A compass alignment method and system based on nonlinear integral reset control algorithm

Abstract

The present application provides a compass alignment method and system based on a nonlinear integral reset control algorithm, the method comprising: replacing the physical platform of a strapdown inertial navigation system with a mathematical platform, introducing a nonlinear reset mechanism, controlling by designing a reset controller, suppressing system overshoot, and realizing rapid compass alignment of the inertial navigation system; the method comprising the following steps: establishing a strapdown inertial navigation equation and a strapdown inertial navigation system error equation, building a closed-loop system; performing horizontal alignment and azimuth alignment of the strapdown inertial navigation system; performing reset control according to the designed reset controller, and the reset rule is: when the product of the speed value and the position value is less than zero, the speed variable and the position variable are set to zero. The advantage of the present application is that by using reset control and state space feedback design, the convergence time of the present application is reduced by more than 40% compared with the traditional design.

Description

Technical Field

[0001] The present application belongs to the field of inertial navigation, and specifically relates to a compass alignment method and system based on a nonlinear integral reset control algorithm. Background Art

[0002] Inertial technology is a general term for inertial navigation and inertial guidance technology, inertial instrument technology, inertial measurement technology, and inertial test equipment and device technology. It occupies a very important position in national defense science and technology, and is therefore one of the key technological fields developed by the world's industrial powers.

[0003] The inertial navigation system uses gyroscopes and accelerometers to sense the angular velocity and linear velocity of the aircraft, and through an integration process, provides the aircraft with accurate attitude, velocity and position information. It determines whether the aircraft can accurately reach the operating site, successfully carry out the operating mission, and return safely. The strapdown inertial navigation system (abbreviated as strapdown inertial navigation system, SINS) does not require any additional external navigation equipment. It only needs to perform numerical integration calculations on the output values ​​of the inertial measurement elements (gyroscopes and accelerometers) fixed on the carrier to obtain high-precision navigation information such as attitude, velocity and position in a very short time, thereby realizing the navigation and positioning of the carrier.

[0004] Therefore, for a strapdown inertial navigation system with an integration link, obtaining the initial state information of the navigation device is a prerequisite for starting work. The calculation process that determines the initial value of the navigation system is called initial alignment. Initial alignment is a crucial link in the strapdown inertial navigation system, which determines the navigation accuracy and speed of the inertial navigation system.

[0005] According to whether external information is obtained during the initial alignment, it can be divided into self-alignment and non-self-alignment. The self-alignment of the inertial navigation system is the initial alignment achieved by analytical methods using the gravity vector and the earth's rotation angular velocity vector. Self-alignment is only related to its own navigation system, and it can obtain information such as the position, speed and attitude of the spacecraft. The advantage of this alignment method is strong autonomy, and the disadvantage is that the alignment time is long. Non-autonomous alignment can introduce external reference information into the system through electromechanical or optical methods to achieve the initial alignment of the inertial system.

[0006] In practical applications, there are two main types of self-alignment methods: state estimation-based methods and compass alignment methods.

[0007] State estimation methods usually use Kalman filters to obtain fairly accurate misalignment angles. However, in order to implement Kalman filtering, the noise characteristics must be known in advance; and all noise must satisfy the Gaussian distribution model, otherwise the Kalman filter will degenerate or even diverge. In addition, if the state estimation method is used to solve the dynamic alignment problem, it is necessary to introduce a robust Kalman filter in the initial alignment to reduce attitude, velocity, position and sensor errors.

[0008] Kalman filtering based on modern control theory is a commonly used optimal estimation method when integrating multi-source navigation information, such as SINS / GPS combined navigation. However, it sometimes has problems such as difficulty in accurate modeling, large amount of calculation and easy divergence.

[0009] The compass azimuth alignment method combines the "compass effect" with classical control theory.

[0010] The compass azimuth alignment method includes two stages: horizontal alignment and azimuth alignment.

[0011] In the first stage of horizontal alignment, the north velocity error and the east velocity error are considered as feedback items to adjust the direction cosine matrix (DCM) of the entire system. Cosine matrix: The rotation transformation relationship between two rectangular coordinate systems can be described by the direction cosine matrix.

[0012] In the second stage, if the horizontal deviation is deemed small enough, the azimuth deviation is processed using the north velocity error as feedback, which is a result of the compass effect.

[0013] Although compass alignment does not obviously depend on the characteristics of the sensor, the selection parameters of the compass loop of different strapdown inertial navigation systems may also be different. One of the basic principles of controller design is to strike a trade-off between response speed and oscillation. Generally speaking, it is difficult for a linear system to achieve both fast response and small overshoot at the same time. From the perspective of classical control, when a small damping rate is set, a fast response is obtained, but it also causes severe oscillations and takes a long time for the system to return and stabilize and converge. Although traditional compass alignment algorithms are easy to implement, their performance (especially in terms of convergence speed) often cannot meet the needs of practical applications. Summary of the invention

[0014] The purpose of the present application is to overcome the defect of slow compass alignment speed of the existing strapdown inertial navigation system.

[0015] In order to achieve the above object, the present application proposes a compass alignment method based on a nonlinear integral reset control algorithm, the method comprising:

[0016] The physical platform of the strapdown inertial navigation system is replaced by a mathematical platform, a nonlinear reset mechanism is introduced, and reset control is performed through a reset controller to suppress system overshoot and achieve compass alignment.

[0017] The method comprises the following steps:

[0018] Step 1: Establish the strapdown inertial navigation equation and the strapdown inertial navigation system error equation, establish the augmented system, and build a closed-loop system;

[0019] Step 2: Obtain the horizontal alignment and azimuth alignment equations of the strapdown inertial navigation system;

[0020] Step 3: Design a reset controller for closed-loop feedback control. The reset rule is: when the product of the speed value and the position value is less than zero, the speed variable and the position variable are set to zero.

[0021] As an improvement of the above method, the strapdown inertial navigation equation is:

[0022]

[0023]

[0024] in, express The first derivative of The direction cosine matrix representing the transformation from the carrier coordinate system to the computational navigation coordinate system; Indicates that the rate gyro measures the carrier angular velocity; Represents the direction cosine matrix for calculating the transformation from the navigation coordinate system to the carrier coordinate system; Represents the angular velocity of the earth's rotation relative to the geocentric inertial coordinate system; the × operator represents the conversion of a three-dimensional vector into an antisymmetric matrix;

[0025] Indicates the carrier speed calculated by the digital platform; Indicates the carrier specific force measured by the accelerometer; g n Represents the projection of gravitational acceleration in the ideal navigation coordinate system.

[0026] As an improvement of the above method, the state equation of the strapdown inertial navigation system is:

[0027]

[0028] Where X = [δV N δV E φ N φ E φ D ] T represents the state variable, represents the first derivative of X; δVN , δV E Respectively represent the north and east velocity errors; φ N ,φ E and φ D They represent the north and east horizontal error angles and the ground azimuth error angle of the calculated navigation coordinate system relative to the horizontal geographic coordinate system respectively; T represents matrix transposition;

[0029] Indicates error; and denote the north and east accelerometer biases respectively; ε N , ε E and ε D They represent the drift of the north, east and azimuth gyros respectively;

[0030] represents the coefficient matrix; g represents the gravitational acceleration; R represents the radius of the earth; ω N =ω ie Cos(L),ω A =ω ie Sin(L) represents the north and celestial components of the Earth's rotation, ω ie represents the angular velocity of the earth's rotation; L represents the local latitude;

[0031] As an improvement of the above method, the state equation of the closed-loop system is:

[0032]

[0033] Y=[δp N δp E δV N δV E ] T

[0034] Where X'=[δp N δp E δV N δV E φ N φ E φ D ] T represents the state variable, represents the first-order derivative of X'; δp N and δp E represents the northward position deviation and eastward position deviation of the system, and the corresponding velocity errors δV N and δV E The integral of

[0035] Indicates error;

[0036] represents the coefficient matrix;

[0037] and denote the control input, bias term and measured output respectively; represents the output coefficient matrix, I 4×4 Represents the 4×4 identity matrix.

[0038] As an improvement to the above method, the following formula is used to calculate the north horizontal error angle φ of the navigation coordinate system relative to the horizontal geographic coordinate system during horizontal alignment: N Make an estimate:

[0039]

[0040]

[0041] in, Denotes δp E The first derivative of ; Indicates δV E The first derivative of ; Respectively represent the feedback coefficient matrix and the control coefficient matrix; Ι 2×2 represents the 2×2 identity matrix;

[0042] Use the following formula to calculate the east horizontal error angle φ of the navigation coordinate system relative to the horizontal geographic coordinate system: E Make an estimate:

[0043]

[0044]

[0045] in, Denotes δp N The first derivative of ; Indicates δV N The first derivative of ; They represent the feedback coefficient matrix and the control coefficient matrix respectively.

[0046] As an improvement to the above method, the following formula is used for azimuth alignment:

[0047]

[0048]

[0049] in, Represents the feedback coefficient matrix; 5×5 Represents the 5×5 identity matrix.

[0050] As an improvement of the above method, the formula of the reset rule is expressed as:

[0051] If δP N ·δV N <0

[0052] Where + indicates the right limit.

[0053] The present application also provides a compass alignment system based on a nonlinear integral reset control algorithm, which is implemented based on the above method. The system includes:

[0054] Build a closed-loop system module to establish the strapdown inertial navigation equation and the strapdown inertial navigation system error equation, establish an augmented system, and build a closed-loop system;

[0055] A horizontal and azimuth alignment module for obtaining the horizontal alignment and azimuth alignment equations of the strapdown inertial navigation system; and

[0056] The reset control module is used to design a reset controller for closed-loop feedback control. The reset rule is: when the product of the speed value and the position value is less than zero, the speed variable and the position variable are set to zero.

[0057] Compared with the prior art, the advantages of this application are:

[0058] The compass alignment method based on the nonlinear integral reset control algorithm provided by the present application proposes a fast nonlinear alignment algorithm, which differs from the traditional method in two main aspects. First, most of the existing compass alignment methods use frequency domain transfer functions to represent the system and design feedback controllers, but cannot achieve accurate pole placement. On the contrary, this patent introduces state space representation, thereby obtaining more degrees of freedom for the controller. Then, reset control is introduced to attenuate the overshoot of the closed-loop system. As we all know, designing a satisfactory controller sometimes means a trade-off between fast response and small overshoot, which is difficult to achieve simultaneously in a linear system. By designing a reset controller, the system overshoot can be avoided through the process of integral reset, thereby achieving a significant reduction in the overshoot of the alignment process. Therefore, it is not difficult to see from the simulation results that by using reset control and state space feedback design, the convergence time of the present application is reduced by more than 40%. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 Shown is the block diagram of the compass algorithm principle;

[0060] Figure 2 Shown is a block diagram of the principle of horizontal alignment based on reset control;

[0061] Figure 3 Shown is a block diagram of the principle of azimuth alignment based on reset control;

[0062] Figure 4 Shown is a comparison of horizontal alignment of reset control and conventional methods;

[0063] Figure 5 Shown is an azimuth alignment comparison;

[0064] Figure 6 Shown is a comparison of the transient level alignment process between reset control and conventional methods;

[0065] Figure 7 Shown is a diagram of the transient process of azimuth alignment;

[0066] Figure 8 Shown is a flow chart of a compass alignment method based on a nonlinear integral reset control algorithm. DETAILED DESCRIPTION

[0067] The technical solution of the present application is described in detail below with reference to the accompanying drawings.

[0068] Compass alignment is often used in navigation systems because it does not require the characteristics of sensor noise. However, the compass alignment process is relatively slow, especially in the azimuth channel. The present application proposes a compass alignment method and system based on a nonlinear integral reset control algorithm. The purpose is to design a compass fast alignment algorithm based on a nonlinear integral reset control system, replace the physical platform with a mathematical platform, introduce a nonlinear reset mechanism, and suppress system overshoot through reset control to overcome the basic limitations of linear systems, including the time domain and the frequency domain. This can greatly improve the speed of compass alignment, suppress system overshoot, ensure the system's fast response speed, and achieve system compass fast alignment. The self-alignment time of the inertial navigation system using the present application can be shortened by more than 40% without losing accuracy.

[0069] like Figure 1 As shown in the figure, the design idea of ​​the compass alignment method and system based on the nonlinear integral reset control algorithm is: the system takes the position p ref and speed V ref As input, they are all expressed in calculation frames, and after calculation by the controller, the angular rate setting value ω is obtained c , and use the angular rate setting value as the input of the Digital Platform.

[0070] Traditionally, a transfer function is used to design a feedback controller. The basic design idea of ​​this application is to design a feedback controller using an integral reset algorithm. The reset principle is that when the product of the speed value and the position value is less than zero, the speed variable and the position variable are reset to zero.

[0071] Example 1

[0072] like Figure 8 As shown, the compass alignment method based on the nonlinear integral reset control algorithm includes the following steps:

[0073] Step 1: Build the strapdown inertial navigation system dynamics model (Digital Platform);

[0074] Assume that the strapdown inertial navigation system is located at a geographical location (referring to longitude and latitude), especially latitude. Under this assumption, the dynamic model of the strapdown inertial navigation system can be described as follows:

[0075]

[0076] in, The direction cosine matrix (DCM) representing the transformation from the carrier coordinate system to the ideal navigation coordinate system; express The first-order derivative of ; the carrier coordinate system is an inertial system coordinate system whose origin is located at the center or center of gravity of the carrier inertial navigation system; the origin of the ideal navigation coordinate system is fixed at the sensor position on the surface of the earth and moves with the movement of the carrier. The navigation coordinate system rotates at a speed of 15° per hour relative to the inertial system. It represents the theoretical angular velocity in the carrier coordinate system; represents the angular velocity of the Earth's rotation relative to the Earth-centered inertial coordinate system; The direction cosine matrix representing the transformation from the ideal navigation coordinate system to the carrier coordinate system; the × operator represents the transformation of the three-dimensional vector into an antisymmetric matrix;

[0077] V n Indicates the actual speed of the strapdown inertial navigation system; Indicates V n The first derivative of b Indicates the actual specific force output by the accelerometer; g n Represents the projection of gravitational acceleration in the ideal navigation coordinate system.

[0078] In reality, the exact navigation coordinates are unknown. We maintain a calculated coordinate based on sensor data. The strapdown inertial navigation equation can be described as:

[0079]

[0080] in, The direction cosine matrix (DCM) representing the transformation from the carrier coordinate system to the computational navigation coordinate system; express The first derivative of; In the strapdown inertial navigation system, there is no real physical platform, but a "approximate" platform is obtained by mathematical calculation, which is called the mathematical platform. The calculated navigation coordinate system is the navigation coordinate system obtained by mathematical calculation, and the angular error between it and the ideal navigation coordinate system is the misalignment angle; Indicates that the rate gyro measures the carrier angular velocity; Represents the direction cosine matrix for calculating the transformation from the navigation coordinate system to the carrier coordinate system;

[0081] Indicates the carrier speed calculated by the digital platform; Indicates that the accelerometer measures the carrier specific force.

[0082] Step 2: Build the strapdown inertial navigation system error model;

[0083] For static alignment, the position and velocity are Comparing (Equation 1) and (Equation 2), assuming that the deviation after rough alignment is small, the error equation can be obtained:

[0084]

[0085] Among them, φ n =[φ N φ E φ D ] T represents the alignment angle error vector, φ N ,φ E and φ D They represent the north and east horizontal error angles and the ground azimuth error angle of the calculated navigation coordinate system relative to the horizontal geographic coordinate system, respectively, and T represents the matrix transpose; Represents φ n The first derivative of ; represents the gyro error vector, ε N , ε E and ε D They represent the drift of the north, east and azimuth gyros respectively;

[0086] δV n =[δV N δV E δV D ] T represents the velocity error vector, δV N , δV E are the north and east velocity errors, δV D represents the ground velocity error, Indicates δV n The first derivative of ; represents the accelerometer error vector, and denote the north and east accelerometer biases, respectively, Represents the ground bias of the accelerometer.

[0087] Further describe the error equation of the inertial navigation system:

[0088]

[0089] in, Indicates δV N The first derivative of ; Indicates δV E The first derivative of ; Represents φ N The first derivative of ; Represents φ E The first derivative of ; Represents φ D The first derivative of N =ω ie Cos(L),ω A =ω ie Sin(L) is the vertical component of the Earth's rotation to the north and to the sky, ω ie represents the angular velocity of the earth's rotation; R represents the radius of the earth; L represents the local latitude; and g represents the acceleration due to gravity.

[0090] Write (Equation 4) as the state equation:

[0091]

[0092] Where X = [δV N δV E φ N φ E φ D ] T represents the state variable, represents the first derivative of X; Indicates error; represents the coefficient matrix,

[0093] Step 3: Establish an augmented system and build a closed-loop system;

[0094] Similar to the traditional compass alignment method, the present application divides the alignment into two stages: horizontal alignment and azimuth alignment. However, unlike the traditional method, the present application uses an augmented state equation instead of a transfer function to describe the system, which makes the controller more flexible and may achieve higher performance.

[0095] like Figure 1 As shown, the traditional compass alignment method only uses the angular rate command ω c As the control input signal, it is fed back into the DCM calculation. Considering that we are dealing with a static alignment problem, δV in (Eq. 4) N and δV E In addition, in order to eliminate the influence of gyro bias on alignment, we can increase the north position deviation δp of the system Nand the eastward position deviation δp E , which are the corresponding velocity errors δV N and δV E Therefore, The augmented system can be described as follows:

[0096] X=[δp N δp E δV N δV E φ N φ E φ D ] T (Formula 6)

[0097]

[0098]

[0099] The closed-loop state equation of the system is:

[0100]

[0101] Y=[δp N δp E δV N δV E ] T (Formula 10)

[0102] in, and are the control input, bias term and measured output respectively. is the output coefficient matrix, I 4×4 Represents the 4×4 identity matrix.

[0103] Step 4: Obtain the horizontal alignment and azimuth alignment equations respectively;

[0104] The main idea of ​​simplifying compass alignment is to achieve high-precision attitude estimation based on the compass effects of the north loop and the east loop. In the horizontal alignment stage, the east loop and the north loop are considered separately to estimate φ N and φ E .

[0105] Horizontal Alignment:

[0106] For φ N The estimation of is done using the following equation:

[0107]

[0108]

[0109] in, Denotes δp E The first derivative of ; Indicates δV E The first derivative of ; are feedback coefficient matrix and control coefficient matrix respectively; Ι 2×2 Represents the 2×2 identity matrix.

[0110] Using the northbound loop to estimate φ E , the equation is as follows:

[0111]

[0112]

[0113] in, Denotes δp N The first derivative of ; Indicates δV N The first derivative of ; are the feedback coefficient matrix and the control coefficient matrix respectively.

[0114] Azimuth Alignment:

[0115] For azimuth alignment, this application provides the following equation:

[0116]

[0117]

[0118] Among them, X, A f and d are defined as X in (Formula 6), A in (Formula 7), and d in (Formula 8); is the feedback coefficient matrix; 5×5 Represents the 5×5 identity matrix.

[0119] Step 5: Reset Controller Design

[0120] According to the above description, it can be seen that (Equations 15 and 16) are N , δV E ,δp N and δp E For the observables, the alignment process has become a feedback control design problem.

[0121] Because the earth's rotation speed is 15deg / h, which is relatively small for the gyroscope, and considering the noise of the gyroscope, it takes a certain amount of time to accumulate to obtain effective observations. When using the control law of the PID control method, the error curve will oscillate during the alignment process, which will increase the alignment time.

[0122] If a nonlinear control strategy is adopted, the alignment time is expected to be reduced.

[0123] Reset rules:

[0124] The reset rule is that when the product of the speed value and the position value is less than zero, the speed variable and the position variable are reset to zero.

[0125]

[0126] Where + indicates the right limit.

[0127] Since the inertial navigation system is solved in each cycle, it is judged whether (Equation 17) is established in each cycle. When (Equation 17) is established, in the current cycle, δP N and δV N are all set to zero, that is, at the current moment, δP is artificially created N and δV N Jump.

[0128] The principle block diagram of the horizontal alignment controller for reset control is as follows Figure 2 As shown, K E3 The integral link introduces a reset mechanism, based on the speed error To control the reset time.

[0129] The principle block diagram of the reset control azimuth alignment controller is as follows Figure 3 As shown, the azimuth alignment is similar to the horizontal alignment. A reset mechanism is introduced into the integral link inside K(s), and the speed error controls the reset moment.

[0130] The following is a simulation verification of the method of this application:

[0131] Latitude is not a big problem as long as it is not close to the polar regions. In the simulation verification, the latitude L = 40° is assumed without loss of generality. The gyro zero drift stability is 0.01° / h, and the accelerometer zero bias stability is 0.5e-4g.

[0132] The simulation results are as follows Figure 4-Figure 7 The simulation results show that, in order to achieve the same alignment accuracy, the compass alignment algorithm using a nonlinear controller can reduce the rising speed from 180s in the traditional method to 120s compared with the traditional algorithm, and static alignment can be completed within 2.5 minutes.

[0133] from Figure 6 It can be observed that when δV N ×δP N When <0, δP N It is reset in about 3 seconds. After that, the system is rapidly damped and converges to zero. It is not difficult to see that if the control parameters are selected correctly, the introduction of reset control greatly reduces the adjustment time and suppresses the oscillation of the closed-loop system.

[0134] Compared with the traditional method, the advantage of this method is more obvious in the azimuth alignment process, because azimuth alignment takes up most of the time in the entire alignment process. It is worth noting that the azimuth alignment error in this simulation is

[0135] For the method proposed in this application, entering a satisfactory error zone It takes about 120 seconds, while for traditional methods, it takes more than 300 seconds to stabilize. Figure 7 It can be seen that when the first δP N and δV N When reset, the closed-loop system is almost stable. After this, even if δP N and δV N In the case of smaller nearby oscillations, the estimated alignment angle is always within an acceptable region.

[0136] Example 2

[0137] The present application also provides a compass alignment system based on a nonlinear integral reset control algorithm, which is implemented based on the above method. The system includes:

[0138] Build a closed-loop system module to establish the strapdown inertial navigation equation and the strapdown inertial navigation system error equation, establish an augmented system, and build a closed-loop system;

[0139] Horizontal and azimuth alignment module, used to obtain the horizontal alignment and azimuth alignment equations of the strapdown inertial navigation system;

[0140] The reset control module is used to design a reset controller for closed-loop feedback control. The reset rule is: when the product of the speed value and the position value is less than zero, the speed variable and the position variable are set to zero.

[0141] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present application and are not intended to limit it. Although the present application is described in detail with reference to the embodiments, a person skilled in the art should understand that any modification or equivalent replacement of the technical solution of the present application does not depart from the spirit and scope of the technical solution of the present application and should be included in the scope of the claims of the present application.

Claims

1. A compass alignment method based on a nonlinear integral reset control algorithm, the method comprising: The physical platform of the strapdown inertial navigation system is replaced by a mathematical platform, a nonlinear reset mechanism is introduced, and reset control is performed through a reset controller to suppress system overshoot and achieve compass alignment. The method comprises the following steps: Step 1: Establish the strapdown inertial navigation equation and the strapdown inertial navigation system error equation, establish the augmented system, and build a closed-loop system; Step 2: Obtain the horizontal alignment and azimuth alignment equations of the strapdown inertial navigation system; Step 3: Design a reset controller for closed-loop feedback control. The reset rule is: when the product of the speed value and the position value is less than zero, the speed variable and the position variable are set to zero; The state equation of the strapdown inertial navigation system is: ； in, represents the state variable, express The first derivative of ; , Represent the north and east velocity errors respectively; , and They represent the north and east horizontal error angles and the ground azimuth error angle of the calculated navigation coordinate system relative to the horizontal geographic coordinate system respectively; T Represents matrix transpose; Indicates error; and denote the north and east accelerometer biases, respectively; , and They represent the drift of the north, east and azimuth gyros respectively; represents the coefficient matrix; g represents the acceleration due to gravity; represents the radius of the Earth; , They represent the north and celestial vertical components of the Earth's rotation, represents the angular velocity of the earth's rotation; L Indicates the local latitude; The state equation of the closed-loop system is: ； ； in, represents the state variable, express The first derivative of ; and represents the north position deviation and east position deviation of the system, and the corresponding velocity errors are and The integral of Indicates error; represents the coefficient matrix; and denote the control input, bias term and measured output respectively; represents the output coefficient matrix, express The identity matrix of .

2. The compass alignment method based on the nonlinear integral reset control algorithm according to claim 1, characterized in that: The strapdown navigation equation is: ; ； in, express The first derivative of The direction cosine matrix representing the transformation from the carrier coordinate system to the computational navigation coordinate system; Indicates that the rate gyro measures the carrier angular velocity; Represents the direction cosine matrix for calculating the transformation from the navigation coordinate system to the carrier coordinate system; represents the angular velocity of the Earth's rotation relative to the Earth-centered inertial coordinate system; The operator represents the conversion of a three-dimensional vector into an antisymmetric matrix; Indicates the carrier speed calculated by the digital platform; represents the carrier specific force measured by the accelerometer; Represents the projection of gravitational acceleration in the ideal navigation coordinate system.

3. The compass alignment method based on the nonlinear integral reset control algorithm according to claim 1, characterized in that: When aligning horizontally, use the following formula to calculate the north horizontal error angle of the navigation coordinate system relative to the horizontal geographic coordinate system: Make an estimate: ； , ； in, express The first derivative of ; express The first derivative of ; denote the feedback coefficient matrix and the control coefficient matrix respectively; express The identity matrix of Use the following formula to calculate the east horizontal error angle of the navigation coordinate system relative to the horizontal geographic coordinate system: Make an estimate: ； , ； in, express The first derivative of ; express The first derivative of ; They represent the feedback coefficient matrix and the control coefficient matrix respectively.

4. The compass alignment method based on the nonlinear integral reset control algorithm according to claim 1, characterized in that: Use the following formula for azimuth alignment: ； , ； in, represents the feedback coefficient matrix; express The identity matrix of .

5. The compass alignment method based on nonlinear integral reset control algorithm according to claim 1, characterized in that: The formula of the reset rule is expressed as: ,if Where + indicates the right limit.

6. A compass alignment system based on a nonlinear integral reset control algorithm, implemented based on the method of any one of claims 1 to 5, characterized in that: The system comprises: Build a closed-loop system module to establish the strapdown inertial navigation equation and the strapdown inertial navigation system error equation, establish an augmented system, and build a closed-loop system; A horizontal and azimuth alignment module for obtaining the horizontal alignment and azimuth alignment equations of the strapdown inertial navigation system; and The reset control module is used to design a reset controller for closed-loop feedback control. The reset rule is: when the product of the speed value and the position value is less than zero, the speed variable and the position variable are set to zero.

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