A combined navigation method based on inertial / doppler log plus damping state

Abstract

The application provides a kind of combined navigation method based on inertia / doppler log plus damping state, comprising: obtaining data source required for algorithm debugging as training sample;Speed, acceleration, angular velocity, angular acceleration of training sample under each navigation state are analyzed, and the navigation state criterion of system is obtained;Through training sample, the combined navigation filter of doppler log is accurately modeled;Through training sample, the optimal design of damping navigation network parameters is carried out;According to the motion state of the carrier obtained by the carrier navigation state criterion, the speed information output is switched, and the optimized speed of the comprehensive system is finally obtained, the speed output of combined navigation and damping navigation is analyzed respectively, and the low-frequency speed error is suppressed.The method has good practical engineering application value, and aims to solve the problems of slow convergence, large speed error and large positioning error of traditional combined navigation.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of navigation positioning, in particular to a combined navigation method based on inertia / Doppler log plus damping state. BACKGROUND

[0002] Since the 21st century, with the increasing investment of human beings in the utilization of oceans and the development of oceans, autonomous underwater vehicles (AUVs) have attracted more and more attention, and have been rapidly developed in both military fields such as battlefield monitoring and covert attack and civil fields such as seawater detection and marine geological exploration. Navigation refers to the autonomous movement process of a person or object from an initial position to a target position by obtaining the state of the object. At present, achieving high-precision autonomous navigation is still a technology that needs to be continuously improved.

[0003] Inertial navigation is a navigation method developed on the basis of Newton's inertial principle. Inertial elements (gyroscopes and accelerometers) are used to measure the angular velocity and acceleration of a carrier, and the attitude, velocity and position are obtained through digital filtering, integration and other operations, so as to achieve the purpose of navigation and positioning of the carrier. Since the devices that constitute the inertial navigation system are installed in the carrier, the system does not rely on external information and does not radiate energy to the outside world when working, and is not easily disturbed, so it is currently an excellent autonomous navigation system.

[0004] However, since the error of a pure inertial navigation system is oscillating and accumulates over time, especially for carriers that work for a long time and have small acceleration, external information needs to be introduced to suppress the system error. In underwater environments, a Doppler log is generally used to provide external velocity, and an inertial / Doppler log combined navigation system is formed with the inertial navigation system. Through some specific information fusion methods, the information output of the combined system is more reliable. SUMMARY

[0005] In order to solve the technical problems proposed in the background art, the present application provides a combined navigation method based on inertia / Doppler log plus damping state, which has good practical engineering application value and aims to solve the problems of slow convergence speed, large velocity error and large positioning error of traditional combined navigation.

[0006] In order to achieve the above purpose, the present application adopts the following technical scheme:

[0007] A combined navigation method based on inertia / Doppler log plus damping state, comprising the following steps:

[0008] Step 1: Obtain the data source required for algorithm debugging as a training sample;

[0009] Step two, the speed, acceleration, angular velocity, angular acceleration of the training sample in each navigation state are analyzed to obtain the navigation state criterion of the system;

[0010] Step three, the speed output of Doppler log is detected to determine whether the current speed output of Doppler log is available;

[0011] Step four, Doppler log integrated navigation filtering is accurately modeled through the training sample;

[0012] Step five, the optimal design of damping navigation network parameters is performed through the training sample;

[0013] Step six, the motion state of the carrier is obtained according to the carrier navigation state criterion, the speed information output in steps four and five is switched, and the optimized speed of the comprehensive system is finally obtained, so as to improve the carrier speed adaptability of the entire integrated navigation system;

[0014] Step seven, the speed outputs of integrated navigation and damping navigation are respectively analyzed, and a high-pass digital filter is designed to suppress low-frequency speed error.

[0015] Further, in step one, the data source obtained requires the navigation carrier to have the following voyage:

[0016] Uniform straight-line voyage;

[0017] Variable speed voyage;

[0018] Large maneuvering voyage;

[0019] Submersion and surfacing voyage;

[0020] And the change characteristics of acceleration, angular velocity and angular acceleration in each voyage are counted.

[0021] Further, in step three, the data of Doppler log is analyzed to evaluate the measurement accuracy of Doppler log, and the fault detection method is specified according to the measurement accuracy; the detection method uses innovation chi-square detection; it uses measurement innovation δr k The method for detecting and isolating filter faults has good detection effect on large data anomalies; the measurement innovation reflects the consistency between the state estimate and the measurement value, and under ideal conditions, it is subject to normal distribution with mean value 0;

[0022]

[0023] δr k ~ N(0, C k )

[0024]

[0025]

[0026] where H k is the observation matrix of the system, Z k is the observation matrix, is the state estimation matrix from k time to k-1 time, N(0,C k ) represents a normal distribution with mean 0 and variance C k , P k,k-1 is the transition matrix from k time to k-1 time, R k is the variance matrix of the measurement noise, T k obeys chi-square distribution is the variable to be detected.

[0027] Further, in the fourth step, the velocity integrated navigation algorithm takes the inertial system error equation as the state equation of the integrated navigation system, takes the difference between the inertial measured velocity and the odometry measured velocity as the observation of the system and establishes the observation equation, adopts the optimal estimation theory to perform real-time estimation and compensation on the state of the system, so as to suppress the influence of inertial device errors on the navigation accuracy.

[0028] The longitude and latitude errors of the system are selected The two variables in (δv e , δv n ) are longitude error and latitude error respectively, the horizontal velocity error (δv e , δv n ) in the navigation system (n system), the two variables in (φ e , φ n , φ u ) are eastward velocity error and northward velocity error respectively, the attitude error (φ e , φ n , φ u ) in the navigation system (n system), the three variables in (φ , φ , φ

[0029] ) are roll error, pitch error and heading deviation respectively, the horizontal accelerometer zero offset in the carrier coordinate system x and the gyro zero offset ε = [ε y ε z ] in the carrier coordinate system are taken as state variables, so the state variables are:

[0030] The state equation of the integrated navigation system is:

[0031]

[0032] where · represents the differential of the variable, Rm R represents the radius of the earth latitude circle, R n f represents the radius of the earth longitude circle, f n represents the projection of the accelerometer in the navigation system, represents the projection of the angular velocity of the navigation system relative to the earth system in the navigation system, represents the projection of the angular velocity of the earth system relative to the inertial system in the navigation system, represents the projection of the angular velocity of the navigation system relative to the inertial system in the navigation system, v n represents the projection of the navigation solution velocity in the navigation system, φ n = [φ e φ n φ u represents the projection of the attitude angle error in the navigation system;

[0033] Taking the difference between the inertial measurement velocity and the Doppler log measurement velocity as the observation, we have:

[0034]

[0035] wherein, and represent the eastward and northward projections of the inertial navigation system solution velocity information, respectively, and represent the eastward and northward projections of the Doppler log output velocity information, respectively;

[0036] According to the state equation and the observation of the integrated navigation system, the integrated navigation system equation is established, and the state error is estimated and compensated in real time by using optimal estimation.

[0037] Further, in step five, according to the classical control theory, the parameters H(s) of the damping navigation network are optimally designed; wherein the input of the damping network is the difference between the system solution velocity and the Doppler log output velocity, and the output is the velocity corrected by the damping network;

[0038] Generally, the design method of the second-order damping network is to fix the damping network as follows:

[0039]

[0040] wherein ω1, ω2, ω3, ω4 are the damping network parameters;

[0041] On this basis, first, the parameters are preliminarily designed through the required gain characteristics and phase characteristics, and then the specific parameters of the damping network are further designed according to the peak value of the closed-loop gain of the second-order system corresponding to the damping coefficient required by the design; if the form of the damping network is transformed as follows:

[0042]

[0043] Wherein, ω1, ω2, A, B are the parameters of the form transformation damping network;

[0044] The classical control theory method of closed loop leading pole is used to design the damping network, so that the equivalent damping network is used to analyze the performance and function of the original damping network; the damping network design method is not only simple for the design process of the damping network parameters, but also is beneficial to the analysis and research of the network performance.

[0045] Further, in step six, according to the motion parameter variation characteristics of the ship in each motion state, and in combination with the error variation characteristics of the Doppler log speed error in each maneuvering condition, whether the Doppler log speed error will change sharply can be judged through the motion parameters; in order to obtain higher precision of the inertial / Doppler log combined navigation system, the system needs to work in the combined navigation mode when the Doppler log speed error changes sharply, and work in the damping mode when the speed error changes slightly; the speed error of the Doppler log changes sharply in the following conditions: a) turning motion; b) linear acceleration and deceleration motion; c) sea wind, sea current changes sharply or log failure; therefore, the inertial / Doppler log damping combined navigation system based on parallel algorithm should be switched to the combined navigation mode in the above three conditions, and work in the damping mode in the remaining states; thus, in combination with the variation law of each motion parameter in each motion state, the combined navigation state switching prediction can be completed.

[0046] Further, in step seven, the main characteristics of the carrier velocity are the synthesis of the swing period function and the impact motion function, the frequency band contains the swing period and higher frequency range, and the frequency band range of the main error source in the carrier velocity includes the Schuler period, the earth period, the Foucault period and the like low frequency characteristics; through analysis of a large amount of real ship test data, the swing situation of the carrier in various sea conditions and the speed error propagation mechanism of the inertial measurement and the log measurement are determined, and spectrum analysis is carried out; on this basis, the setting of the high-pass filter is researched, the low-frequency error signal is filtered out through setting a reasonable high-pass filter, and the speed measurement precision in the ship motion state is improved.

[0047] Compared with the prior art, the beneficial effects of the present application are:

[0048] The combined navigation method based on the inertial / Doppler log damping state provided by the present application has good practical engineering application value, and aims to solve the problems of slow speed convergence, large speed error and large positioning error of the traditional combined navigation. BRIEF DESCRIPTION OF DRAWINGS

[0049] Fig. 1is a flow chart of a combined navigation method of an inertial / doppler log provided by an embodiment of the present application;

[0050] Fig. 2 is a schematic diagram of a combined navigation method of an inertial / doppler log provided by an embodiment of the present application. DETAILED DESCRIPTION

[0051] The specific embodiments of the present application provided in the following are described in detail with reference to the accompanying drawings.

[0052] As Figs. 1-2 shown, a combined navigation method based on an inertial / doppler log plus damping state includes the following steps:

[0053] Step one, obtain the data source required for algorithm debugging as a training sample;

[0054] Step two, perform feature analysis of speed, acceleration, angular velocity, and angular acceleration in each navigation state on the training sample, and obtain the navigation state criterion of the system;

[0055] Step three, perform fault detection on the speed output of the doppler log, and determine whether the speed output of the current doppler log is available;

[0056] Step four, perform accurate modeling on the doppler log combined navigation filtering through the training sample;

[0057] Step five, perform optimal design on the damping navigation network parameters through the training sample;

[0058] Step six, obtain the motion state of the carrier according to the carrier navigation state criterion, switch the speed information output in steps four and five, and finally obtain the optimized speed of the comprehensive system, thereby improving the carrier speed measurement adaptability of the entire combined navigation system;

[0059] Step seven, perform spectrum analysis on the speed output of the combined navigation and the damping navigation respectively, and perform high-pass digital filter design to realize suppression of low-frequency speed error.

[0060] The specific embodiments are as follows:

[0061] Step one, obtain the data source required for algorithm debugging as a training sample.

[0062] The data source obtained requires the navigation carrier to have the following voyage:

[0063] Uniform straight-line voyage;

[0064] Variable-speed motion voyage;

[0065] Large maneuvering voyage;

[0066] The voyage has the characteristics of diving and floating;

[0067] The acceleration, angular velocity and angular acceleration of each voyage are counted.

[0068] Step two, the training sample is analyzed for the characteristics of speed, acceleration, angular velocity and angular acceleration in each voyage state, and the voyage state criterion of the system is obtained.

[0069] Step three, the speed output of the Doppler log is detected for fault, and it is judged whether the speed output of the current Doppler log is available.

[0070] In step three, the data of the Doppler log is analyzed for statistical characteristics, the measurement accuracy of the Doppler log is evaluated, and the fault detection method is specified accordingly; the detection method uses innovation chi-square detection; it uses the measurement innovation δr k The method for detecting and isolating filter faults has good detection effect on large data anomalies; the measurement innovation reflects the consistency between state estimation and measurement value, and under ideal state, it is subject to normal distribution with mean value of 0;

[0071]

[0072] δr k ~ N(0, C k )

[0073]

[0074]

[0075] Wherein, H k is the observation matrix of the system, Z k is the observation matrix, is the state estimation matrix from k time to k-1 time, N(0, C k ) represents normal distribution with mean value of 0 and variance of C k , P k,k-1 is the transition matrix from k time to k-1 time, R k is the variance matrix of measurement noise, T k is subject to chi-square distribution, which is the variable to be detected.

[0076] Step four, the Doppler log integrated navigation filter is accurately modeled through the training sample.

[0077] In the fourth step, the velocity combination navigation algorithm takes the inertial system error equation as the state equation of the combination navigation system, takes the difference between the inertial measured velocity and the odograph measured velocity as the observation of the system and establishes the observation equation, adopts the optimal estimation theory to perform real-time estimation and compensation on the state of the system, so as to restrain the influence of the inertial device error on the navigation precision.

[0078] Selecting the system latitude and longitude error Two variables in (δL, δB) are longitude error and latitude error respectively, the horizontal velocity error (δv e , δv n ) in the navigation system (n system), two variables in (δv e , δv n ) are eastward velocity error and northward velocity error respectively, the attitude error (φ e , φ n , φ u ) in the navigation system (n system), three variables in (φ e , φ n , φ u ) are roll error, pitch error and heading deviation respectively, the horizontal accelerometer zero offset in the carrier coordinate system and the gyro zero offset ε = [ε x ε y ε z ] in the carrier coordinate system are taken as the state variables, so the state variables are:

[0079]

[0080] The state equation of the combination navigation system is:

[0081]

[0082] Wherein, · represents the differential of the variable, R m represents the radius of the earth latitude circle, R n represents the radius of the earth longitude circle, f n represents the projection of the accelerometer in the navigation system, represents the projection of the rotation angular velocity of the navigation system relative to the earth system in the navigation system, represents the projection of the rotation angular velocity of the earth system relative to the inertial system in the navigation system, represents the projection of the rotation angular velocity of the navigation system relative to the inertial system in the navigation system, v n represents the projection of the navigation solution velocity in the navigation system, φ n = [φ e φ n φ u ] represents the projection of the attitude angle error in the navigation system.

[0083] The difference between the inertial measurement speed and the Doppler speed is taken as the observation, and has:

[0084]

[0085] wherein, and respectively represent the east and north projections of the inertial navigation system calculated speed information, and respectively represent the east and north projections of the Doppler speed information outputted by the Doppler speed meter;

[0086] The combined navigation system equation is established according to the state equation and the observation of the combined navigation system, and the state error is estimated and compensated in real time by using the optimal estimation.

[0087] Step five, the optimal design of the damping navigation network parameters is carried out through the training sample.

[0088] In step five, the parameter H(s) of the damping navigation network is optimally designed according to the classical control theory; wherein the input of the damping network is the difference between the system solution speed and the Doppler speed outputted by the Doppler speed meter, and the output is the speed corrected by the damping network;

[0089] Generally, the design method of the second-order damping network is to fix the damping network as follows:

[0090]

[0091] wherein ω1, ω2, ω3, ω4 are the damping network parameters;

[0092] On this basis, firstly, the parameters are preliminarily designed through the required gain characteristics and phase characteristics, and then the specific parameters of the damping network are further designed according to the peak value of the closed-loop gain of the second-order system corresponding to the damping coefficient required by the design; if the form of the damping network is transformed as:

[0093]

[0094] wherein ω1, ω2, A, B are the damping network parameters after the form transformation;

[0095] The classical control theory method of the closed-loop dominant pole is used to design the damping network, so that the equivalent damping network can be used to analyze the performance and role of the original damping network itself; this damping network design method not only simplifies the design process of the damping network parameters, but also is more conducive to the analysis and research work of the network performance.

[0096] Step six, according to the carrier navigation state criterion to obtain the motion state of the carrier, the speed information output in step four and step five are switched, and the optimized speed of the integrated system is finally obtained, thereby improving the carrier speed measurement adaptability of the entire integrated navigation system.

[0097] In step six, according to the motion parameter variation characteristics of the ship in each motion state, combined with the error variation characteristics of the Doppler log speed measurement error in each maneuvering condition, whether the Doppler log speed measurement error will change sharply can be judged through the motion parameters; in order to obtain higher precision of the inertial / Doppler log integrated navigation system, the system needs to work in the integrated navigation mode when the Doppler log speed measurement error changes sharply, and work in the damping mode when the speed measurement error changes little; the speed measurement error of the Doppler log changes sharply in the following conditions: a) turning motion; b) linear acceleration and deceleration motion; c) sea wind, sea current changes sharply or log failure; therefore, the inertial / Doppler log damping integrated navigation system based on parallel algorithm should be switched to the integrated navigation working mode in the above three conditions, and work in the damping working mode in the remaining states; thus, combined with the variation law of each motion parameter in each motion state, the integrated navigation state switching prediction can be completed.

[0098] Step seven, the speed outputs of the integrated navigation and the damping navigation are respectively subjected to spectrum analysis, and a high-pass digital filter is designed to realize the suppression of low-frequency speed error.

[0099] In step seven, the main feature of the carrier speed is the synthesis of the swing period function and the impact motion function, the frequency band contains the swing period and higher frequency range, and the frequency band range of the main error source of the carrier speed includes the Schuler period, the earth period, the Foucault period and the like low-frequency characteristics; through analysis of a large amount of ship test data, the swing of the carrier in various sea conditions and the speed error propagation mechanism of the inertial measurement and the log measurement are determined, and spectrum analysis is performed; on this basis, the high-pass filter setting research is carried out, and by setting a reasonable high-pass filter, the low-frequency error signal is filtered out, and the speed measurement precision of the ship in the motion state is improved.

[0100] The inertial / Doppler log damping state-based integrated navigation method provided by the application has good practical engineering application value, and aims to solve the problems of slow speed convergence, large speed error and large positioning error of the traditional integrated navigation.

[0101] The above examples are implemented on the premise of the technical scheme of the application, detailed implementation modes and specific operation processes are given, but the protection scope of the application is not limited to the above examples. The methods used in the above examples are all conventional methods unless otherwise specified.

Claims

1. A combined navigation method based on inertial / Doppler log plus damped state, characterized by, It comprises the following steps: Step one, obtaining the data source required by algorithm debugging as training samples; Step two, analyzing the characteristics of speed, acceleration, angular velocity and angular acceleration under each navigation state of the training samples to obtain the navigation state criterion of the system; Step three, detecting the fault of the speed output of the Doppler log to determine whether the current speed output of the Doppler log is available; Step four, accurately modeling the Doppler log integrated navigation filtering through the training samples; Step five, optimally designing the damping navigation network parameters through the training samples; Step six, obtaining the motion state of the carrier according to the carrier navigation state criterion, switching the speed information output in steps four and five, and finally obtaining the optimized speed of the integrated system to improve the carrier speed adaptability of the entire integrated navigation system; Step seven, respectively performing spectrum analysis on the speed outputs of the integrated navigation and the damping navigation, and designing a high-pass digital filter to realize the suppression of low-frequency speed error. In step six, according to the motion parameter variation characteristics of the ship under each motion state and the error variation characteristics of the Doppler log speed error under each maneuvering condition, whether the Doppler log speed error will change dramatically can be determined through the motion parameters. In order to obtain higher precision of the inertial / Doppler log integrated navigation system, the system needs to work in the integrated navigation mode when the Doppler log speed error changes dramatically, and work in the damping mode when the speed error changes slightly. In the following cases, the Doppler log speed error changes dramatically: a) turning motion; b) linear acceleration and deceleration motion; c) sea wind, sea current changes dramatically or log fault; Therefore, the inertial / Doppler log damping integrated navigation system based on parallel algorithm should switch to integrated navigation mode under the above three conditions, and work in damping mode under other conditions. Thus, combined with the variation law of each motion parameter under each motion state, the integrated navigation state switching prediction can be completed.

2. The method of claim 1, wherein, In step one, the data source obtained requires the navigation carrier to have the following voyage: Uniform straight-line voyage; Variable speed voyage; Large maneuvering voyage; Submersion and surfacing voyage; And statistics the variation characteristics of acceleration, angular velocity and angular acceleration under each voyage.

3. The method of claim 1, wherein the inertial / Doppler-aided, damped state-based navigation method is based on a Kalman filter. The step three needs to evaluate the measurement accuracy of the Doppler log by analyzing the statistical characteristics of the data of the Doppler log, and specify the fault detection method; the detection method uses innovation chi-square detection; which is to use the measurement innovation δr k The method for detecting and isolating filter faults has good detection effect on large data anomalies; the measurement innovation reflects the consistency between the state estimation and the measurement value, and under ideal conditions, it is subject to normal distribution with a mean of 0; δr k ~ N(0,C k ) where H k is the observation matrix of the system, Z k is the observation matrix, is the state estimation matrix from k time to k-1 time, N(0, C k ) represents the normal distribution with mean 0 and variance C k , P k,k-1 is the transition matrix from k time to k-1 time, R k is the variance matrix of the measurement noise, T k obeys the chi-square distribution is the variable to be detected.

4. The method of claim 1, wherein, In step four, the speed integrated navigation algorithm takes the inertial system error equation as the state equation of the integrated navigation system, takes the difference between the inertial measurement speed and the log measurement speed as the observation quantity and establishes the observation equation, adopts the optimal estimation theory to perform real-time estimation and compensation on the state of the system, thereby suppressing the influence of inertial device error on navigation precision. Select the system latitude and longitude error Two variables in (δλ, δφ) are longitude error and latitude error respectively, horizontal velocity error (δv e , δv n ) in navigation system, i.e. n system, Two variables in (δv e , δv n ) are eastward velocity error and northward velocity error respectively, attitude error (φ e , φ n , φ u ) in navigation system, i.e. n system, Three variables in (φ e , φ n , φ u ) are roll error, pitch error and heading deviation respectively, horizontal accelerometer zero offset in carrier coordinate system and gyro zero offset in carrier coordinate system ε = [ε x ε y ε z ], as state variable, then the state variable is: The state equation of the integrated navigation system is: where • denotes differentiation with respect to the variable, R m denotes the radius of the earth's latitude circle, R n denotes the radius of the earth's longitude circle, f n denotes the projection of the accelerometer in the navigation frame, denotes the projection of the angular velocity of the navigation frame relative to the earth frame in the navigation frame, f denotes the projection of the angular velocity of the earth frame relative to the inertial frame in the navigation frame, f denotes the projection of the angular velocity of the navigation frame relative to the inertial frame in the navigation frame, v n denotes the projection of the navigation solution velocity in the navigation frame, φ n = [φ e φ n φ u denotes the projection of the attitude angle error in the navigation frame; The difference between the inertial measurement speed and the Doppler log measurement speed is the observation quantity, which is: wherein, and Vx and Vy represent the east and north projections of the velocity information calculated by the inertial navigation system, respectively, and Vx and Vy represent the east and north projections of the velocity information calculated by the inertial navigation system, respectively, According to the state equation and the observation quantity of the integrated navigation system, the integrated navigation system equation is established, and the optimal estimation is used to perform real-time estimation and compensation on the state error.

5. The method of claim 1, wherein, The step five is: according to the classical control theory, the parameter H (s) of the damping navigation network is optimally designed; wherein, the input of the damping network is the difference between the speed of system solution and the output speed of Doppler log, and the output is the speed after being corrected by the damping network; Generally, the design method of the second-order damping network is as follows: Wherein, ω1, ω2, ω3, ω4 are the parameters of the damping network; On this basis, firstly, the parameters are preliminarily designed through the gain characteristics and phase characteristics required by the design, and then the specific parameters of the damping network are further designed according to the peak value of the closed-loop gain of the second-order system corresponding to the damping coefficient required by the design; if the form of the damping network is transformed as follows: Wherein, ω1, ω2, A, B are the parameters of the damping network after form transformation; The classical control theory method of closed-loop dominant pole is used to design the damping network, so that the performance and effect of the original damping network itself can be analyzed by using the equivalent damping network; this damping network design method not only simplifies the design process of the damping network parameters, but also is more conducive to the analysis and research of the network performance.

6. The method of claim 1, wherein, The step seven is: the main features of the carrier speed are the synthesis of the swing period function and the impact motion function, the frequency band contains the swing period and higher frequency range, and the frequency band range of the main error source in the carrier speed includes the low-frequency characteristics such as the Schuler period, the earth period and the Foucault period; through the analysis of a large amount of real ship test data, the swing situation of the carrier under various sea conditions and the error propagation mechanism of the inertial measurement and the speed measurement of the log are determined, and the frequency spectrum analysis is carried out; on this basis, the high-pass filter setting research is carried out, the low-frequency error signal is filtered out by setting a reasonable high-pass filter, and the speed measurement precision under the ship movement state is improved.

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