Shipborne load abnormity measuring method, medium and equipment

Abstract

The invention relates to the technical field of shipborne heavy force measurement, in particular to a shipborne heavy force abnormity measurement method, a medium and equipment. The method comprises the following steps: performing combined navigation fusion on a shipborne inertial navigation system and a satellite navigation system through Kalman filtering to obtain corrected angular velocity and specific force; calculating a gravity anomaly measurement coarse value and a virtual vertical accelerometer specific force; enabling the gravity anomaly measurement coarse value, the virtual vertical accelerometer specific force and the actual vertical accelerometer specific force to respectively pass through an FIR low-pass filter to obtain a gravity anomaly measurement fine value, a virtual vertical accelerometer specific force filtering value and an actual vertical accelerometer specific force filtering value; and correcting the gravity anomaly measurement precise value to obtain a final gravity anomaly measurement result. According to the ship-borne gravity anomaly measurement method, gravity anomaly measurement errors generated by actual vertical accelerometer offset errors can be restrained, and the gravity anomaly measurement accuracy is improved; and meanwhile, the precision requirement on a gravity sensitive instrument such as an accelerometer is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of shipborne gravity measurement, and in particular to a shipborne gravity anomaly measurement method, medium and equipment. Background Art

[0002] Gravity anomaly information is a crucial component of geophysical field data and a core element of ocean gravity field environmental information. It has significant application value in marine resource development, geophysical research, and particularly in the development of naval battlefield environments, underwater autonomous navigation, and precision weapon strikes. Shipborne gravity anomaly measurements are a crucial means of obtaining high-precision, high-resolution, and large-scale ocean gravity field information.

[0003] Currently, dynamic gravity measurement is primarily based on inertial navigation systems. A horizontal attitude reference is established using gyroscopes and accelerometers (gravity sensors can be considered a specialized acceleration measurement element). Vertical gravity information is then obtained using vertical accelerometers. Therefore, high-precision vertical accelerometers are crucial components for gravity anomaly measurement. To improve their performance and accuracy, vertical accelerometers used in gravity anomaly measurement are carefully selected. Firstly, high-precision vertical accelerometers with minimal bias and random walk are typically chosen. Secondly, a temperature control module is specifically designed to compensate for temperature-induced accelerometer drift, achieving a temperature stability of 0.001°C. Ultimately, the accuracy of the vertical accelerometers is controlled to approximately 1 mGal. While these approaches improve the accuracy of the vertical accelerometers, and thus the accuracy of gravity measurements, they also significantly increase costs.

[0004] Therefore, in order to improve the accuracy of gravity anomaly measurement, it is necessary to propose a more accurate shipborne gravity anomaly measurement method, which can reduce the high-precision requirements of accelerometers and reduce the cost of gravity anomaly measurement to a certain extent. Summary of the Invention

[0005] The present invention aims to provide a method, medium and equipment for measuring shipborne gravity anomaly with high measurement accuracy. The specific technical solutions are as follows:

[0006] A shipborne gravity anomaly measurement method comprises the following steps:

[0007] Step 1: Use Kalman filtering to integrate the shipborne inertial navigation system and the satellite navigation system, collect the attitude, velocity and position information output by the integrated navigation, and obtain the corrected angular velocity and specific force;

[0008] Step 2: Calculate the rough value of gravity anomaly measurement and the virtual vertical accelerometer specific force based on the attitude, velocity and position information, as well as the corrected angular velocity and specific force;

[0009] Step 3: Passing the rough gravity anomaly measurement value, the virtual vertical accelerometer specific force, and the actual vertical accelerometer specific force through an FIR low-pass filter to obtain a precise gravity anomaly measurement value, a filtered value of the virtual vertical accelerometer specific force, and a filtered value of the actual vertical accelerometer specific force;

[0010] Step 4: Fuse the virtual vertical accelerometer specific force filter value and the actual vertical accelerometer specific force filter value to obtain the fused vertical accelerometer specific force. The fused vertical accelerometer specific force is used to correct the gravity anomaly measurement precision value to obtain the final gravity anomaly measurement result.

[0011] Preferably, in step 1, performing combined navigation fusion of the shipborne inertial navigation system and the satellite navigation system through Kalman filtering is specifically:

[0012] The Kalman filter state quantity X is:

[0013]

[0014] Where φ represents attitude error, δv represents velocity error, δp represents position error, and ε represents gyro bias. Indicates the accelerometer zero bias;

[0015] The measurement equation of Kalman filter is:

[0016] Z k =H k X k +V k ;

[0017] Where, subscript k represents the sampling time, Z k represents the measurement value at time k, H k represents the measurement transfer matrix at time k, X k Table V represents the Kalman filter state at time kk, V k represents the measurement noise at time k;

[0018] Z k Expressed as:

[0019]

[0020] Where, Indicates the speed information output by the inertial navigation system, Represents the position information output by the inertial navigation system, Indicates the speed information output by the satellite navigation system receiver. Represents the position information output by the satellite navigation system receiver;

[0021] H k Expressed as:

[0022]

[0023] Where, 0 3×3 represents the three-dimensional zero matrix, I 3×3 Represents the three-dimensional identity matrix;

[0024] The state equation of the Kalman filter is:

[0025] X k =AX k-1 +W k-1 ;

[0026] Where A represents the state one-step transfer matrix, which is obtained through the inertial navigation error propagation equation, X k Represents the Kalman filter state at time k-1, W k-1 represents process noise;

[0027] The Kalman filter equation is:

[0028] ①、 in represents the one-step prediction state, represents the state estimate at time k-1;

[0029] ②P k|k-1 =AP k-1 A T +Q k-1 , where P k|k-1 represents the one-step forecast error covariance matrix, P k-1 represents the estimation error covariance matrix at time k-1, represents the state noise variance matrix at time k-1;

[0030] ③、 where K k represents the Kalman filter gain at time k, represents the measurement noise variance matrix at time k;

[0031] ④、 in represents the state estimate at time k;

[0032] ⑤、P k =(IK k H k )P k|k-1 , where I represents the identity matrix, P k Represents the estimation error covariance matrix at time k.

[0033] Preferably, the step of obtaining the corrected angular velocity and specific force information in step 1 includes:

[0034] The attitude, velocity and position information output by the combined navigation after Kalman filtering are recorded as

[0035] The accelerometer zero bias estimated by the integrated navigation Kalman filter is used to correct the horizontal accelerometer. The corrected angular velocity and specific force are expressed as:

[0036]

[0037] Where, They represent the angular velocity, x-direction specific force and y-direction specific force actually output by the inertial navigation system, They represent the corrected angular velocity, x-direction specific force, and y-direction specific force, respectively. and They represent the accelerometer zero bias in the x-direction and y-direction estimated by the integrated navigation, respectively.

[0038] Preferably, the step of calculating the rough value of gravity anomaly measurement in step 2 includes:

[0039] The angular velocity, specific force, attitude, speed and position information output by the inertial navigation system are collected and recorded as f b 、 The superscript b indicates the projection under the carrier system, and the superscript n indicates the projection under the navigation system. The subscript ib indicates is the angular velocity of the carrier system relative to the inertial system. The subscript INS indicates the information output by the inertial navigation system. The velocity and position information output by the satellite navigation system receiver are recorded as and The subscript GNSS indicates the information output by the satellite navigation system;

[0040] The calculation formula for the rough value of gravity anomaly measurement is as follows:

[0041]

[0042] Where, δg c Indicates the rough value of gravity anomaly measurement, represents the celestial acceleration, f U represents the celestial force, γ represents the normal gravitational acceleration, ω ie represents the angular velocity of the Earth's rotation, v E 、v N Represent the eastward and northward speeds respectively; L is the latitude of the carrier location, R is the radius of the earth; f U pass Comparison of the calibrated accelerometer Projection obtained, By calculating the celestial velocity output by the integrated navigation system The difference is obtained, It is called the Ertfos correction, and γ is calculated based on the WGS84 model.

[0043] Preferably, the calculation formula of the virtual vertical accelerometer specific force in step 2 is:

[0044] f vz sinγ=Z1cosψ-Z2sinψ;

[0045] Where, f vz represents the virtual vertical accelerometer specific force, γ and ψ represent the roll angle and heading attitude angle respectively, and Z1 and Z2 are:

[0046]

[0047] Where θ represents the pitch attitude angle, and represents the corrected x-axis and y-axis accelerometer specific force, ΔT represents the integrated navigation Kalman filter period, Δv E and Δv N Denotes the velocity increment in the east and north directions, Δv E,cor / g and Δv N,cor / g Indicates harmful speed increments in the east and north directions;

[0048] Δv cor / g is a slowly varying term, which can be expressed as:

[0049]

[0050] Where, represents the projection of the Earth's rotational angular velocity in the navigation system, Represents the projection of position rate in the navigation system, g n represents the gravitational acceleration vector;

[0051] and Expressed as:

[0052]

[0053] Where h is the height of the carrier, R M and R N They are the meridian curvature radius and the meridinomial curvature radius of the earth respectively.

[0054] Preferably, the parameters of the FIR low-pass filter in step 3 are determined according to the carrier motion speed and the spatial resolution required for gravity anomaly measurement, and the cutoff frequency F of the FIR low-pass filter is c Designed to:

[0055]

[0056] In the formula, v represents the carrier movement speed, λ represents the spatial resolution;

[0057] The FIR low-pass filter is designed using the window function method. The sea and air gravity measurement uses the Hamming window or Hanning window function to design the FIR filter. The filter length N FIR Determined by the following formula:

[0058]

[0059] Where, F s Indicates the frequency of the integrated navigation Kalman filter;

[0060] The crude value of gravity anomaly measurement δg c , virtual vertical accelerometer relative force f vz and the actual vertical accelerometer specific force f z , are processed by the designed FIR low-pass filter to obtain the precise value of gravity anomaly measurement δg f , virtual vertical accelerometer specific force filter value f′ vz and the actual vertical accelerometer force filter value f′ z .

[0061] Preferably, the virtual vertical accelerometer specific force filter value f′ in step 4 vz and the actual vertical accelerometer force filter value f z The fusion method of ′ is as follows:

[0062]

[0063] Where f′ vz,DC Represents the DC component of the virtual vertical accelerometer specific force filter value, f′ z,AC Represents the AC component of the actual vertical accelerometer specific force filtered value, Represents the fused vertical accelerometer specific force.

[0064] Preferably, the gravity anomaly measurement precision correction expression is:

[0065]

[0066] Where, Indicates the accuracy of gravity anomaly measurement after correction.

[0067] The present invention also provides a readable storage medium having computer program instructions stored thereon, which implements the shipborne gravity anomaly measurement method as described above when the computer program instructions are executed by a processor.

[0068] The present invention also provides an electronic device comprising: at least one processor, at least one memory and computer program instructions stored in the memory, when the computer program instructions are executed by the processor, a shipborne gravity anomaly measurement method as described above is performed.

[0069] The application of the technical solution of the present invention has the following beneficial effects:

[0070] A shipborne gravity anomaly measurement method comprises the following steps: step 1: performing integrated navigation fusion on a shipborne inertial navigation system and a satellite navigation system through Kalman filtering, and collecting attitude, velocity and position information output by the integrated navigation to obtain calibrated angular velocity and specific force; step 2: calculating a coarse gravity anomaly measurement value and a virtual vertical accelerometer specific force based on the attitude, velocity and position information, as well as the calibrated angular velocity and specific force; step 3: passing the coarse gravity anomaly measurement value, the virtual vertical accelerometer specific force and the actual vertical accelerometer specific force through an FIR low-pass filter to obtain a precise gravity anomaly measurement value, a filtered virtual vertical accelerometer specific force value and a filtered actual vertical accelerometer specific force value; and step 4: fusing the filtered virtual vertical accelerometer specific force value and the filtered actual vertical accelerometer specific force value to obtain a fused vertical accelerometer specific force, wherein the fused vertical accelerometer specific force is used to calibrate the precise gravity anomaly measurement value to obtain a final gravity anomaly measurement result. The shipborne gravity anomaly measurement method proposed in the present invention can suppress the gravity anomaly measurement error caused by the actual vertical accelerometer bias error, improve the accuracy of gravity anomaly measurement, and reduce the accuracy requirements for gravity-sensitive instruments such as accelerometers.

[0071] In addition to the above-described objects, features and advantages, the present invention has other objects, features and advantages. The present invention will be further described in detail below with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] The accompanying drawings, which constitute part of this application, are intended to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are intended to explain the present invention and do not constitute an undue limitation of the present invention. In the accompanying drawings:

[0073] Figure 1 1 is a flow chart of a method for measuring shipborne gravity anomaly according to an embodiment of the present invention;

[0074] Figure 2 1 is a schematic diagram comparing the corrected gravity anomaly measurement precision value and the actual gravity anomaly in an embodiment of the present invention;

[0075] Figure 3 3 is a schematic diagram comparing the precision errors of gravity anomaly measurements before and after correction in an embodiment of the present invention. DETAILED DESCRIPTION

[0076] The embodiments of the present invention are described in detail below with reference to the accompanying drawings. However, the present invention can be implemented in many different ways as defined and covered by the claims.

[0077] Example:

[0078] See also Figure 1 A shipborne gravity anomaly measurement method comprises the following steps:

[0079] Step 1: Use Kalman filtering to integrate the shipborne inertial navigation system and the satellite navigation system, collect the attitude, velocity and position information output by the integrated navigation, and obtain the corrected angular velocity and specific force;

[0080] In the step 1, the Kalman filter state quantity X for combined navigation fusion of the shipborne inertial navigation system and the satellite navigation system through Kalman filtering is:

[0081]

[0082] Where φ represents attitude error, δv represents velocity error, δp represents position error, and ε represents gyro bias. Indicates the accelerometer zero bias;

[0083] The measurement equation of Kalman filter is:

[0084] Z k =H k X k +V k ;

[0085] Where, subscript k represents the sampling time, Z k represents the measurement value at time k, H k represents the measurement transfer matrix at time k, X k Table V represents the Kalman filter state at time kk, V k represents the measurement noise at time k;

[0086] Z k Expressed as:

[0087]

[0088] Where, Indicates the speed information output by the inertial navigation system, Represents the position information output by the inertial navigation system, Indicates the speed information output by the satellite navigation system receiver. Represents the position information output by the satellite navigation system receiver;

[0089] H k Expressed as:

[0090]

[0091] Where, 0 3×3 represents the three-dimensional zero matrix, I 3×3 Represents the three-dimensional identity matrix;

[0092] The state equation of the Kalman filter is:

[0093] X k =AX k-1 +W k-1 ;

[0094] Where A represents the state one-step transfer matrix, which is obtained through the inertial navigation error propagation equation, X k Represents the Kalman filter state at time k-1, W k-1 represents process noise;

[0095] The Kalman filter equation is:

[0096] ①、 in represents the one-step prediction state, represents the state estimate at time k-1;

[0097] ②P k|k-1 =AP k-1 A T +Q k-1 , where P k|k-1 represents the one-step forecast error covariance matrix, P k-1 represents the estimation error covariance matrix at time k-1, represents the state noise variance matrix at time k-1;

[0098] ③、 where K k represents the Kalman filter gain at time k, represents the measurement noise variance matrix at time k;

[0099] ④、 in represents the state estimate at time k;

[0100] ⑤、P k =(IK k H k )P k|k-1 , where I represents the identity matrix, P k Represents the estimation error covariance matrix at time k.

[0101] The steps of obtaining the corrected angular velocity and specific force information in step 1 include:

[0102] The attitude, velocity and position information output by the combined navigation after Kalman filtering are recorded as

[0103] The accelerometer zero bias estimated by the integrated navigation Kalman filter is used to correct the horizontal accelerometer. The corrected angular velocity and specific force are expressed as:

[0104]

[0105] Where, They represent the angular velocity, x-direction specific force and y-direction specific force actually output by the inertial navigation system, They represent the corrected angular velocity, x-direction specific force, and y-direction specific force, respectively. and They represent the accelerometer zero bias in the x-direction and y-direction estimated by the integrated navigation, respectively.

[0106] Step 2: Calculate the rough value of gravity anomaly measurement and the virtual vertical accelerometer specific force based on the attitude, velocity, and position information, as well as the corrected angular velocity and specific force. Specifically:

[0107] The angular velocity, specific force, attitude, speed and position information output by the inertial navigation system are collected and recorded as f b 、 The superscript b indicates the projection under the carrier system, and the superscript n indicates the projection under the navigation system. The subscript ib indicates is the angular velocity of the carrier system relative to the inertial system. The subscript INS indicates the information output by the inertial navigation system. The velocity and position information output by the satellite navigation system receiver are recorded as and The subscript GNSS indicates the information output by the satellite navigation system;

[0108] The calculation formula for the rough value of gravity anomaly measurement is as follows:

[0109]

[0110] Where, δg c Indicates the rough value of gravity anomaly measurement, represents the celestial acceleration, f U represents the celestial force, γ represents the normal gravitational acceleration, ω ie represents the angular velocity of the Earth's rotation, v E 、v N Represent the eastward and northward speeds respectively; L is the latitude of the carrier location, R is the radius of the earth; f U pass Comparison of the calibrated accelerometer Projection obtained, By calculating the celestial velocity output by the integrated navigation system The difference is obtained, It is called the Ertfos correction, and γ is calculated based on the WGS84 model.

[0111] The calculation formula of the virtual vertical accelerometer specific force is:

[0112] f vz sinγ=Z1cosψ-Z2sinψ;

[0113] Where, f vz represents the virtual vertical accelerometer specific force, γ and ψ represent the roll angle and heading attitude angle respectively, and Z1 and Z2 are:

[0114]

[0115] Where θ represents the pitch attitude angle, and represents the corrected x-axis and y-axis accelerometer specific force, ΔT represents the integrated navigation Kalman filter period, Δv E and Δv N Denotes the velocity increment in the east and north directions, Δv E,cor / g and Δv N,cor / g Indicates harmful speed increments in the east and north directions;

[0116] Δv cor / g is a slowly varying term, which can be expressed as:

[0117]

[0118] Where, represents the projection of the Earth's rotational angular velocity in the navigation system, Represents the projection of position rate in the navigation system, g n represents the gravitational acceleration vector;

[0119] and Expressed as:

[0120]

[0121] Where h is the height of the carrier, R M and R N They are the meridian curvature radius and the meridinomial curvature radius of the earth respectively.

[0122] Step 3: The gravity anomaly measurement rough value, the virtual vertical accelerometer specific force, and the actual vertical accelerometer specific force are respectively passed through an FIR low-pass filter to obtain the gravity anomaly measurement fine value, the virtual vertical accelerometer specific force filtered value, and the actual vertical accelerometer specific force filtered value, specifically:

[0123] The parameters of the FIR low-pass filter are determined by the carrier motion speed and the spatial resolution required for gravity anomaly measurement. The cutoff frequency F of the FIR low-pass filter is c Designed to:

[0124]

[0125] In the formula, v represents the carrier movement speed, λ represents the spatial resolution;

[0126] The FIR low-pass filter is designed using the window function method. The sea and air gravity measurement uses the Hamming window or Hanning window function to design the FIR filter. The filter length N FIR Determined by the following formula:

[0127]

[0128] Where, F s Indicates the frequency of the integrated navigation Kalman filter;

[0129] The crude value of gravity anomaly measurement δg c , virtual vertical accelerometer relative force f vz and the actual vertical accelerometer specific force f z , are processed by the designed FIR low-pass filter to obtain the precise value of gravity anomaly measurement δg f , virtual vertical accelerometer specific force filter value f′ vz and the actual vertical accelerometer force filter value f′ z .

[0130] Step 4: Fuse the virtual vertical accelerometer specific force filter value and the actual vertical accelerometer specific force filter value to obtain the fused vertical accelerometer specific force. The fused vertical accelerometer specific force is used to correct the gravity anomaly measurement precision value to obtain the final gravity anomaly measurement result. Specifically:

[0131] Virtual vertical accelerometer specific force filtered value f′ vz and the actual vertical accelerometer force filter value f′ z The fusion method is as follows:

[0132]

[0133] Where f′ vz,DC Represents the DC component of the virtual vertical accelerometer specific force filter value, f′ z,ACRepresents the AC component of the actual vertical accelerometer specific force filtered value, Represents the fused vertical accelerometer specific force.

[0134] The correction expression of gravity anomaly measurement precision is:

[0135]

[0136] Where, Indicates the accuracy of gravity anomaly measurement after correction.

[0137] This embodiment conducted a simulation test based on data from a certain navigation test. The simulation test lasted 30 minutes, and the simulation conditions were set as shown in the following table.

[0138] Table 1 Accuracy of simulation test equipment

[0139] Zero bias Random walk noise gyroscope 0.003° / h 0.0005° / √h accelerometer 50mGal 10mGal / √Hz Speed ​​measurement accuracy Positioning accuracy Satellite navigation system (0.03,0.03,1)m / s (3,3,10)m

[0140] In the simulation, the gravity anomaly is set to a sine function with an amplitude of 100 mGal and a period of 1 hour. The inertial navigation sampling frequency is 20 Hz, the FIR low-pass filter cutoff frequency is set to 0.01 Hz, and the filter length is set to 600. The gravity anomaly measurement method assisted by the virtual accelerometer provided in this embodiment is applied. The gravity anomaly measurement results are as follows: Figure 2 and 3 shown.

[0141] As can be seen, the gravity anomaly measurements after correction using the virtual accelerometer closely match the true values. Compared to the uncorrected gravity anomaly measurement accuracy, the method provided in this example effectively suppresses the bias error of the actual vertical accelerometer. The gravity anomaly measurement errors before and after correction are 50.5 mGal and 1.22 mGal, respectively, significantly improving the accuracy of gravity anomaly measurements.

[0142] This embodiment further includes a readable storage medium having computer program instructions stored thereon. When the computer program instructions are executed by a processor, the above-mentioned shipborne gravity anomaly measurement method is implemented.

[0143] Exemplarily, the computer program may be divided into one or more modules / units, which are stored in the memory and executed by the processor to implement the present invention. The one or more modules / units may be a series of computer program instruction segments capable of implementing specific functions, and the instruction segments are used to describe the execution process of the computer program in the electronic device.

[0144] This embodiment also includes an electronic device, including: at least one processor, at least one memory, and computer program instructions stored in the memory. When the computer program instructions are executed by the processor, a shipborne gravity anomaly measurement method as described above is performed.

[0145] The electronic device may be a computing device such as a mobile phone, desktop computer, laptop, PDA, or cloud server. The electronic device may include, but is not limited to, a processor and memory. For example, the electronic device may also include input / output devices, network access devices, buses, etc.

[0146] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention are intended to be within the scope of protection of the present invention.

Claims

1. A shipborne gravity anomaly measurement method, characterized in that: The steps include: Step 1: Use Kalman filtering to integrate the shipborne inertial navigation system and the satellite navigation system, collect the attitude, velocity and position information output by the integrated navigation, and obtain the corrected angular velocity and specific force; Step 2: Calculate the rough value of gravity anomaly measurement and the virtual vertical accelerometer specific force based on the attitude, velocity and position information, as well as the corrected angular velocity and specific force; Step 3: Passing the rough gravity anomaly measurement value, the virtual vertical accelerometer specific force, and the actual vertical accelerometer specific force through an FIR low-pass filter to obtain a precise gravity anomaly measurement value, a filtered value of the virtual vertical accelerometer specific force, and a filtered value of the actual vertical accelerometer specific force; Step 4: Fuse the virtual vertical accelerometer specific force filter value and the actual vertical accelerometer specific force filter value to obtain the fused vertical accelerometer specific force. The fused vertical accelerometer specific force is used to correct the gravity anomaly measurement precision value to obtain the final gravity anomaly measurement result.

2. A shipborne gravity anomaly measurement method according to claim 1, characterized in that: In step 1, the combined navigation fusion of the shipborne inertial navigation system and the satellite navigation system by using Kalman filtering is specifically as follows: The Kalman filter state quantity X is: X=[φ,δv,δp,ε,▽] T ; Where φ represents attitude error, δv represents velocity error, δp represents position error, ε represents gyro bias, and ▽ represents accelerometer bias. The measurement equation of Kalman filter is: Z k =H k X k +V k ; Where, subscript k represents the sampling time, Z k represents the measurement value at time k, H k represents the measurement transfer matrix at time k, X k Represents the Kalman filter state at time k, V k represents the measurement noise at time k; Z k Expressed as: Where, Indicates the speed information output by the inertial navigation system, Represents the position information output by the inertial navigation system, Indicates the speed information output by the satellite navigation system receiver. Represents the position information output by the satellite navigation system receiver; H k Expressed as: Where, 0 3×3 represents the three-dimensional zero matrix, I 3×3 Represents the three-dimensional identity matrix; The state equation of the Kalman filter is: X k =AX k-1 +W k-1 ; Where A represents the state one-step transfer matrix, which is obtained through the inertial navigation error propagation equation, X k Represents the Kalman filter state at time k-1, W k-1 represents process noise; The Kalman filter equation is: ①、 in represents the one-step prediction state, represents the state estimate at time k-1; ②P k|k-1 =AP k-1 A T +Q k-1 , where P k|k-1 represents the one-step forecast error covariance matrix, P k-1 represents the estimation error covariance matrix at time k-1, represents the state noise variance matrix at time k-1; ③、 where K k represents the Kalman filter gain at time k, represents the measurement noise variance matrix at time k; ④、 in represents the state estimate at time k; ⑤、P k =(IK k H k )P k|k-1 , where I represents the identity matrix, P k Represents the estimation error covariance matrix at time k.

3. A shipborne gravity anomaly measurement method according to claim 2, characterized in that: The steps of obtaining the corrected angular velocity and specific force information in step 1 include: The attitude, velocity and position information output by the combined navigation after Kalman filtering are recorded as The accelerometer zero bias estimated by the integrated navigation Kalman filter is used to correct the horizontal accelerometer. The corrected angular velocity and specific force are expressed as: Where, They represent the angular velocity, x-direction specific force and y-direction specific force actually output by the inertial navigation system, Represent the corrected angular velocity, x-direction specific force, and y-direction specific force, respectively, x and ▽ y They represent the accelerometer zero bias in the x-direction and y-direction estimated by the integrated navigation, respectively.

4. A shipborne gravity anomaly measurement method according to claim 3, characterized in that: The step of calculating the rough value of gravity anomaly measurement in step 2 includes: The angular velocity, specific force, attitude, speed and position information output by the inertial navigation system are collected and recorded as f b 、 The superscript b indicates the projection under the carrier system, and the superscript n indicates the projection under the navigation system. The subscript ib indicates is the angular velocity of the carrier system relative to the inertial system. The subscript INS indicates the information output by the inertial navigation system. The velocity and position information output by the satellite navigation system receiver are recorded as and The subscript GNSS indicates the information output by the satellite navigation system; The calculation formula for the rough value of gravity anomaly measurement is as follows: Where, δg c Indicates the rough value of gravity anomaly measurement, represents the celestial acceleration, f U represents the celestial force, γ represents the normal gravitational acceleration, ω ie represents the angular velocity of the Earth's rotation, v E 、v N Represent the eastward and northward speeds respectively; L is the latitude of the carrier location, R is the radius of the earth; f U pass Comparison of the calibrated accelerometer Projection obtained, By calculating the celestial velocity output by the integrated navigation system The difference is obtained, It is called the Ertfos correction, and γ is calculated based on the WGS84 model.

5. A shipborne gravity anomaly measurement method according to claim 4, characterized in that: The calculation formula of the virtual vertical accelerometer specific force in step 2 is: in vz sinγ=Z1cosψ-Z2sinψ; Where, f vz represents the virtual vertical accelerometer specific force, γ and ψ represent the roll angle and heading attitude angle respectively, and Z1 and Z2 are: Where θ represents the pitch attitude angle, and represents the corrected x-axis and y-axis accelerometer specific force, ΔT represents the integrated navigation Kalman filter period, Δv E and Δv N Denotes the velocity increment in the east and north directions, Δv E,cor / g and Δv N,cor / g Indicates harmful speed increments in the east and north directions; Δv cor / g is a slowly varying term, which can be expressed as: Where, represents the projection of the Earth's rotational angular velocity in the navigation system, Represents the projection of position rate in the navigation system, g n represents the gravitational acceleration vector; and Expressed as: Where h is the height of the carrier, R M and R N They are the meridian curvature radius and the meridinomial curvature radius of the earth respectively.

6. A shipborne gravity anomaly measurement method according to claim 5, characterized in that: The parameters of the FIR low-pass filter in step 3 are determined according to the carrier motion speed and the spatial resolution required for gravity anomaly measurement. The cutoff frequency F of the FIR low-pass filter is c Designed to: In the formula, v represents the carrier movement speed, λ represents the spatial resolution; The FIR low-pass filter is designed using the window function method. The sea and air gravity measurement uses the Hamming window or Hanning window function to design the FIR filter. The filter length N FIR Determined by the following formula: Where, F s Indicates the frequency of the integrated navigation Kalman filter; The crude value of gravity anomaly measurement δg c , virtual vertical accelerometer relative force f vz and the actual vertical accelerometer specific force f z , are processed by the designed FIR low-pass filter to obtain the precise value of gravity anomaly measurement δg f , virtual vertical accelerometer specific force filter value f′ vz and the actual vertical accelerometer force filter value f′ z .

7. A shipborne gravity anomaly measurement method according to claim 6, characterized in that: The virtual vertical accelerometer specific force filtered value f′ in step 4 vz and the actual vertical accelerometer force filter value f′ z The fusion method is as follows: Where f′ vz,DC Represents the DC component of the virtual vertical accelerometer specific force filter value, f′ z,AC Represents the AC component of the actual vertical accelerometer specific force filtered value, Represents the fused vertical accelerometer specific force.

8. A shipborne gravity anomaly measurement method according to claim 7, characterized in that: The correction expression of gravity anomaly measurement precision is: Where, Indicates the accuracy of gravity anomaly measurement after correction.

9. A readable storage medium, characterized in that Computer program instructions are stored thereon, and when the computer program instructions are executed by a processor, a shipborne gravity anomaly measurement method according to any one of claims 1 to 8 is implemented.

10. An electronic device, characterized in that: include: At least one processor, at least one memory, and computer program instructions stored in the memory, when the computer program instructions are executed by the processor, a shipborne gravity anomaly measurement method according to any one of claims 1 to 8.

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