A pressure field-assisted barometer error calibration method

Abstract

This invention discloses a barometer error calibration method based on a pressure field, comprising the following steps: S1, performing drift suppression and cross-consistency calibration on the original height observation data of the tag barometer and anchor barometer to obtain the cross-calibration height of each anchor barometer; S2, constructing a time-varying pressure field model for each anchor barometer to solve for the pressure plane value at the horizontal position of the tag barometer, thereby obtaining the residual between the drift compensation height of the tag barometer and the pressure plane; S3, estimating and updating the height offset of the tag barometer online based on the time-varying pressure field model to obtain the tag barometer pressure height correction amount; S4, using the tag barometer pressure height correction amount to correct and update the drift-suppressed tag barometer pressure height, and outputting the elevation result. This method can effectively suppress errors caused by barometer drift and changes in ambient pressure, improve the stability and accuracy of elevation estimation, and has good robustness and adaptability.

Description

Technical Field

[0001] This invention relates to the field of barometer data calibration technology, and in particular to a barometer error calibration method based on pressure field assistance. Background Technology

[0002] In environments where GNSS signals are obstructed, such as indoors or underground parking garages, 3D positioning and altitude estimation often rely on barometric altimeter data. However, barometric measurements are susceptible to factors such as temperature drift, device bias, airflow disturbances at the installation location, and slow changes in ambient air pressure. This leads to systematic errors and time-varying drift in the altitude output, resulting in accumulated vertical positioning errors. Especially in long-term operation scenarios, relying solely on the raw barometric output for altitude calculation can easily lead to abrupt altitude changes, amplified drift, and inconsistencies with the true altitude, making it difficult to meet the requirements for stable and continuous vertical positioning.

[0003] Currently, barometer error calibration mostly employs linear or polynomial compensation models. Publicly available patent CN111964836B proposes a barometer calibration method, device, and electronic equipment. This method determines the calibration result based on the correspondence between the barometer calibration value, the barometer feedback value, and the ambient temperature, but it lacks sufficient real-time error compensation during operation. Publicly available patent CN114608745A proposes a barometer calibration method and system that achieves automatic calibration of a single device through linkage between a terminal, PC tools, and a standard barometer source, but it leans more towards offline / tooling calibration processes. However, the above methods generally have certain limitations: static calibration models are sensitive to environmental changes and struggle to adapt to the dynamic characteristics of barometer pressure changes over time and space.

[0004] Therefore, to improve the stability and error controllability of barometer altitude output in complex scenarios, it is necessary to introduce a "pressure field" auxiliary mechanism. This mechanism models and constrains the spatial consistency and slow variation characteristics of ambient air pressure, decoupling barometer errors from environmental changes and enabling online, adaptive error identification and calibration. By constructing a pressure field reference, the continuity and accuracy of barometric altitude output can be maintained even in the absence of an absolute altitude benchmark, thus providing more reliable vertical information support for 3D positioning systems. Summary of the Invention

[0005] The purpose of this invention is to provide a barometer error calibration method based on a pressure field to solve the above-mentioned technical problems.

[0006] Therefore, the technical solution of the present invention is as follows:

[0007] A barometer error calibration method based on pressure field assistance, comprising the following steps:

[0008] S1. Perform drift suppression and cross-consistency calibration on the raw height observation data of the tag barometer and anchor barometer to obtain the cross-calibration height of each anchor barometer.

[0009] S2. For each anchor barometer, based on the cross-calibration height of the anchor barometer obtained in step S1, construct its time-varying pressure field model to solve for the pressure plane value at the horizontal position of the tag barometer, thereby obtaining the residual between the drift compensation height of the tag barometer and the pressure plane; wherein, the time-varying pressure field model is constructed as a first-order plane model of the anchor barometer at a specified time.

[0010] S3. Based on the time-varying pressure field model, the height offset of the tag barometer is estimated and updated online to obtain the barometer pressure height correction amount.

[0011] S4. Use the tag barometer pressure height correction amount to correct and update the drift-suppressed tag barometer pressure height, and output the elevation result.

[0012] Further, in step S1, the drift suppression operation steps for the tag barometer and anchor barometer are as follows:

[0013] 1) Construct a linear drift model for the barometer, the expression of which is:

[0014] ,

[0015] In the formula, and These represent the slope and intercept of the linear drift model of the barometer, respectively. This is the set of sampling time indexes within the initial static time period. For a moment The barometer's original altitude observation value, This is the start time of the initial static time period. This refers to finding the optimal solution for the parameters in the least squares sense. For the type of pressure gauge, or ;

[0016] 2) Based on the original height observations from the tag barometer and the anchor barometer, the slope of the linear drift model of the tag barometer was calculated. With intercept And the slope of the linear drift model of the anchor barometer With intercept ;

[0017] 3) Drift suppression compensation is applied to the original height observations of the tag barometer and anchor barometer along the entire trajectory during the initial stationary period. The expression is as follows:

[0018] ,

[0019] ,

[0020] In the formula, For a moment The drift suppression compensation height of the tag barometer time The original altitude observation value of the tag barometer; For a moment Anchor barometer Drift suppression compensation height, time Anchor barometer The original height observation value.

[0021] Further, in step S2, the cross-consistency calibration operation steps for the tag barometer and the anchor barometer are as follows:

[0022] 1) Using the tag barometer as the absolute reference, estimate the constant height offset of each anchor point barometer relative to the tag barometer. The expression is as follows:

[0023] ,

[0024] In the formula, For anchor point barometer The height offset relative to the estimated height of the tag barometer, This represents the number of samples of the original height observations during the initial static time period.

[0025] 2) The estimated height offset of each anchor barometer relative to the tag barometer is compensated to the anchor barometer drift suppression compensation height at each time point, thus obtaining the anchor barometer cross-calibration height over the entire trajectory during the initial stationary period. Its expression is:

[0026] ,

[0027] In the formula, For a moment Anchor barometer after cross-calibration Barometric altitude.

[0028] Furthermore, in step S2, the specific steps for obtaining the air pressure plane value at the horizontal position of the tag barometer are as follows:

[0029] S201, Constructing an anchor point barometer The time-varying pressure field model is expressed as follows:

[0030] ,

[0031] In the formula, , and For a moment The coefficients of the plane model below, and Anchor point barometers Horizontal coordinates in the navigation coordinate system For anchor point barometer Compared to the planar model at time Residual modeling error;

[0032] S202. Stack the observations of the time-varying pressure field model of all anchor barometers during the initial static time period to estimate the plane coefficient vector. , ;

[0033] S203. Apply the moving average filtering method to the plane coefficient vector. Perform time-domain smoothing to obtain the smoothing plane coefficient vector. ;

[0034] S204. Calculate the air pressure plane value at the horizontal position of the label barometer. The calculation expression is as follows:

[0035] ,

[0036] In the formula, For a moment The barometric pressure reading at the horizontal position of the label barometer. and They are time points The horizontal coordinates of the tag barometer in the navigation coordinate system.

[0037] S205. Calculate the residual between the tag barometer drift compensation height and the barometric pressure plane. The expression is as follows:

[0038] ,

[0039] In the formula, For a moment The residual between the label barometer drift compensation height and the barometric pressure plane.

[0040] Further, in step S202, the plane coefficient vector Specifically, the least squares method can be used to solve this problem, and its expression is as follows:

[0041] ,

[0042] In the formula, This is a matrix constructed from the locations of the anchor barometers. For a moment The cross-calibration height of all anchor barometers is stacked to form a measurement vector.

[0043] Furthermore, the specific implementation steps of step S3 are as follows:

[0044] S301. Construct a residual local statistic detection model, the expression of which is:

[0045] ,

[0046] In the formula, For time The local standard deviation of the residuals within the sliding window centered on the center. For a moment The drift suppression compensation of the tag barometer compensates for the residual between the height and the barometric pressure plane value. For a moment Mean of residuals within the sliding window For time The set of discrete time-time indices contained within the centered sliding window. This represents the number of residual samples within the sliding window. For a moment The barometric pressure reading at the horizontal position of the label barometer. For a moment Drift suppression compensation height for tag barometers;

[0047] S302. Collect all data that satisfy the local standard deviation. Less than the local standard deviation threshold The discrete moments are used to construct a set of equal-height segments;

[0048] S303. Within the set of contour segments, determine a robust estimate of the constant bias, expressed as follows:

[0049] ,

[0050] In the formula, For robust estimation of constant bias, This is the operator for taking the median.

[0051] S304. Compensate the robust estimate of the constant bias to the pressure plane value at the horizontal position of the tag barometer to obtain the bias-corrected pressure plane value, the expression of which is:

[0052] ,

[0053] In the formula, For a moment The offset-corrected pressure plane value at the horizontal position of the barometer label.

[0054] S305. Calculate the residual after correcting for the barometer's pressure height offset. The expression is as follows:

[0055] ,

[0056] In the formula, For a moment The residual after correction for the barometer's barometric height offset;

[0057] S306. Fit a third-order polynomial trend term onto the residual after correcting for the altitude bias of the tag barometer to calculate the detrended residual after correcting for the altitude bias of the tag barometer. The expression is as follows:

[0058] ,

[0059] In the formula, For a moment Detrended residuals after correction for barometer height bias.

[0060] S307. A one-dimensional Savitzky-Golay filter is used to process the detrended residual after the barometer pressure altitude offset correction to obtain the time. Tag barometer barometric height correction .

[0061] Further, in step S302, the local standard deviation threshold... The setup method is as follows: Select a static or motion without significant rise and fall as reference data, calculate the standard deviation of the residuals within the corresponding time window of the motion segment, and use this as the local standard deviation threshold. .

[0062] Furthermore, in step S306, the third-order polynomial trend term The expression is:

[0063] ,

[0064] In the formula, , , and These are polynomial coefficients, based on time... The residual sequence within the time window corresponding to the lower-order high-level segment set was obtained by third-order polynomial least squares fitting. For normalized time.

[0065] Further, in step S4, the expression for correcting and updating the drift-suppressed tag barometer height using the tag barometer height correction amount is as follows:

[0066] ,

[0067] In the formula, For a moment The elevation output of the tag barometer For a moment Tag barometer drift suppression compensation height For a moment Label barometer pressure height correction amount.

[0068] Compared with existing technologies, this barometer error calibration method based on pressure field assistance solves the problems of existing barometer calibration schemes based on linear or nonlinear fitting being sensitive to environmental changes and difficult to achieve online high-precision calibration. Specifically, this method first performs drift suppression and cross-consistency calibration on the barometer data of the tag and reference anchor point to eliminate systematic bias between sensors; then, it constructs a time-varying pressure field model based on anchor point pressure observations and performs online modeling and updating of the tag barometer height bias; finally, it uses pressure field height observations to correct and update the tag height, outputting a stable elevation result. This method can effectively suppress errors caused by barometer drift and changes in environmental pressure, improve the stability and accuracy of elevation estimation, and has the advantages of strong robustness, good adaptability, simple implementation, and high engineering practicality. Attached Figure Description

[0069] Figure 1 This is a flowchart of the barometer error calibration method based on pressure field assistance of the present invention;

[0070] Figure 2 This is a comparison curve of the elevation calculation results of different barometer calibration methods in Experiment 1 of the simulation experiment of this invention;

[0071] Figure 3 This is a schematic diagram comparing the elevation error distribution of different barometer calibration methods in Experiment 1 of the simulation experiment of this invention. Detailed Implementation

[0072] The present invention will be further described below with reference to the accompanying drawings and specific embodiments, but the following embodiments are by no means intended to limit the present invention.

[0073] See Figure 1 The implementation method of the barometer error calibration method based on pressure field assistance is described below.

[0074] S1. Perform drift suppression and cross-consistency calibration on the raw height observation data of the tag barometer and anchor barometer to obtain the cross-calibrated height of each anchor barometer.

[0075] In 3D positioning, barometers estimate altitude by measuring atmospheric pressure based on the physical law that "air pressure decreases with increasing altitude." However, single barometer measurements suffer from drift suppression and poor absolute accuracy. Therefore, in addition to barometers on the object to be located (i.e., tag barometers), one or more barometers at fixed locations with known altitudes (i.e., anchor barometers) are also installed. In practical applications, tag barometers and anchor barometers measure air pressure synchronously to use the differential air pressure between them to cancel out the interference caused by the above problems.

[0076] S101. Construct a linear drift model for the barometer to perform drift suppression compensation on the raw height observation data of the tag barometer and the anchor barometer.

[0077] Specifically, the drift suppression compensation operation steps of step S101 are described as follows.

[0078] 1) Construct a linear drift model for the barometer, the expression of which is:

[0079] ,

[0080] In the formula, and These represent the slope and intercept of the linear drift model of the barometer, respectively. This is the set of sampling time indexes within the initial static time period. For a moment The barometer's original altitude observation value, This is the start time of the initial static time period. To find the optimal solution for the parameters in the least squares sense, This is an index of discrete time points for barometer sampling. Indicates the type of pressure gauge. for Indicates a barometer label. for Indicates the first Anchor point barometer, This refers to the serial number of the anchor point barometer; when the number of anchor point barometers is M, then... The value of is 1, ..., M.

[0081] 2) By substituting the original height observations from the tag barometer and the anchor barometer into the barometer linear drift model, the slope of the tag barometer linear drift model can be calculated separately. With intercept And the slope of the linear drift model of each anchor point barometer. With intercept .

[0082] 3) Based on the slope of the linear drift model of the tag barometer With intercept The drift suppression compensation is applied to the original altitude observations of the tag barometer along its entire trajectory during the initial stationary period. The expression for this compensation is:

[0083] ,

[0084] In the formula, For a moment The drift suppression compensation height of the tag barometer For a moment The original altitude observation value of the tag barometer;

[0085] Based on the slope of the linear drift model of the anchor point barometer With intercept The drift suppression compensation is applied to the original height observations of the barometers at each anchor point along the entire trajectory during the initial stationary period. The expression for this compensation is as follows:

[0086] ,

[0087] In the formula, For a moment Anchor barometer Drift suppression compensation height, time Anchor barometer The original height observation value.

[0088] S102. Using the tag barometer as the absolute reference, estimate the constant height offset of the anchor barometer relative to the tag barometer.

[0089] Using the barometer at the i-th anchor point For example, its height offset model expression relative to the tag barometer is:

[0090] ,

[0091] In the formula, For a moment The drift suppression compensation height of the tag barometer For a moment Anchor barometer Drift suppression compensation height, For anchor point barometer The height offset relative to the constant value of the tag barometer, For a moment Anchor barometer Residual noise term relative to the tag barometer.

[0092] Based on the height offset model described above, the constant height offset of each anchor barometer relative to the tag barometer can be estimated by averaging the residuals over the initial static time period.

[0093] Therefore, anchor point barometer The expression for the estimated altitude offset relative to the tag barometer is:

[0094] ,

[0095] In the formula, For anchor point barometer The height offset relative to the estimated height of the tag barometer, This represents the number of samples of the original height observations during the initial static time period.

[0096] S103. The estimated height offset of each anchor barometer relative to the tag barometer is compensated to the anchor barometer drift suppression compensation height at each time point, so as to obtain the anchor barometer cross-calibration height on the entire trajectory during the initial static time period.

[0097] Using the barometer at the i-th anchor point For example, the expression for obtaining the cross-calibration height compensation of the anchor barometer is:

[0098] ,

[0099] In the formula, For a moment Anchor barometer The cross-calibration height.

[0100] S2. For each anchor barometer, based on the cross-calibration height of the anchor barometer obtained in step S1, construct its time-varying pressure field model to solve for the pressure plane value at the horizontal position of the tag barometer, thereby obtaining the residual between the drift compensation height of the tag barometer and the pressure plane.

[0101] The specific implementation steps of step S2 are as follows:

[0102] S201. To approximate the pressure field distribution in a horizontal plane, an anchor point barometer... The time-varying pressure field model is constructed for time intervals. The expression for the first-order planar model is:

[0103] ,

[0104] In the formula, , and For a moment The coefficients of the next first-order plane model, and Anchor point barometers Horizontal coordinates in the navigation coordinate system For anchor point barometer Compared to the first-order planar model at time Residual modeling error;

[0105] S202. Stack the observations of the time-varying pressure field model of all anchor barometers during the initial static time period to estimate the plane coefficient vector. ;

[0106] Among them, the plane coefficient vector Specifically, the least squares method can be used to solve this problem, and its expression is as follows:

[0107] ,

[0108] In the formula, This is a matrix constructed from the locations of all anchor barometers. For a moment The cross-calibration height of all anchor barometers is stacked to form a measurement vector.

[0109] S203. To suppress high-frequency fluctuations caused by the evolution of the pressure field over time, a moving average filtering method is used to smooth the plane coefficient vector in the time domain. Its expression is:

[0110] ,

[0111] In the formula, For a moment The time-domain smoothed plane coefficient vector, Let be the length of the moving average window, and j be the discrete time points within the moving average window. For time The set of discrete time-time indices contained within the centered moving average window. For a moment The plane coefficient vector.

[0112] S204. Calculate the air pressure plane value at the horizontal position of the label barometer. The calculation expression is as follows:

[0113] ,

[0114] In the formula, For a moment The barometric pressure reading at the horizontal position of the label barometer. and They are time points The horizontal coordinates of the tag barometer in the navigation coordinate system.

[0115] S3. Based on the time-varying pressure field model, the height offset of the tag barometer is estimated and updated online to obtain the barometer pressure height correction amount.

[0116] Although the time-varying pressure field model constructed in step S2 can characterize the spatial variation of the pressure field, at any given time... There is still a systematic bias between the drift suppression compensation height of the tag barometer and the pressure plane value at the horizontal position of the tag barometer in step S2. Therefore, it is necessary to estimate and update the tag barometer height bias online based on the time-varying pressure field model.

[0117] The specific steps for step S3 are as follows:

[0118] S301. Construct a residual local statistic detection model, the expression of which is:

[0119] ,

[0120] In the formula, For time The local standard deviation of the residuals within the sliding window centered on the center. For a moment The drift suppression compensation of the tag barometer compensates for the residual between the height and the barometric pressure plane value. For a moment Mean of residuals within the sliding window For time The set of discrete time-time indices contained within the centered sliding window. This represents the number of residual samples within the sliding window. For a moment The barometric pressure reading at the horizontal position of the label barometer. For a moment Drift suppression compensation height for tag barometers;

[0121] S302. Collect all data that satisfy the local standard deviation. Less than the local standard deviation threshold The discrete time points are determined, and a set of contour segments is constructed. Its expression is:

[0122] .

[0123] The elevation segment refers to a time interval within which the vertical displacement of the tag barometer is negligible and its true height remains approximately constant. Within this interval, the change between the drift suppression compensation height of the tag barometer and the pressure plane value at the horizontal position of the tag barometer is mainly caused by random noise and slow offset, and does not include significant actual vertical movement.

[0124] Local standard deviation threshold The method for determining the standard deviation is as follows: Select a static or motion without significant rise and fall as reference data, calculate the standard deviation of the residuals within the corresponding time window of the motion, and use it as the local standard deviation threshold. .

[0125] S303. Within the set of contour segments, the relationship between the drift suppression compensation height of the tag barometer and the pressure plane value at the horizontal position of the tag barometer can be expressed as:

[0126] ,

[0127] In the formula, For a moment The drift suppression compensation height of the tag barometer For a moment The barometric pressure reading at the horizontal position of the label barometer. For constant bias, This represents the residual noise term within the equal-height window.

[0128] Based on the above relational expression, constant bias Specifically, the median of the residuals within the set of equal-height segments can be used as a robust estimate of the constant bias and denoted as... Its expression is:

[0129] ,

[0130] In the formula, For robust estimation of constant bias, This is the operator for taking the median.

[0131] S304. Compensate the robust estimate of the constant bias to the pressure plane value at the horizontal position of the tag barometer to obtain the bias-corrected pressure plane value, the expression of which is:

[0132] ,

[0133] In the formula, For a moment The offset-corrected pressure plane value at the horizontal position of the barometer label.

[0134] S305. Calculate the residual after correcting for the barometer's pressure height offset. The expression is as follows:

[0135] ,

[0136] In the formula, For a moment The residual after correction for the barometer's barometric height offset;

[0137] S306. To characterize the slowly changing drift of the tag barometer and the anchor barometer, a third-order polynomial trend term is fitted to the residual after the tag barometer pressure height offset correction, so as to calculate the detrended residual after the tag barometer pressure height offset correction.

[0138] The expression for the third-order polynomial trend term is:

[0139] ,

[0140] In the formula, , , and These are polynomial coefficients, based on time... The residual sequence within the time window corresponding to the lower-order high-level segment set was obtained by third-order polynomial least squares fitting. To normalize time, This is a low-order trend term used to approximate a slowly time-varying bias;

[0141] Therefore, the detrended residual expression after correction for the barometer's pressure altitude bias is:

[0142] ,

[0143] In the formula, For a moment Detrended residuals after correction for barometer height bias.

[0144] S307. To suppress random noise while preserving slowly changing components, a one-dimensional Savitzky-Golay filter is used to process the detrended residual after the barometer pressure altitude offset correction. Its expression is:

[0145] ,

[0146] In the formula, For a moment Label barometer barometric height correction value For the Savitzky–Golay smoothing operator.

[0147] S4. Use the barometer pressure height correction value to correct and update the drift suppression compensation height of the barometer and output a stable elevation result.

[0148] Specifically, the expression for correcting and updating the drift suppression compensation height of the tag barometer using the tag barometer pressure height correction amount is as follows:

[0149] ,

[0150] In the formula, For a moment The elevation output of the tag barometer For a moment Tag barometer drift suppression compensation height For a moment Label barometer pressure height correction amount.

[0151] Furthermore, in order to verify the correctness of the present invention, actual measurement experiments were conducted; wherein, the specifications of the tag barometer and the anchor point barometer are the same, and the specific performance parameters are shown in Table 1 below.

[0152] Table 1:

[0153] index range Height measurement accuracy Pressure conversion delay Sampling rate parameter 10–1200 mbar 10 cm 1 ms 50 Hz

[0154] Based on the barometer data collected using the performance parameters shown in Table 1, five sets of positioning experiments were designed. The barometers were calibrated using the method of this invention, with the traditional linear fitting method used for barometer calibration serving as a control.

[0155] In the five sets of experiments, the elevation error test results of the method of the present invention compared with those of the traditional linear fitting method, and the calculation results of the improvement percentage of elevation accuracy are shown in Table 2 below.

[0156] Table 2:

[0157] Experiment No. Elevation error (m) of traditional linear fitting Elevation error (m) of the method of this invention Increase in percentage (%) 1 0.91 0.12 86.81 2 0.85 0.09 89.41 3 0.92 0.10 89.13 4 0.90 0.12 86.67 5 0.95 0.13 86.32

[0158] As can be seen from the comparative test results in Table 2, the method of the present invention can achieve higher precision barometer error calibration. Compared with the traditional linear fitting method, the elevation positioning accuracy of the method of the present invention is improved by 87.67%. This verifies the effectiveness and correctness of the method.

[0159] like Figure 2 The figure shows a comparison of elevation calculation results using different barometer calibration methods in Experiment 1. As can be seen from the figure, within a test period of approximately 160 seconds, the traditional linear fitting method (red line) fails to effectively handle dynamic changes in ambient air pressure, resulting in a significant divergence in relative elevation error over time (with a maximum error of approximately 2m). In contrast, the method of this invention (green line) can dynamically compensate for measurement errors by introducing auxiliary information from the air pressure field. Furthermore, the elevation curve calibrated using this method consistently converges stably to near the true value (blue line), effectively eliminating cumulative drift. This demonstrates that the method of this invention significantly outperforms the traditional linear fitting method in both elevation positioning accuracy and long-term robustness.

[0160] like Figure 3The figure shows a comparison of the elevation error distribution of different barometer calibration methods in Experiment 1. It is clear from the figure that the 75th percentile of the elevation positioning error decreased from 0.91m (traditional linear fitting method) to 0.12m (the method described in this paper), further demonstrating that the method of this invention can achieve higher precision barometer error calibration, thus verifying the effectiveness and correctness of the method.

[0161] The parts of this invention not disclosed in detail are well-known in the art. Although illustrative specific embodiments of the invention have been described above to help those skilled in the art understand the invention, it should be understood that the invention is not limited to the scope of the specific embodiments. For those skilled in the art, various changes are obvious as long as they are within the spirit and scope of the invention as defined and determined by the appended claims, and all inventions utilizing the concept of this invention are protected.

Claims

1. A barometer error calibration method based on pressure field assistance, characterized in that the steps are as follows: include: S1. Perform drift suppression and cross-consistency calibration on the raw height observation data of the tag barometer and anchor barometer to obtain the cross-calibration height of each anchor barometer. S2. For each anchor barometer, based on the cross-calibration height of the anchor barometer obtained in step S1, construct its time-varying pressure field model to solve for the pressure plane value at the horizontal position of the tag barometer, thereby obtaining the residual between the drift compensation height of the tag barometer and the pressure plane; wherein, the time-varying pressure field model is constructed as a first-order plane model of the anchor barometer at a specified time. S3. Based on the time-varying pressure field model, the height offset of the tag barometer is estimated and updated online to obtain the barometer pressure height correction amount. S4. Use the tag barometer pressure height correction amount to correct and update the drift-suppressed tag barometer pressure height, and output the elevation result.

2. The barometer error calibration method based on pressure field assistance according to claim 1, characterized in that, In step S1, the drift suppression operation steps for the tag barometer and anchor barometer are as follows: 1) Construct a linear drift model for the barometer, the expression of which is: ， In the formula, and These represent the slope and intercept of the linear drift model of the barometer, respectively. This is the set of sampling time indexes within the initial static time period. For a moment The barometer's original altitude observation value, This is the start time of the initial static time period. This refers to finding the optimal solution for the parameters in the least squares sense. For the type of pressure gauge, or ; 2) Based on the original height observations from the tag barometer and the anchor barometer, the slope of the linear drift model of the tag barometer was calculated. With intercept And the slope of the linear drift model of the anchor barometer With intercept ; 3) Drift suppression compensation is applied to the original height observations of the tag barometer and anchor barometer along the entire trajectory during the initial stationary period. The expression is as follows: ， ， In the formula, For a moment The drift suppression compensation height of the tag barometer time The original altitude observation value of the tag barometer; For a moment Anchor barometer Drift suppression compensation height, time Anchor barometer The original height observation value.

3. The barometer error calibration method based on pressure field assistance according to claim 2, characterized in that, In step S2, the cross-consistency calibration procedure for the tag barometer and the anchor barometer is as follows: 1) Using the tag barometer as the absolute reference, estimate the constant height offset of each anchor point barometer relative to the tag barometer. The expression is as follows: ， In the formula, For anchor point barometer The height offset relative to the estimated height of the tag barometer, This represents the number of samples of the original height observations during the initial static time period. 2) The estimated height offset of each anchor barometer relative to the tag barometer is compensated to the anchor barometer drift suppression compensation height at each time point, thus obtaining the anchor barometer cross-calibration height over the entire trajectory during the initial stationary period. Its expression is: ， In the formula, For a moment Anchor barometer after cross-calibration Barometric altitude.

4. The barometer error calibration method based on pressure field assistance according to claim 1, characterized in that, In step S2, the specific steps for obtaining the air pressure plane value at the horizontal position of the tag barometer are as follows: S201, Constructing an anchor point barometer The time-varying pressure field model is expressed as follows: ， In the formula, , and For a moment The coefficients of the plane model below, and Anchor point barometers Horizontal coordinates in the navigation coordinate system For anchor point barometer Compared to the planar model at time Residual modeling error; S202. Stack the observations of the time-varying pressure field model of all anchor barometers during the initial static time period to estimate the plane coefficient vector. , ; S203. Apply the moving average filtering method to the plane coefficient vector. Perform time-domain smoothing to obtain the smoothing plane coefficient vector. ; S204. Calculate the air pressure plane value at the horizontal position of the label barometer. The calculation expression is as follows: ， In the formula, For a moment The barometric pressure reading at the horizontal position of the label barometer. and They are time points The horizontal coordinates of the tag barometer in the navigation coordinate system; S205. Calculate the residual between the tag barometer drift compensation height and the barometric pressure plane. The expression is as follows: ， In the formula, For a moment The residual between the label barometer drift compensation height and the barometric pressure plane.

5. The barometer error calibration method based on pressure field assistance according to claim 4, characterized in that, In step S202, the plane coefficient vector Specifically, the least squares method can be used to solve this problem, and its expression is as follows: ， In the formula, This is a matrix constructed from the locations of the anchor barometers. For a moment The cross-calibration height of all anchor barometers is stacked to form a measurement vector.

6. The barometer error calibration method based on pressure field assistance according to claim 1, characterized in that, The specific implementation steps of step S3 are as follows: S301. Construct a residual local statistic detection model, the expression of which is: ， In the formula, For time The local standard deviation of the residuals within the sliding window centered on the center. For a moment The drift suppression compensation of the tag barometer compensates for the residual between the height and the barometric pressure plane value. For a moment Mean of residuals within the sliding window For time The set of discrete time-time indices contained within the centered sliding window. This represents the number of residual samples within the sliding window. For a moment The barometric pressure reading at the horizontal position of the label barometer. For a moment Drift suppression compensation height for tag barometers; S302. Collect all data that satisfy the local standard deviation. Less than the local standard deviation threshold The discrete moments are used to construct a set of equal-height segments; S303. Within the set of contour segments, determine a robust estimate of the constant bias, expressed as follows: ， In the formula, For robust estimation of constant bias, The operator for taking the median; S304. Compensate the robust estimate of the constant bias to the pressure plane value at the horizontal position of the tag barometer to obtain the bias-corrected pressure plane value, the expression of which is: ， In the formula, For a moment The offset-corrected pressure plane value at the horizontal position of the label barometer; S305. Calculate the residual after correcting for the barometer's pressure height offset. The expression is as follows: ， In the formula, For a moment The residual after correction for the barometer's barometric height offset; S306. Fit a third-order polynomial trend term onto the residual after correcting for the altitude bias of the tag barometer to calculate the detrended residual after correcting for the altitude bias of the tag barometer. The expression is as follows: ， In the formula, For a moment Detrended residuals after correction for barometric altitude bias in tag barometers; S307. A one-dimensional Savitzky-Golay filter is used to process the detrended residual after the barometer pressure altitude offset correction to obtain the time. Tag barometer barometric height correction .

7. The barometer error calibration method based on pressure field assistance according to claim 6, characterized in that, In step S302, the local standard deviation threshold The setup method is as follows: Select a static or motion without significant rise and fall as reference data, calculate the standard deviation of the residuals within the corresponding time window of the motion segment, and use this as the local standard deviation threshold. .

8. The barometer error calibration method based on pressure field assistance according to claim 6, characterized in that, In step S306, the third-order polynomial trend term The expression is: ， In the formula, , , and These are polynomial coefficients, based on time... The residual sequence within the time window corresponding to the lower-order high-level segment set was obtained by third-order polynomial least squares fitting. For normalized time.

9. The barometer error calibration method based on pressure field assistance according to claim 6, characterized in that, In step S4, the expression for correcting and updating the drift-suppressed tag barometer height using the tag barometer height correction amount is as follows: ， In the formula, For a moment The elevation output of the tag barometer For a moment Tag barometer drift suppression compensation height For a moment Label barometer pressure height correction amount.

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