CN117075166B - Ship satellite compass heading smoothing method - Google Patents
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/42—Determining position
- G01S19/43—Determining position using carrier phase measurements, e.g. kinematic positioning; using long or short baseline interferometry
- G01S19/44—Carrier phase ambiguity resolution; Floating ambiguity; LAMBDA [Least-squares AMBiguity Decorrelation Adjustment] method
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/42—Determining position
- G01S19/45—Determining position by combining measurements of signals from the satellite radio beacon positioning system with a supplementary measurement
- G01S19/47—Determining position by combining measurements of signals from the satellite radio beacon positioning system with a supplementary measurement the supplementary measurement being an inertial measurement, e.g. tightly coupled inertial
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Abstract
The invention provides a ship satellite compass heading smoothing method, which comprises the steps of installing two satellite navigation antennas on the axial direction of a ship, connecting the satellite navigation antennas with a satellite navigation receiver through a radio frequency cable, and outputting carrier phase observed quantity and ephemeris data to a processor in real time; the ship measurement longitudinal axis is provided with a gyroscope and an accelerometer, and real-time data of the gyroscope and the accelerometer are transmitted to the processor; the processor calculates satellite view vector by using ephemeris data, carries out differential processing on carrier phase observed quantity, and builds a standard baseline model after finishing whole-cycle ambiguity estimation; the processor builds a recursive baseline model by performing decorrelation processing and QR decomposition on the observed noise; constructing a prediction baseline model and a combined recursion baseline model by using gyroscope and accelerometer data; and solving a baseline vector, extracting a north component and an east component, and calculating a heading. The invention can improve the saw tooth phenomenon of the heading of the satellite compass, realize smooth output of angles, has small calculated amount and can be realized on a low-cost processor.
Description
Technical Field
The invention belongs to the technical field of satellite navigation and positioning, and particularly relates to a marine satellite compass heading smoothing method.
Background
In recent years, satellite compass is becoming an important navigation device for measuring the projection direction of the longitudinal axis of a ship in the horizontal plane. The satellite compass adopts the radio signal of the global navigation satellite system to calculate the ship heading, and has the remarkable advantages that: compared with a magnetic compass, the satellite compass has high precision and is not influenced by surrounding magnetic objects; compared with an electric compass, the satellite compass has no accumulated error and does not need manual calibration and maintenance. The above advantages of marine satellite compass make the satellite compass increasingly prominent in marine navigation.
The satellite compass is installed on the axis of the ship measurement longitudinal axis by adopting a double antenna, the satellite navigation receiver connected with the double antenna accurately estimates a baseline vector determined by the double antenna by utilizing a high-precision carrier phase measurement technology and a differential technology, and then the baseline vector is converted into a course angle and a pitch angle under geographic coordinates, wherein the course angle is the projection of the baseline in a horizontal plane and the true north included angle of the geographic meridian, and because the baseline vector determined by the double antenna is located on the axis of the ship measurement longitudinal axis, namely, the course angle is equal to the ship heading.
At present, satellite compass is mainly used for providing high-precision heading data for automatic steering instruments, radars, chart instruments and AIS (B) type ship automatic identification systems, and has two problems: (1) The original output rate of the satellite navigation receiver is low, so that the output rate of the satellite compass is low, and a significant time interval exists between two heading measurements; (2) The satellite compass is continuously measured for many times to obtain the ship heading, the measurement result of the satellite compass is in zigzag fluctuation along with time, and the heading curve is not smooth enough, so that the efficiency of equipment such as an automatic steering instrument is not improved.
Disclosure of Invention
In view of the above, the present invention aims to overcome the above-mentioned drawbacks of the prior art, and provides a method for smoothing the heading of a satellite compass for a ship.
In order to achieve the above purpose, the technical scheme of the invention is realized as follows:
a marine satellite compass heading smoothing method comprises the following steps:
step 1: two satellite navigation antennas are arranged on the axial direction of the ship measurement longitudinal axis, the distance between the two satellite navigation antennas is calibrated, and the distance is recorded as a base line lengthThe method comprises the steps of carrying out a first treatment on the surface of the A gyroscope and an accelerometer are arranged on the axis direction of the ship measurement longitudinal axis, the gyroscope is used for measuring the rotation angle variation of the ship, the accelerometer is used for measuring the pitch angle of the ship, and the gyroscopeAnd the accelerometer transmitting real-time data to the processor;
step 2: installing two satellite navigation receivers in a marine satellite compass circuit system and respectively connecting the two satellite navigation receivers with the two satellite navigation antennas in the step (1) through radio frequency cables; the two satellite navigation receivers respectively output carrier phase observed quantity and satellite ephemeris data to the processor in real time; calibrating carrier phase measurement precision of two satellite navigation receivers;
step 3: a processor to first calculate satellite view vectors using ephemeris data; then, carrying out twice difference on the carrier phase observed quantity of the two satellite navigation receivers to obtain a double-difference carrier phase observed vector;
step 4: the processor takes the double-difference carrier phase observation vector, the satellite view vector, the base line length and the carrier phase measurement precision as input quantities, and completes the whole-cycle ambiguity estimation of the double-difference carrier phase observation vector through a CLAMBDA algorithm to obtain a defuzzified double-difference carrier phase observation vector;
step 5: constructing a standard baseline model by using the defuzzified double-difference carrier phase observation vector, the satellite view vector and the carrier phase measurement precision，
Wherein, the subscript k indicates that all observation vectors and matrixes belong to the kth moment; y represents a defuzzified double-difference carrier phase observation vector; b is a coefficient matrix of the baseline vector B, and is constructed by satellite view vectors; v is the observed noise vector of y, obeys gaussian distribution,；is thatIs determined by the carrier phase measurement accuracy and the covariance matrix;
step 6: decorrelating observed noise of a standard baseline model, and performing decorrelationQR decomposition is carried out on the processed equation to obtain a recursive baseline modelWherein, the method comprises the steps of, wherein,is the recursive observation vector at time k,is a recursive coefficient matrix of the baseline vector at time k,equivalent observation noise of the k-moment recursive baseline model;
step 7: if the current time is the initial time, k=0, calculating a least square estimation solution of the baseline vector at the initial timeWherein, the method comprises the steps of, wherein,is an estimate of the baseline vector at the initial time,is a recursive coefficient matrix of the baseline vector at the initial time,is a recursive observation vector at the initial time, and the east component is extractedAnd north componentCalculating course angleAnd measuring pitch angle by accelerometerThen performing step (3); otherwise, go to step (8);
step 8: heading angle using last time k-1The gyroscopes measure the change of yaw angle at the previous moment and the current momentAnd pitch angle measured by accelerometer at current momentCalculating a base line vector predicted at the current time；
Step 9: by usingRegarded asWhereinIs an estimate of the baseline vector at time k-1,a baseline vector at time k-1; using the baseline vector predicted at the current time as described in step (8)Construction of new observationsThe construction method comprises the following steps ofWhereinIs the recursive observation vector at time k-1,is a recursive coefficient matrix of the baseline vector at time k-1,obtaining a predicted baseline modelWherein, the method comprises the steps of, wherein,to predict the equivalent observation vector of the baseline model,is the baseline vector at time k,equivalent observed noise for the predicted baseline model;
step 10: multiplying the predicted baseline model obtained in step (9) by a scale factorMaking the noise item obey normal distribution to obtain an additional baseline model；
Step 11: constructing based on the additional baseline model and the recursive baseline model，，Obtaining a combined standard baseline model；
Step 12: QR decomposition is carried out on the combined standard baseline model to obtain a combined recursive baseline model consistent with the matrix structure of the recursive baseline model；
Step 13: calculating least square estimation solution of current moment baseline vectorExtracting east component thereofAnd north componentCalculating course angle；
Step 14: updating the recursive baseline model by using the combined recursive baseline model, respectively realizing assignment operation on the observation vector and the coefficient matrix,，；
step 15: repeating the steps (3) to (14).
Further, in the step 6, the decorrelation process is performed on the observed noise of the standard baseline model and the QR decomposition is performed on the equation after the decorrelation process, and the specific steps are as follows:
step 6.1: for covariance matrixBy using a Cholesky decomposition method, the method comprises the steps of,
（a）
wherein the method comprises the steps ofIs a lower triangular matrix;
step 6.2: construction matrixMultiplying the construction matrix by both sides of the standard baseline model to obtain
（b）
Wherein,at this time, noise is observedIs subject to a standard normal distribution of the distribution,is a unit array;
step 6.3: for a pair ofPerforming QR decomposition to obtain
（c）
Wherein the method comprises the steps ofIs an orthogonal square matrix with dimension equal toThe number of rows of the matrix,the dimension of the upper triangular array is 3;
step 6.4: order theThe square matrix is regarded asAndtwo parts, whereinFor the first 3 rows, the rest is；
（d）
Step 6.5: allowing formula (d) to act on both sides of formula (b)
（e）
Order-making，Then
（f）
Since equation (c) is an orthogonal transform, it does not change the statistical properties of the observed noise, soThe standard normal distribution is maintained.
Further, the scale factorBased on the scene determination, for marine applications,the value interval is 0.85-0.89.
Compared with the prior art, the marine satellite compass heading smoothing method has the following advantages:
according to the invention, the ship heading change in the time interval of twice heading measurement is measured by using the gyroscope, and the change quantity is fused into heading estimation of the next epoch, so that the tight coupling of gyroscope data, accelerometer data and satellite navigation data is realized;
the algorithm of the invention can be recursively realized;
the algorithm of the invention has small calculated amount and low complexity, and is suitable for low-cost processors such as single chip computers and the like.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the invention. In the drawings:
FIG. 1 is a schematic diagram of a device used in a marine satellite compass heading smoothing method;
FIG. 2 is a flow chart of a marine satellite compass heading smoothing method provided by the invention;
FIG. 3 is a diagram of a saw tooth heading output of a satellite compass without smoothing;
fig. 4 is a schematic diagram of smoothing effect by the smoothing method of the present invention.
Detailed Description
It should be noted that, without conflict, the embodiments of the present invention and features of the embodiments may be combined with each other.
In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, are merely for convenience in describing the present invention and simplifying the description, and do not indicate or imply that the devices or elements referred to must have a specific orientation, be configured and operated in a specific orientation, and thus should not be construed as limiting the present invention. Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first", "a second", etc. may explicitly or implicitly include one or more such feature. In the description of the present invention, unless otherwise indicated, the meaning of "a plurality" is two or more.
In the description of the present invention, it should be noted that, unless explicitly specified and limited otherwise, the terms "mounted," "connected," and "connected" are to be construed broadly, and may be either fixedly connected, detachably connected, or integrally connected, for example; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium, and can be communication between two elements. The specific meaning of the above terms in the present invention can be understood by those of ordinary skill in the art in a specific case.
The invention will be described in detail below with reference to the drawings in connection with embodiments.
As shown in fig. 1-2, the invention provides a marine satellite compass heading smoothing method, which comprises the following steps:
step 1: two satellite navigation antennas are arranged on the axial direction of the ship measurement longitudinal axis, the distance between the two satellite navigation antennas is calibrated, and the distance is recorded as a base line lengthThe method comprises the steps of carrying out a first treatment on the surface of the A gyroscope and an accelerometer are arranged in the axial direction of a ship measurement longitudinal axis, the gyroscope is used for measuring the rotation angle variation of the ship, the accelerometer is used for measuring the pitch angle of the ship, and the gyroscope and the accelerometer transmit real-time data to a processor;
step 2: installing two satellite navigation receivers in a marine satellite compass circuit system and respectively connecting the two satellite navigation receivers with the two satellite navigation antennas in the step (1) through radio frequency cables; the two satellite navigation receivers respectively output carrier phase observed quantity and satellite ephemeris data to the processor in real time; calibrating carrier phase measurement precision of two satellite navigation receivers;
step 3: a processor to first calculate satellite view vectors using ephemeris data; then, carrying out twice difference on the carrier phase observed quantity of the two satellite navigation receivers to obtain a double-difference carrier phase observed vector;
step 4: the processor takes the double-difference carrier phase observation vector, the satellite view vector, the base line length and the carrier phase measurement precision as input quantities, and completes the whole-cycle ambiguity estimation of the double-difference carrier phase observation vector through a CLAMBDA algorithm to obtain a defuzzified double-difference carrier phase observation vector;
step 5: constructing a standard baseline model by using the defuzzified double-difference carrier phase observation vector, the satellite view vector and the carrier phase measurement precision，
Wherein, the subscript k indicates that all observation vectors and matrixes belong to the kth moment; y represents a defuzzified double-difference carrier phase observation vector; b is a coefficient matrix of the baseline vector B, and is constructed by satellite view vectors; v is the observed noise vector of y, obeys gaussian distribution,；is thatIs determined by the carrier phase measurement accuracy and the covariance matrix;
step 6: decorrelation processing is carried out on the observation noise of the standard baseline model, QR decomposition is carried out on the equation after the decorrelation processing, and a recursive baseline model is obtainedWherein, the method comprises the steps of, wherein,is the recursive observation vector at time k,is a recursive coefficient matrix of the baseline vector at time k,equivalent observation noise of the k-moment recursive baseline model;
specifically, step 6.1: for the covariance matrix of step (5)By Cholesky decomposition, i.e.
（b.1）
Wherein the method comprises the steps ofIn the form of a lower triangular matrix,
step 6.2: construction matrixMultiplying the two sides of formula (a) by the construction matrix at the same time to obtain
（b.2）
Wherein the method comprises the steps ofAt this time, noise is observedIs subject to a standard normal distribution of the distribution,is a unit array.
Step 6.3: for a pair ofQR decomposition is performed to obtain
（b.3）
Wherein the method comprises the steps ofIs an orthogonal square matrix with dimension equal toThe number of rows of the matrix,is an upper triangular array with a dimension of 3.
Step 6.4: order theThe square matrix is regarded asAndtwo parts, whereinFor the first 3 rows, the rest is；
（b.4）
Step 6.5: allowing formula (b.4) to act on both sides of formula (b.2)
（b.5）
I.e.Order-making，I.e.
（b.6）
Since equation (b.3) is an orthogonal transform, it does not change the statistical properties of the observed noise, soThe standard normal distribution is maintained.
Step 7: if the current time is the initial time, k=0, calculating a least square estimation solution of the baseline vector at the initial timeWherein, the method comprises the steps of, wherein,is an estimate of the baseline vector at the initial time,is a recursive coefficient matrix of the baseline vector at the initial time,is a recursive observation vector at the initial time, and the east component is extractedAnd north componentCalculating course angleAnd measuring pitch angle by accelerometerThen performing step (3); otherwise, go to step (8);
step 8: heading angle using last time k-1The gyroscopes measure the change of yaw angle at the previous moment and the current momentAnd pitch angle measured by accelerometer at current momentCalculating a base line vector predicted at the current time；
Step 9: by usingRegarded asWhereinIs an estimate of the baseline vector at time k-1,a baseline vector at time k-1; using the baseline vector predicted at the current time as described in step (8)Construction of new observationsThe construction method comprises the following steps ofWhereinIs the recursive observation vector at time k-1,is the recursive coefficient matrix of the baseline vector at the moment k-1 to obtain a predicted baseline modelWherein, the method comprises the steps of, wherein,to predict the equivalent observation vector of the baseline model,is the baseline vector at time k,equivalent observed noise for the predicted baseline model;
step 10: multiplying the predicted baseline model obtained in step (9) by a scale factorMaking the noise item obey normal distribution to obtain an additional baseline model；
In particular, the scale factorBased on the scene determination, for marine applications,the value interval is 0.85-0.89, fine adjustment is specifically carried out by combining the size of the ship, and the smaller the ship body is, the lower the value is.
Step 11: constructing based on the additional baseline model and the recursive baseline model，，Obtaining a combined standard baseline model；
Step 12: QR decomposition is carried out on the combined standard baseline model to obtain a combined recursive baseline model consistent with the matrix structure of the recursive baseline model；
Step 13: calculating least square estimation solution of current moment baseline vectorExtracting east component thereofAnd north componentCalculating course angle；
Step 14: updating the recursive baseline model by using the combined recursive baseline model, respectively realizing assignment operation on the observation vector and the coefficient matrix,，；
step 15: repeating the steps (3) to (14).
Fig. 3 is a heading result of a static baseline obtained by directly using the standard baseline model described in the step (5) without adopting any smoothing algorithm, and it can be seen that the output value presents a saw tooth shape with time, and fig. 4 is a diagram of a heading smoothing effect of the satellite compass in a real ship running process obtained by adopting the steps described in the invention. By comparing the method, the saw tooth phenomenon of the compass heading of the satellite can be improved, and the smooth output of angles can be realized.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, alternatives, and improvements that fall within the spirit and scope of the invention.
Claims (3)
1. A marine satellite compass heading smoothing method is characterized in that: the method comprises the following steps:
step 1: two satellite navigation antennas are arranged on the axial direction of the ship measurement longitudinal axis, the distance between the two satellite navigation antennas is calibrated, and the distance is recorded as a base line lengthThe method comprises the steps of carrying out a first treatment on the surface of the A gyroscope and an accelerometer are arranged in the axial direction of a ship measurement longitudinal axis, the gyroscope is used for measuring the rotation angle variation of the ship, the accelerometer is used for measuring the pitch angle of the ship, and the gyroscope and the accelerometer transmit real-time data to a processor;
step 2: installing two satellite navigation receivers in a marine satellite compass circuit system and respectively connecting the two satellite navigation receivers with the two satellite navigation antennas in the step (1) through radio frequency cables; the two satellite navigation receivers respectively output carrier phase observed quantity and satellite ephemeris data to the processor in real time; calibrating carrier phase measurement precision of two satellite navigation receivers;
step 3: a processor to first calculate satellite view vectors using ephemeris data; then, carrying out twice difference on the carrier phase observed quantity of the two satellite navigation receivers to obtain a double-difference carrier phase observed vector;
step 4: the processor takes the double-difference carrier phase observation vector, the satellite view vector, the base line length and the carrier phase measurement precision as input quantities, and completes the whole-cycle ambiguity estimation of the double-difference carrier phase observation vector through a CLAMBDA algorithm to obtain a defuzzified double-difference carrier phase observation vector;
step 5: constructing a standard baseline model by using the defuzzified double-difference carrier phase observation vector, the satellite view vector and the carrier phase measurement precision，
Wherein, the subscript k indicates that all observation vectors and matrixes belong to the kth moment; y represents a defuzzified double-difference carrier phase observation vector; b is a coefficient matrix of the baseline vector B, and is constructed by satellite view vectors; v is the observed noise vector of y, obeys gaussian distribution,；/>is->Is determined by the carrier phase measurement accuracy and the covariance matrix;
step 6: decorrelation processing is carried out on the observation noise of the standard baseline model, QR decomposition is carried out on the equation after the decorrelation processing, and a recursive baseline model is obtainedWherein->Is the recursive observation vector at time k, +.>Is a recursive coefficient matrix of the baseline vector at time k, < >>Equivalent observation noise of the k-moment recursive baseline model;
step 7: if the current time is the initial time, k=0, calculating a least square estimation solution of the baseline vector at the initial timeWherein->Is an estimate of the baseline vector at the initial moment, < >>Is a recursive coefficient matrix of the baseline vector at the initial moment,/->Is a recursive observation vector at the initial time, and extracts the east component +.>North component->Calculating course angleAnd measuring the pitch angle by means of an accelerometer>Then performing step (3); otherwise, go to step (8);
step 8: heading angle using last time k-1The change in yaw angle is measured by the gyroscopes at the previous and current moment k>And the pitch angle measured by the accelerometer at the current moment +.>Calculating a base line vector predicted at the current time；
Step 9: by usingTreated as->Wherein->Estimated value of baseline vector at time k-1, < >>A baseline vector at time k-1; baseline vector predicted by the current time as described in step (8)>Construction of a New observer->The construction method comprises the following steps ofWherein->Is the recursive observation vector at time k-1, < >>Is the recursive coefficient matrix of the baseline vector at time k-1 to obtain the predicted baseline model +.>Wherein->Equivalent observation vector for predicting baseline model, +.>For the baseline vector at time k +.>Equivalent observed noise for the predicted baseline model;
step 10: multiplying the predicted baseline model obtained in step (9) by a scale factorMaking the noise term follow normal distribution, obtaining additional baseline model +.>；
Step 11: constructing based on the additional baseline model and the recursive baseline model，/>，Obtaining a combined standard baseline model->；
Step 12: QR decomposition is carried out on the combined standard baseline model to obtain a combined recursive baseline model consistent with the matrix structure of the recursive baseline model；
Step 13: calculating least square estimation solution of current moment baseline vectorExtracting east component ∈>North component->Calculating course angle->；
Step 14: updating the recursive baseline model by using the combined recursive baseline model, respectively realizing assignment operation on the observation vector and the coefficient matrix,，/>；
step 15: repeating the steps (3) to (14).
2. The marine satellite compass heading smoothing method as defined in claim 1, wherein: in the step 6, the decorrelation processing is performed on the observed noise of the standard baseline model, and the QR decomposition is performed on the equation after the decorrelation processing, and the specific steps are as follows:
step 6.1: for covariance matrixBy using a Cholesky decomposition method, the method comprises the steps of,
（a）
wherein the method comprises the steps ofIs a lower triangular matrix;
step 6.2: construction matrixMultiplying the construction matrix by both sides of the standard baseline model to obtain
（b）
Wherein,at this time, noise ∈>Obeys a standard normal distribution, is->Is a unit array;
step 6.3: for a pair ofPerforming QR decomposition to obtain
（c）
Wherein the method comprises the steps ofIs an orthogonal square matrix with dimension equal to +.>Row number of matrix->The dimension of the upper triangular array is 3;
step 6.4: order theSquare matrix is regarded as->And->Two parts, wherein->For the first 3 rows, the rest is +.>；
（d）
Step 6.5: allowing formula (d) to act on both sides of formula (b)
（e）
Let->，/>Then
（f）
Since equation (c) is an orthogonal transform, it does not change the statistical properties of the observed noise, soThe standard normal distribution is maintained.
3. The marine satellite compass heading smoothing method as defined in claim 1, wherein: the scale factorBased on the scene determination, for marine applications, +.>The value interval is 0.85-0.89.
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