Zero-velocity correction navigation method and system based on exponential function fitting

Abstract

The invention discloses a zero-velocity correction navigation method and system based on exponential function fitting, and relates to the technical field of inertial navigation. The method is characterized by comprising the following steps: judging the current state of a carrier according to output values of a triaxial accelerometer of N sampling points; when the current state of the carrier is a zero-speed state, fitting the speed error curve by using an exponential function according to speed data output by inertial navigation to obtain a speed error equation; integral operation is carried out on the speed error equation in a time period after initial alignment is completed, and a position error estimation value of the time period is obtained; and compensating the position error estimation value to the position data output by the inertial navigation at the current moment to obtain the corrected position data. According to the method, the exponential function is used for fitting the speed error when the carrier is parked, so that the position output by the inertial navigation system is compensated, the position error can be kept in a certain range for a long time, and the problem of long-endurance navigation of the underwater vehicle in a hidden environment is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of inertial navigation, and in particular to a zero-speed correction navigation method and system based on exponential function fitting. Background Art

[0002] The inertial navigation system is a completely autonomous navigation method that does not rely on external information input. It is widely used in various fields. However, since its solution is based on integral calculation, its positioning error will gradually increase with the increase of time, so the long-term positioning accuracy is poor. Internal error sources such as gyro drift and accelerometer bias cause the position error of the inertial navigation system to produce periodic oscillations. Error control methods such as dynamic and static alignment, empirical smoothing, zero-speed correction and combined navigation are often used to solve the problem of position divergence of the inertial navigation system. Due to the particularity and complexity of satellite navigation denial and underwater environment, it is very challenging to achieve long-duration navigation tasks in hidden waters. In general underwater environments, inertial navigation systems (INS) and acoustic sensors (Doppler odometers, baselines, sonars, etc.) are often used to solve long-duration navigation problems. However, due to the working principle of acoustic sensors, the sound waves they emit are easily detected by the enemy, resulting in mission failure. Therefore, the inertial navigation / acoustic sensor combined navigation system is not suitable for navigation problems in hidden waters. To solve the long-duration navigation mission in hidden waters, the inertial navigation system still needs to complete the long-duration navigation mission alone without relying on external sensors. Compared with other methods, zero velocity update (ZUPT) is an indispensable means for the inertial navigation system. By stopping the vehicle to estimate the velocity error and then correcting other errors, it can effectively control the error accumulation of the inertial navigation system for a long time. It is a cheap and effective method.

[0003] Commonly used zero-speed correction processing methods include curve fitting method, Kalman filter estimation method, etc. The curve fitting method is simple, efficient and reliable, and has the characteristics of fast calculation speed. However, since it is a purely kinematic method, the state information change process inside the physical system cannot be known; the Kalman filter method can track the change process of the internal state, but its disadvantage is that its calculation time is long and the selection of prior statistics is more troublesome. At present, both domestic and foreign countries have conducted research on zero-speed correction of curve fitting method. The literature "On the Adjustment of Individual Traverses" (3rd International Symposium on Inertial Technology for Surveying and Geodesy, 1985.) and "Parameter Estimation Inertial Surveying" (3rd International Symposium on Inertial Technology for Surveying and Geodesy, 1985.) first proposed the zero-speed correction method of polynomial fitting. The document "Several Estimation Methods for Zero-Speed ​​Correction of Inertial Measurement System" (Journal of China Inertial Technology, 1995, 3(2): 24-29) believes that the quadratic polynomial curve can better conform to the propagation characteristics of the inertial navigation system error. Through the sports car test, it is concluded that the quadratic curve fitting method can effectively correct the position error of the inertial navigation system. The document "Research on Zero-Speed ​​Correction Technology of Inertial Navigation System" (Journal of System Simulation, 2008, 20(17)) improves the quadratic polynomial curve fitting method, decouples the speed error of the inertial navigation system, and uses the harmonic function of trigonometric function to estimate the position error of the inertial navigation system. Simulation experiments are carried out under the same conditions, and the experimental results of the quadratic curve fitting method and the trigonometric function fitting method are compared. The experimental results show that the trigonometric function fitting method proposed in this document has a better position error correction effect than the quadratic curve fitting method.

[0004] The study found that the inertial navigation system that uses the various fitting methods proposed in the above literature to correct zero-speed still has a position error with an obvious divergent trend when performing long-duration navigation missions, and the position error cannot be stabilized within a certain range for a long time. Summary of the invention

[0005] In view of the above problems, the present invention proposes a zero-speed correction navigation method and system based on exponential function fitting.

[0006] According to one aspect of the present invention, a zero-speed correction navigation method based on exponential function fitting is proposed, and the method comprises the following steps:

[0007] Obtain the speed and position data of the inertial navigation output and the three-axis accelerometer output values ​​of N sampling points in real time;

[0008] Determine the current state of the carrier according to the output values ​​of the three-axis accelerometer at N sampling points; the state includes a zero-speed state and a non-zero-speed state;

[0009] When the current state of the carrier is zero speed, the speed error curve is fitted using an exponential function according to the speed data output by the inertial navigation system to obtain the speed error equation;

[0010] Integrate the velocity error equation within the time period from the completion of the initial alignment to obtain an estimated position error value for the time period;

[0011] The position error estimate is compensated to the position data output by the inertial navigation system at the current moment to obtain the corrected position data.

[0012] Furthermore, judging the current state of the carrier according to the output values ​​of the three-axis accelerometer at N sampling points includes: calculating the variance of the output values ​​of the three-axis accelerometer at the N sampling points, and judging whether the variance is less than a preset threshold value, if so, it indicates that the current state of the carrier is a zero-speed state, i.e., a parking state, otherwise it is a non-zero-speed state.

[0013] Furthermore, when the carrier is in a non-zero speed state, the variance of the triaxial accelerometer output values ​​of the next group of N sampling points is calculated and the judgment is made again.

[0014] Furthermore, the calculation formula of the variance is:

[0015]

[0016] In the formula, represents the output value of the triaxial accelerometer at the kth sampling point; N represents the total number of sampling points.

[0017] Furthermore, fitting the speed error curve using an exponential function according to the speed data output by the inertial navigation system to obtain the speed error equation includes:

[0018] Assume that there are N zero-speed states, and the time from the kth zero-speed state to the end of the initial alignment is t k , k = 1, 2, ..., N; the initial alignment refers to the process of pointing each coordinate axis of the inertial navigation coordinate system relative to the reference coordinate system; then the speed error curve corresponding to the N-time zero speed state is expressed as:

[0019]

[0020] In the formula, δV k represents the speed error of the kth zero-speed state; a, b, c represent the speed error curve coefficients; represents the Schura frequency, g represents the acceleration due to gravity, and R represents the equatorial mean radius;

[0021] The speed error curve coefficient is calculated using the least squares method, and then the speed error equation is obtained: δV(t)=a+be ωt +ce -ωt .

[0022] Further, the integral operation is expressed as:

[0023]

[0024] Where δP represents the position error.

[0025] According to another aspect of the present invention, a zero-speed correction navigation system based on exponential function fitting is proposed, the system comprising:

[0026] A data acquisition module configured to acquire speed and position data output by an inertial navigation system and output values ​​of a three-axis accelerometer at N sampling points in real time;

[0027] A zero-speed detection module, which is configured to determine the current state of the carrier according to the output values ​​of the three-axis accelerometer at N sampling points; the state includes a zero-speed state and a non-zero-speed state;

[0028] The speed error estimation module is configured to fit the speed error curve using an exponential function according to the speed data output by the inertial navigation system when the current state of the carrier is a zero-speed state, so as to obtain a speed error equation;

[0029] A position error estimation module configured to perform an integral operation on a velocity error equation within a time period elapsed from the completion of the initial alignment to obtain a position error estimation value for the time period;

[0030] The position correction module is configured to compensate the position error estimate value to the position data output by the inertial navigation system at the current moment to obtain the corrected position data.

[0031] Furthermore, the method of judging the current state of the carrier according to the output values ​​of the three-axis accelerometer at N sampling points in the zero-speed detection module includes: calculating the variance of the output values ​​of the three-axis accelerometer at the N sampling points, and judging whether the variance is less than a preset threshold value, if so, it indicates that the current state of the carrier is a zero-speed state, i.e., a parking state, otherwise it is a non-zero-speed state; when the carrier is in a non-zero-speed state, calculating the variance of the output values ​​of the three-axis accelerometer at the next group of N sampling points and re-judging.

[0032] Furthermore, in the speed error estimation module, fitting the speed error curve using an exponential function according to the speed data output by the inertial navigation to obtain the speed error equation includes:

[0033] Assume that there are N zero-speed states, and the time from the kth zero-speed state to the end of the initial alignment is t k , k = 1, 2, ..., N; the initial alignment refers to the process of pointing each coordinate axis of the inertial navigation coordinate system relative to the reference coordinate system; then the speed error curve corresponding to the N-time zero speed state is expressed as:

[0034]

[0035] In the formula, δV k represents the speed error of the kth zero-speed state; a, b, c represent the speed error curve coefficients; represents the Schura frequency, g represents the acceleration due to gravity, and R represents the equatorial mean radius;

[0036] The speed error curve coefficient is calculated using the least squares method, and then the speed error equation is obtained: δV(t)=a+be ωt +ce -ωt .

[0037] Further, the integral operation in the position error estimation module is expressed as:

[0038]

[0039] Where δP represents the position error.

[0040] The beneficial technical effects of the present invention are:

[0041] In order to improve the zero-speed correction of the existing fitting method, the present invention proposes a zero-speed correction navigation method and system based on exponential function fitting, which uses an exponential function to fit the speed error of the carrier when it stops. According to the error propagation principle of the inertial navigation system, the speed error is decoupled into the Shula part and the dynamic part. There is no maneuvering when the carrier stops for zero-speed correction, so the speed error at the parking point only comes from the Shula part. The position error caused by the Shula oscillation of the inertial navigation system can be obtained by integration, and then the position output by the inertial navigation system is compensated. The zero-speed correction navigation method based on exponential function fitting proposed by the present invention is more in line with the law of inertial navigation position error, and has a better position error correction effect than other existing curve fitting zero-speed correction methods; it can estimate the position error of the underwater vehicle only by staged parking without using external sensors, and then compensate the error of the position output by the inertial navigation system, so that the position error can be kept within a certain range for a long time, thereby solving the long-time navigation problem of underwater vehicles in concealed environments and realizing a higher-precision underwater autonomous positioning function. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] The present invention can be better understood by referring to the description given below in conjunction with the accompanying drawings, which together with the following detailed description are included in this specification and form a part of this specification, and are used to further illustrate the preferred embodiments of the present invention and explain the principles and advantages of the present invention.

[0043] Figure 1 The present invention is a flowchart of a zero-speed correction navigation method based on exponential function fitting according to an embodiment of the present invention.

[0044] Figure 2 This is the velocity error curve of the Shula oscillation part.

[0045] Figure 3 The figure is a flow chart of determining the current state of a carrier in an embodiment of the present invention.

[0046] Figure 4 Flow chart of speed error equation estimation in an embodiment of the present invention.

[0047] Figure 5 Flow chart of position error calculation in an embodiment of the present invention.

[0048] Figure 6 4 is a structural diagram of position correction in an inertial navigation system in an embodiment of the present invention.

[0049] Figure 7 This is a comparison chart of the latitude position error between the present invention and the uncorrected inertial navigation system and other correction methods.

[0050] Figure 8 This is a comparison chart of the longitude position error between the present invention and the uncorrected inertial navigation system and other correction methods. DETAILED DESCRIPTION

[0051] In order to enable those skilled in the art to better understand the scheme of the present invention, exemplary implementations or embodiments of the present invention will be described below in conjunction with the accompanying drawings. Obviously, the described implementations or embodiments are only implementations or embodiments of a part of the present invention, not all of them. Based on the implementations or embodiments of the present invention, all other implementations or embodiments obtained by ordinary technicians in the field without creative work should fall within the scope of protection of the present invention.

[0052] The embodiment of the present invention proposes a zero-speed correction navigation method based on exponential function fitting, such as Figure 1 As shown, the method comprises the following steps:

[0053] S1, real-time acquisition of the speed and position data of the inertial navigation output and the output values ​​of the three-axis accelerometer at N sampling points;

[0054] S2. judging the current state of the carrier according to the output values ​​of the three-axis accelerometers at N sampling points; the state includes a zero-speed state and a non-zero-speed state;

[0055] S3. When the current state of the carrier is a zero-speed state, the speed error curve is fitted using an exponential function according to the speed data output by the inertial navigation system to obtain a speed error equation;

[0056] S4, integrating the velocity error equation within the time period from the completion of the initial alignment to obtain an estimated position error value for the time period;

[0057] S5. Compensate the position error estimate to the position data output by the inertial navigation system at the current moment to obtain corrected position data.

[0058] Since the error models of the inertial navigation system are different in the long-flight and short-flight working states, the error models of the inertial navigation system can be distinguished for the long-flight and short-flight working states to improve the calculation accuracy. According to the error model principle of the inertial navigation system, the velocity error of the inertial navigation system can be decoupled into the Shula part and the dynamic part. In the process of solving the problem, the velocity error of the carrier is decomposed into δV = δV sh +δV nst , where the Shula part δV sh The 84.4-minute period oscillation is an inherent characteristic of the inertial navigation system and has nothing to do with the maneuverability of the carrier. Figure 2 The Schura oscillation curve model of the inertial navigation system is shown. The dynamic part δV nst Affected by the acceleration of the carrier relative to the earth, it is related to the maneuver of the carrier. In the embodiment of the present invention, the time interval for correction is less than 10 minutes, and the inertial navigation system with a working time of less than 1 hour can be regarded as short-term work, and the accumulation of various errors is not large. Therefore, the error model can be simplified to the following form:

[0059]

[0060] The subscripts x, y, and z represent the east, north, and celestial directions of the geographic coordinate system, respectively. α, β, and γ represent the pitch error angle, roll error angle, and azimuth error angle, respectively. x ,f y ,f z For comparison, is the accelerometer zero deviation, ε x ,ε y ,ε z is the constant drift of the gyro, μ x ,μ y represents the accelerometer scale factor error. g and R are the gravitational acceleration and the radius of the earth, respectively.

[0061] The method starts from S1. In S1, the velocity and position data of the inertial navigation output and the output values ​​of the three-axis accelerometer at N sampling points are obtained in real time.

[0062] According to an embodiment of the present invention, first, the speed V output by the inertial navigation is obtained. INS 、Position P INS , the time t from the completion of the initial alignment and the output of the triaxial accelerometer

[0063] Then, S2 is executed. In S2, the current state of the carrier is determined according to the output values ​​of the three-axis accelerometers at the N sampling points; the state includes a zero-speed state and a non-zero-speed state.

[0064] According to an embodiment of the present invention, Figure 3 As shown, the zero-speed detection submodule is used to determine whether the carrier is in a parking state; the output of the three-axis accelerometer is obtained, and the sum of the variances of the three-axis output data of the accelerometer at N consecutive sampling points is calculated:

[0065]

[0066] In the formula, represents the output value of the triaxial accelerometer at the kth sampling point; N represents the total number of sampling points.

[0067] Set the threshold bool to determine whether VAR<bool is true (the threshold needs to be obtained through multiple experiments). If true, set the zero-speed flag is_zero=1 to indicate that the current state is zero speed, and the subsequent steps can be performed; otherwise, set is_zero=0 to indicate non-zero speed, re-read the output data of the three-axis accelerometer of the next set of sampling points, and repeat S2.

[0068] According to actual needs, the threshold bool for judging the zero-speed state needs to be obtained through multiple experiments. The threshold in the example of the present invention is only for the simulation program corresponding to the example of the present invention. The zero-speed threshold needs to be obtained again for different embodiments and needs.

[0069] Then, S3 is executed. In S3, when the carrier is in a zero-speed state, the speed error curve is fitted using an exponential function according to the speed data output by the inertial navigation system to obtain a speed error equation.

[0070] According to an embodiment of the present invention, Figure 4 As shown, the speed error curve estimation submodule uses an exponential function to fit the speed error curve and obtain the speed error equation. Initialize the matrices Z, H, and X required by the speed error curve estimation module. The specific meanings are explained in the following formula. Obtain the speed data V output by the inertial navigation at the measurement point INS , assuming the true velocity of the carrier is V truth , then the speed error δV=Vtruth -V INS , since the carrier is currently in the parking state, V truth =0, speed error δV = -V INS When the velocity error at three or more moments is obtained, the function δV(t) = a + be can be used. ωt +ce -ωt As the velocity error equation, represents the Shula frequency, g represents the gravitational acceleration, and R represents the average radius of the equator. During the entire working time, there are N parking times. Let the time of the kth (k=1,2,…,N) parking distance initial alignment end time be t k , initial alignment refers to the process of pointing the coordinate axes of the inertial navigation coordinate system relative to the reference coordinate system, which is:

[0071]

[0072] Converted into matrix form

[0073]

[0074] in Z=[δV1 δV2 ... δV3] T

[0075]

[0076] The coefficients of the curve are calculated using the least squares method. Thus, t1~t n The velocity error curve equation during this period.

[0077] Then, S4 is executed, in which an integral operation is performed on the velocity error equation within the time period from the completion of the initial alignment to obtain a position error estimation value for the time period.

[0078] According to an embodiment of the present invention, Figure 5 As shown, the position error estimation submodule uses the speed error equation for this period to perform an integral operation to obtain the estimated value of the position error for this period. According to S3, the function δV(t)=a+be ωt +ce -ωt The coefficients a, b, and c in the equation can be used to obtain the integral of the velocity error curve equation over time during this period of time, and the estimated value of the position error can be obtained.

[0079]

[0080] Then, S5 is executed, in which the position error estimate is compensated to the position data output by the inertial navigation system at the current moment to obtain the corrected position data.

[0081] According to an embodiment of the present invention, the position error estimate value δP obtained in S4 is compensated to the position output of the inertial navigation system to obtain the corrected carrier position P=P INS -δP. Figure 6 Shows the structural diagram of position correction in an inertial navigation system.

[0082] The technical effect of the present invention is further verified through experiments.

[0083] Under the same simulation conditions, the method of the present invention is compared with an inertial navigation system without position error correction, an inertial navigation system using a quadratic function to fit a velocity error curve for position correction, and an inertial navigation system using a trigonometric function to fit a velocity error curve for position correction.

[0084] The simulation conditions are set as follows: build a trajectory generator and inertial navigation system simulation platform in MATLAB, set the iteration interval to 0.1s, set the gyro constant drift to 0.01° / h, and the angle random walk Accelerometer constant zero bias 100μg, speed random walk The random error of the inertial device is set to white noise, and the initial pitch angle error, initial roll angle error, and initial azimuth angle error are all set to 0.

[0085] Set the carrier's motion trajectory: drive eastward for 21600s (6h), then drive 45deg northwest for 21600s (6h). During this process, the carrier stops for 60s every 540s to make zero-speed corrections. The motion characteristics between the parking points are the same, including acceleration, constant speed, and deceleration. The acceleration is 0.2m / s 2 and -0.2m / s 2 , acceleration time is 5s, constant speed lasts 530s, deceleration time is 5s. The total simulation time is 43200s (12h).

[0086] Compare the position correction effects of the following different correction methods.

[0087] 1) System 1: An inertial navigation system that uses trigonometric functions to fit the velocity error curve for position correction.

[0088] 2) System 2: An inertial navigation system that uses a quadratic function to fit the velocity error curve for position correction.

[0089] 3) System 3: An inertial navigation system that uses the method of the present invention to correct position errors.

[0090] 4)system4: Inertial navigation system without position error correction.

[0091] Figure 7 and Figure 8 For the comparison results, Figure 7 It shows the comparison of the latitude position error between the present invention and the uncorrected inertial navigation system and other correction methods. Figure 8 The comparison of the position error in the longitude direction between the inertial navigation system of the present invention and the uncorrected inertial navigation system and other correction methods is shown. The results show that the maximum position error in the latitude direction of the inertial navigation system (system4) before correction reaches 12000m, and the maximum position error in the longitude direction reaches 8000m; the maximum position error in the latitude direction of the inertial navigation system (system2) corrected by zero speed through conventional quadratic curve fitting reaches 7000m, and the maximum position error in the longitude direction reaches 6000m; the maximum position error in the latitude direction of the inertial navigation system (system1) corrected by zero speed through trigonometric function fitting reaches 2700m, and the maximum position error in the longitude direction reaches 3000m; the maximum position error in the latitude direction of the inertial navigation system (system3) corrected by the method of the present invention does not exceed 1500m, and the maximum position error in the longitude direction reaches 800m. It can be seen that the method of the present invention can compensate for the position error of the inertial navigation system, and the effect is significant compared with other methods.

[0092] Another embodiment of the present invention provides a zero-speed correction navigation system based on exponential function fitting, the system comprising:

[0093] A data acquisition module configured to acquire speed and position data output by an inertial navigation system and output values ​​of a three-axis accelerometer at N sampling points in real time;

[0094] A zero-speed detection module, which is configured to determine the current state of the carrier according to the output values ​​of the three-axis accelerometer at N sampling points; the state includes a zero-speed state and a non-zero-speed state;

[0095] The speed error estimation module is configured to fit the speed error curve using an exponential function according to the speed data output by the inertial navigation system when the current state of the carrier is a zero-speed state, so as to obtain a speed error equation;

[0096] A position error estimation module configured to perform an integral operation on a velocity error equation within a time period elapsed from the completion of the initial alignment to obtain a position error estimation value for the time period;

[0097] The position correction module is configured to compensate the position error estimate value to the position data output by the inertial navigation system at the current moment to obtain the corrected position data.

[0098] In this embodiment, optionally, the determining of the current state of the carrier according to the three-axis accelerometer output values ​​of N sampling points in the zero-speed detection module includes: calculating the variance of the three-axis accelerometer output values ​​of the N sampling points, and determining whether the variance is less than a preset threshold value, if so, indicating that the current state of the carrier is a zero-speed state, i.e., a parking state, otherwise, it is a non-zero-speed state; when the carrier is in a non-zero-speed state, calculating the variance of the three-axis accelerometer output values ​​of the next group of N sampling points and re-determining.

[0099] In this embodiment, optionally, in the speed error estimation module, fitting the speed error curve using an exponential function according to the speed data output by the inertial navigation to obtain the speed error equation includes:

[0100] Assume that there are N zero-speed states, and the time from the kth zero-speed state to the end of the initial alignment is t k , k = 1, 2, ..., N; the initial alignment refers to the process of pointing each coordinate axis of the inertial navigation coordinate system relative to the reference coordinate system; then the speed error curve corresponding to the N-time zero speed state is expressed as:

[0101]

[0102] In the formula, δV k represents the speed error of the kth zero-speed state; a, b, c represent the speed error curve coefficients; represents the Schura frequency, g represents the acceleration due to gravity, and R represents the equatorial mean radius;

[0103] The speed error curve coefficient is calculated using the least squares method, and then the speed error equation is obtained: δV(t)=a+be ωt +ce -ωt .

[0104] In this embodiment, optionally, the formula for integrating the velocity error equation within the time period elapsed from the completion of the initial alignment in the position error estimation module is:

[0105]

[0106] Where δP represents the position error.

[0107] The function of a zero-speed correction navigation system based on exponential function fitting in an embodiment of the present invention can be described by the aforementioned zero-speed correction navigation method based on exponential function fitting. Therefore, for the parts not described in detail in the system embodiment, please refer to the above method embodiment and will not be repeated here.

[0108] Although the present invention has been described according to a limited number of embodiments, it will be apparent to those skilled in the art, with the benefit of the above description, that other embodiments are contemplated within the scope of the invention thus described. The disclosure of the present invention is intended to be illustrative rather than restrictive of the scope of the invention, which is defined by the appended claims.

Claims

1. A zero-speed correction navigation method based on exponential function fitting, characterized in that: The following steps are involved: Obtain the speed and position data of the inertial navigation output and the three-axis accelerometer output values ​​of N sampling points in real time; Determine the current state of the carrier according to the output values ​​of the three-axis accelerometer at N sampling points; the state includes a zero-speed state and a non-zero-speed state; When the current state of the carrier is zero speed, the speed error curve is fitted using an exponential function according to the speed data output by the inertial navigation system to obtain the speed error equation; Integrate the velocity error equation within the time period from the completion of the initial alignment to obtain an estimated position error value for the time period; The position error estimate is compensated to the position data output by the inertial navigation system at the current moment to obtain the corrected position data.

2. The zero-speed correction navigation method based on exponential function fitting according to claim 1 is characterized in that: The method of judging the current state of the carrier according to the output values ​​of the three-axis accelerometer at N sampling points includes: calculating the variance of the output values ​​of the three-axis accelerometer at the N sampling points, and judging whether the variance is less than a preset threshold value, if so, it indicates that the current state of the carrier is a zero-speed state, i.e., a parking state, otherwise, it is a non-zero-speed state.

3. The zero-speed correction navigation method based on exponential function fitting according to claim 2 is characterized in that: When the current state of the carrier is a non-zero speed state, the variance of the triaxial accelerometer output values ​​of the next group of N sampling points is calculated and re-judged.

4. The zero-speed correction navigation method based on exponential function fitting according to claim 3 is characterized in that: The calculation formula of the variance is: In the formula, represents the output value of the triaxial accelerometer at the kth sampling point; N represents the total number of sampling points.

5. The zero-speed correction navigation method based on exponential function fitting according to claim 1 is characterized in that: According to the speed data output by the inertial navigation system, the speed error curve is fitted using an exponential function to obtain the speed error equation, which includes: Assume that there are N zero-speed states, and the time from the kth zero-speed state to the end of the initial alignment is t k , k = 1, 2, ..., N; the initial alignment refers to the process of pointing each coordinate axis of the inertial navigation coordinate system relative to the reference coordinate system; then the velocity error curve corresponding to the N-time zero-speed state is expressed as: In the formula, δV k represents the speed error of the kth zero-speed state; a, b, c represent the speed error curve coefficients; represents the Schura frequency, g represents the acceleration due to gravity, and R represents the equatorial mean radius; The speed error curve coefficient is calculated using the least squares method, and then the speed error equation is obtained: δV(t)=a+be ωt +ce -ωt .

6. The zero-speed correction navigation method based on exponential function fitting according to claim 5 is characterized in that: The formula for integrating the velocity error equation within the time period from the completion of the initial alignment is: Where δP represents the position error.

7. A zero-speed correction navigation system based on exponential function fitting, characterized in that: include: A data acquisition module configured to acquire speed and position data output by an inertial navigation system and output values ​​of a three-axis accelerometer at N sampling points in real time; A zero-speed detection module, which is configured to determine the current state of the carrier according to the output values ​​of the three-axis accelerometer at N sampling points; the state includes a zero-speed state and a non-zero-speed state; The speed error estimation module is configured to fit the speed error curve using an exponential function according to the speed data output by the inertial navigation system when the current state of the carrier is a zero-speed state, so as to obtain a speed error equation; A position error estimation module configured to perform an integral operation on a velocity error equation within a time period elapsed from the completion of the initial alignment to obtain a position error estimation value for the time period; The position correction module is configured to compensate the position error estimate value to the position data output by the inertial navigation system at the current moment to obtain the corrected position data.

8. The zero-speed correction navigation system based on exponential function fitting according to claim 7, characterized in that: The method of judging the current state of the carrier according to the output values ​​of the three-axis accelerometer at N sampling points in the zero-speed detection module includes: calculating the variance of the output values ​​of the three-axis accelerometer at the N sampling points, and judging whether the variance is less than a preset threshold value, if so, it indicates that the current state of the carrier is a zero-speed state, i.e., a parking state, otherwise, it is a non-zero-speed state; when the carrier is in a non-zero-speed state, calculating the variance of the output values ​​of the three-axis accelerometer at the next group of N sampling points and re-judging.

9. The zero-speed correction navigation system based on exponential function fitting according to claim 7, characterized in that: In the speed error estimation module, the speed error curve is fitted using an exponential function according to the speed data output by the inertial navigation system to obtain the speed error equation, which includes: Assume that there are n zero-speed states, and the time from the kth zero-speed state to the end of the initial alignment is t k , k = 1, 2, ..., N; the initial alignment refers to the process of pointing each coordinate axis of the inertial navigation coordinate system relative to the reference coordinate system; then the speed error curve corresponding to the n-time zero speed state is expressed as: In the formula, δV k represents the speed error of the kth zero-speed state; a, b, c represent the speed error curve coefficients; represents the Schura frequency, g represents the acceleration due to gravity, and R represents the equatorial mean radius; The speed error curve coefficient is calculated using the least squares method, and then the speed error equation is obtained: δV(t)=a+be ωt +ce -ωt .

10. The zero-speed correction navigation system based on exponential function fitting according to claim 9, characterized in that: The formula for integrating the velocity error equation within the time period elapsed from the completion of the initial alignment in the position error estimation module is: Where δP represents the position error.

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