation method. The signal strength and spatial geometric distribution difference of each visible satellite are comprehensively considered, and these observation conditions are fused into the preset weight model. The state-related model between each visible satellite and the receiver under the direct position estimation analysis is corrected, the dynamic weight distribution direct position estimation can be realized, the key satellite signal is maximally used for positioning, and the satellite navigation positioning precision is greatly improved.

[0087] Based on the method in the above embodiments, the embodiment of the application provides an electronic device, as shown in the figure, which can include a processor (Processor) 610, a communication interface (Communications Interface) 620, a memory (Memory) 630 and a communication bus (Communications Bus) 640. The processor 610, the communication interface 620 and the memory 630 can communicate with each other through the communication bus 640. The processor 610 can call the logic instructions in the memory 630 to execute the method in the above embodiments. Figure 6

[0088] In addition, the logic instructions in the memory 630 described above can be implemented in the form of a software function unit and sold or used as an independent product. It can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the application essentially or the part that contributes to the prior art or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the application.

[0089] ​Based on the method in the above embodiments, the embodiments of the present application provide a computer readable storage medium, which stores a computer program. When the computer program is run on a processor, the processor executes the method in the above embodiments.

[0090] Based on the method in the above embodiments, the embodiments of the present application provide a computer program product, which, when run on a processor, causes the processor to execute the method in the above embodiments.

[0091] It can be understood that the processor in the embodiments of the present application can be a central processing unit (CPU), and can also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. The general-purpose processor can be a microprocessor or any conventional processor.

[0092] The method steps in the embodiments of the present application can be implemented in the form of hardware or by a processor executing software instructions. The software instructions can be composed of corresponding software modules, and the software modules can be stored in a random access memory (RAM), a flash memory, a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically EPROM (EEPROM), a register, a hard disk, a mobile hard disk, a CD-ROM or any other form of storage medium well known in the art. An exemplary storage medium is coupled to the processor, so that the processor can read information from the storage medium and write information to the storage medium. Of course, the storage medium can also be an integral part of the processor. The processor and the storage medium can be located in an ASIC.

[0093] In the embodiments described above, all or some of the embodiments can be implemented by software, hardware, firmware or any combination thereof. When implemented by software, all or some of the embodiments can be implemented in the form of a computer program product storing computer program instructions. When the computer program instructions are loaded into and executed by a computer, all or some of the procedures or functions described in the embodiments of the present application are performed. The computer can be a general purpose computer, a special purpose computer, a computer network, or another programmable apparatus. The computer program instructions can be stored in a computer readable storage medium or transmitted by a computer readable storage medium. The computer program instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center through a wired (such as coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (such as infrared, wireless, microwave, etc.) manner. The computer readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. integrated with one or more available media. The available media can be a magnetic medium (such as a floppy disk, a hard disk, a magnetic tape), an optical medium (such as a DVD), or a semiconductor medium (such as a solid state disk (SSD)), etc.

[0094] It can be understood that various numerical numbers involved in the embodiments of the present application are only used for differentiation for convenience of description, and do not limit the scope of the embodiments of the present application.

[0095] It should be understood that expressions such as "include" and "may include" used in the present application represent the existence of disclosed functions, operations or constituent elements, and do not limit one or more additional functions, operations and constituent elements. In the present application, terms such as "include" and / or "have" can be interpreted to represent specific features, numbers, operations, constituent elements, components or combinations thereof, but cannot be interpreted to exclude the existence or addition of one or more other features, numbers, operations, constituent elements, components or combinations thereof.

[0096] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art can easily think of changes or replacements within the technical scope disclosed in the present application, which should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A direct position estimation navigation and positioning method based on satellite geometry and signal strength, characterized in that, include: Based on the navigation signals received from each visible satellite, a direct position estimation analysis is performed to determine the state correlation model between each visible satellite and the receiver; The state-related model is modified using a preset weight model to determine the modified state-related model; The preset weighting model is determined based on the spatial angular coordinates and signal-to-noise ratio of each of the visible satellites; The corrected state-related model is solved to determine the navigation and positioning results of the receiver.

2. The direct position estimation navigation and positioning method based on satellite geometry and signal strength according to claim 1, characterized in that, The step of modifying the state-related model using a preset weight model to determine the modified state-related model includes: Based on the preset weight model, the weight factor corresponding to each of the visible satellites is determined; Based on the state-related model, the correlation values ​​corresponding to each of the visible satellites are determined; The corrected state-related model is obtained by jointly accumulating the weight factors and correlation values ​​corresponding to each of the visible satellites.

3. The direct position estimation navigation and positioning method based on satellite geometry and signal strength according to claim 2, characterized in that, The step of solving the modified state-related model to determine the navigation and positioning result of the receiver includes: The corrected state correlation model is solved using the state update results of the receiver to obtain the correlation value corresponding to each state update of the receiver; The maximum correlation peak value is determined from the correlation values ​​corresponding to each state update of the receiver; Based on the maximum correlation peak value, the PVT navigation solution of the receiver is obtained to obtain the navigation and positioning result of the receiver.

4. The direct position estimation navigation and positioning method based on satellite geometry and signal strength according to any one of claims 1-3, characterized in that, Before modifying the state-related model using a preset weight model and determining the modified state-related model, the method further includes: Based on the spatial angular coordinates of each of the visible satellites, determine the first spatial position accuracy factor that associates all of the visible satellites. Based on the spatial angular coordinates of each of the visible satellites and the first spatial position accuracy factor, a quantitative index is determined to characterize the contribution of each of the visible satellites to spatial position accuracy. The preset weighting model is determined based on the quantization index corresponding to each visible satellite and the signal-to-noise ratio of each visible satellite.

5. The direct position estimation navigation and positioning method based on satellite geometry and signal strength according to claim 4, characterized in that, The determination of quantitative indicators to characterize the contribution of each visible satellite to spatial position accuracy, based on the spatial angular coordinates of each visible satellite and the first spatial position accuracy factor, includes: The spatial position accuracy factor is calculated based on the spatial angular coordinates of each of the visible satellites, and the second spatial position accuracy factor after removing itself is determined for each of the visible satellites. The ratio of the spatial position precision factor corresponding to each visible satellite is calculated by comparing the second spatial position precision factor corresponding to each visible satellite with the first spatial position precision factor associated with all the visible satellites. The quantitative index corresponding to each visible satellite is determined based on the preset magnification factor, the preset weight threshold, and the ratio of the spatial position accuracy factor corresponding to each visible satellite; the preset magnification factor is determined based on the satellite altitude distribution dispersion and the satellite azimuth distribution dispersion.

6. The direct position estimation navigation and positioning method based on satellite geometry and signal strength according to claim 5, characterized in that, The determination of the quantitative index corresponding to each visible satellite based on a preset magnification factor, a preset weight threshold, and the ratio of the spatial position accuracy factor corresponding to each visible satellite includes: When the ratio of the spatial position precision factor corresponding to each of the visible satellites is not greater than the preset weight threshold, a first quantitative index is determined based on the preset magnification factor and the ratio of the spatial position precision factor corresponding to each of the visible satellites. When the ratio of the spatial position accuracy factor corresponding to each of the visible satellites is greater than the preset weight threshold, a second quantitative index is obtained according to the preset weight threshold. Based on the first quantification index and the second quantification index, the quantification index corresponding to each visible satellite is obtained.

7. A direct position estimation navigation and positioning device based on satellite geometry and signal strength, characterized in that, include: The analysis module is used to perform direct position estimation analysis based on the navigation signals received from each visible satellite, and to determine the state correlation model between each visible satellite and the receiver; The correction module is used to correct the state-related model using a preset weight model and determine the corrected state-related model. The preset weighting model is determined based on the spatial angular coordinates and signal-to-noise ratio of each of the visible satellites; The positioning module is used to solve the corrected state-related model and determine the navigation and positioning result of the receiver.

8. An electronic device, characterized in that, Includes memory and one or more processors; The memory is coupled to the one or more processors, and the memory is used to store computer program code, the computer program code including computer instructions; The one or more processors invoke the computer instructions to cause the electronic device to perform the method as described in any one of claims 1-6.

9. A computer-readable storage medium comprising instructions, characterized in that: When the instructions are executed on an electronic device, the electronic device causes the electronic device to perform the method as described in any one of claims 1-6.

10. A computer program product, comprising a computer program or instructions, characterized in that: When the computer program or instructions are run on an electronic device, the electronic device causes the electronic device to perform the method as described in any one of claims 1-6.

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