KR101960164B1 - A method for calculating a Real-Time Heading value of object using EKF-Cl - Google Patents

Abstract

The present invention relates to a method for calculating a real-time azimuth angle of an object using an extended Kalman filter, and more particularly, to a method for calculating azimuth angle of an object using GPS, an EC module and a single IMU module, By calculating the final convergence azimuth angle (psi_CI) using an extended Kalman filter (EKF) with a covariance intersection (CI) based on the accelerometer value, it is possible to calculate the azimuth angle of the object using an extended Kalman And a method for calculating a real-time azimuth angle of an object using a filter (EKF-Cl).
It is also possible to evaluate the validity of the GPS data separately based on the horizontal position error (HDOP) and the correction quality (FIX) value, so that even if the GPS data acquired from the plurality of GPSs is invalid or missing, And a method for calculating an azimuth angle of an object using an accelerometer value.

Description

[0001] The present invention relates to a method for calculating a real-time azimuth angle of an object using an extended Kalman filter,

The present invention relates to a method of calculating a real-time azimuth angle of an object using an extended Kalman filter, and more particularly, to a method of calculating an azimuth angle of an object based on azimuth and accelerometer values for GPS and EC calculated using a plurality of GPSs, Real-time azimuth calculation method of an object (precision farming machine) using an extended Kalman filter with a covariance intersection that can accurately calculate the azimuth angle of an object with a low-cost sensor by calculating the final convergence azimuth using an extended Kalman filter with a covariance intersection .

An apparatus and method for measuring the position of an individual using GPS or an inertial sensor have been invented and are continuously under development so that continuous position information can be provided even in a case where reception of a GPS (Global Positioning System) such as indoor and urban areas is poor. In addition, inertial navigation and position measurement techniques have been invented that can be used for an autopilot to navigate ships, automobiles, aircraft, etc. to predetermined routes and altitudes or routes.

An automatic navigation device to a ship compares the target azimuth indicated by the GPS or external input with the compass direction to determine the steering angle (that is, the angle that indicates the direction of the route when the ship attempts to navigate to a certain target point) ) To be automatically operated in the target direction, and is applied to small vessels as well as large-sized vessels.

Especially, in aeronautical field, the control board for UAVs calculates the angular velocity and acceleration information of navigation related signals, GPS signals and inertial sensors according to GPS / INS integrated navigation procedure, System has been applied and used.

However, there is not proposed a system and method that can accurately calculate the moving and azimuth values of an object such as an agricultural machine by a sensor fusion technique even with a low-cost sensor.

In addition, there is no technique to separately evaluate the validity of GPS data in case the positioning data using the satellite is invalid or missing.

Accordingly, there is an urgent need for a technology that can more accurately calculate an azimuth angle of an object in real time through sensor fusion of a plurality of low-cost sensor data. In addition, reliability of satellite information can be evaluated by using Horizontal Dilution of Precision (HDOP) and fix quality of GPS data (FIX), and can be replaced with other sensor data if the data is inaccurate The system is essential.

Korean Registered Patent No. 10-0414439 (Registered Date: December 2, 2003)

SUMMARY OF THE INVENTION The present invention has been made in view of the above problems, and it is an object of the present invention to provide a GPS and an EC (Electronic Compass) calculated using three GPSs, a single EC, and a single IMU (Psi_CI) is calculated using an extended Kalman filter (EKF) based on azimuth and accelerometer values (CI, Covariance Intersection) to obtain an object (precision agricultural machine, etc.) Which can accurately calculate an azimuth angle of an object by using an extended Kalman filter.

It is another object of the present invention to provide a method and system for evaluating the validity of GPS data on the basis of horizontal position error (HDOP) and fix quality of GPS data (FIX) The present invention provides a method of calculating an azimuth angle of an object using an azimuth angle with respect to an EC and an accelerometer value of an IMU.

In order to achieve the above objects, a method for calculating a real-time azimuth angle of an object using an extended Kalman filter (EKF-Cl) using a covariance intersection according to the present invention has a total of six recursive structures. We calculate azimuth, validity, weight, and covariance matrices for GPS, EC, and IMU modules detected in real time and perform real - time sensor fusion.

In order to calculate a precise azimuth angle, the present invention uses a plurality of GSP receivers, a single EC module and an IMU module. The first reason is to increase accuracy of azimuth calculation by including inertia and geomagnetism data in the GPS reception information, and to cope with a situation in which the GPS receiver fails or outputs unusable data.

GPS receivers and EC modules that output precise position data and azimuth are expensive equipment. However, in the present invention, the low-cost sensors can be fused by using the EKF-CI technique and the data of the accuracy similar to that of the expensive equipments can be outputted.

Therefore, an extended Kalman filter (EKF-CI) with a covariance intersection was used as a method for calculating more accurate azimuth using GPS, EC, and IMU module data. Parameters used to derive the final convergence azimuth are the forward azimuth for each data of the GPS receiver and the EC module, the weight based on the validity evaluation, and the azimuth for the GPS and EC modules, which are their convergence data, The values of the X-Axis accelerometer and the X-Axis accelerometer (IMU (Acc _x , Acc _y )), and the covariance matrix.

In addition, effectiveness indicators are separately defined to verify that the GPS reception data is missing or unavailable individually. Horizontal position error (HDOP) and correction quality (FIX) values are mainly used as indicators of validity.

In this case, the individual HDOPs are ideal (ideal) when the value is less than 1, excellent to a reliable level when the value is 1 to 2, and a reliable minimum level when the value is 2 to 5 (Good), 5 to 10 can be used for the calculation of position, Moderate to have high quality of correction, Fair to low confidence if 10 to 20, Incorrect to 20 or more (Poor), which is an unusable value.

FIX is a value that can not be used when the value is 0, GPS fix at 1, DGPS fix at 2, PPS fix at 3, Real Time Kinematics at 4, and Float RTK at 5 .

In the present invention, when combining the horizontal position error (HDOP) and the correction quality (FIX) value, it is determined that the HDOP is 1 to 2 and the FIX is 2 to 5, When HDOP is 1 to 2 and FIX is 1, when HDOP is 3 to 5 and FIX is 2 to 5, it is judged to be very excellent, and when HDOP is 3 to 5 and FIX is 1 , It is determined that the HDOP is 6 to 10 and the FIX is 2 to 5, and it is judged that all of the HDOPs are bad and are excluded.

 In the present invention, the two indicators are used together to determine the validity of the GPS data, and a weight is given to the useful GSP data.

If the GPS reception data is missing or unusable, the EC module receives the azimuth calculation and weight instead of the GPS receiver.

According to the method of calculating the real-time azimuth angle of an object using the extended Kalman filter according to the present invention, the azimuth angle and the accelerometer value for GPS and EC calculated using three GPSs, a single EC, and a single IMU, (Psi_CI) using the applied extended Kalman filter (EKF-CI), it is possible to accurately calculate the azimuth angle of the object by the EKF-CI sensor fusion technique even with a low-cost sensor.

In addition, the effectiveness of the GPS data based on the HDOP and FIX values can be evaluated separately, and the advantage of applying the azimuthal angle to the EC and the accelerometer value of the IMU, even when GPS data obtained from multiple GPSs is invalid or missing have.

FIG. 1 is a block diagram showing a schematic configuration of an azimuth calculation system of an object using an extended Kalman filter (EKF-CI) to which a covariance intersection point according to an embodiment of the present invention is applied.
FIG. 2 is a flowchart illustrating a method of calculating a real-time azimuth angle of an object using an extended Kalman filter (EKF-CI) to which a covariance intersection point according to an embodiment of the present invention is applied.
FIG. 3 is a flowchart for deriving a final fusion azimuth angle of an object using an extended Kalman filter (EKF-CI) to which a covariance intersection point according to an embodiment of the present invention is applied.

The present invention may be embodied in many other forms without departing from its spirit or essential characteristics. Accordingly, the embodiments of the present invention are to be considered in all respects as merely illustrative and not restrictive.

The terms first, second, etc. may be used to describe various components, but the components should not be limited by the terms.

The terms are used only for the purpose of distinguishing one component from another. For example, without departing from the scope of the present invention, the first component may be referred to as a second component, and similarly, the second component may also be referred to as a first component.

It is to be understood that when an element is referred to as being "connected" or "connected" to another element, it may be directly connected or connected to the other element, .

On the other hand, when an element is referred to as being "directly connected" or "directly connected" to another element, it should be understood that there are no other elements in between.

The terminology used in this application is used only to describe a specific embodiment and is not intended to limit the invention. The singular expressions include plural expressions unless the context clearly dictates otherwise.

In the present application, the terms "comprises", "having", "having", and the like are intended to specify the presence of stated features, integers, steps, operations, components, Steps, operations, elements, components, or combinations of elements, numbers, steps, operations, components, parts, or combinations thereof.

Unless defined otherwise, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

Terms such as those defined in commonly used dictionaries are to be interpreted as having a meaning consistent with the contextual meaning of the related art and are to be interpreted as either ideal or overly formal in the sense of the present application Do not.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings, in order that the present invention may be easily understood by those skilled in the art. .

FIG. 1 is a block diagram showing a schematic configuration of an azimuth calculation device for an object using an EKF-CI according to an embodiment of the present invention.

1, an azimuth calculation device 110 for an object using an EKF-Cl according to an embodiment of the present invention includes a power unit 10, a GPS module 20, an EC module 30, an IMU module A control unit 50, a first communication unit 60, a second communication unit 70, a third communication unit 80, a fourth communication unit 90, and a data storage unit 100.

The power supply unit 10 receives a power source such as 24 V or 5 V and supplies the entire power source required by the azimuth angle calculation apparatus 100 using the extended Kalman filter (EKF-Cl) according to the present embodiment. At this time, the power supply unit 10 may supply a voltage level (for example, 12V, 5V, 3.3V, etc.) according to a component supplying power.

The GPS module 20 includes three GPSs 20-1, 20-2, and 20-3, and transmits GPS reception information to the controller 50. [

Here, although the illustrated example shows the GPS module 20 composed of three GPSs in total, four or more GPSs are possible, and the number of the GPS modules is not limited in the present invention.

The EC (Electronic Compass) module 30 is a MEMS-based geomagnetic sensor capable of detecting not only a large magnetic field generated by a nearby magnet but also a small magnetic field such as a geomagnetic field. From the EC module 30, azimuth angle can be known by using geomagnetism data. The calculation of the azimuth angle of the object from the geomagnetism data values of the EC module 30 is a known technique, and a further explanation will be omitted.

The IMU (Inertial Measurement Unit) module 40 is a MEMS-based sensor for measuring the acceleration of an object. The IMU module 40 has a built-in three-axis acceleration sensor, and it is possible to measure the acceleration in the traveling direction, the lateral direction, and the height direction.

In the present invention, only the X-axis accelerometer component and the Y-axis accelerometer component of the IMU module 40 are used for calculating the azimuth angle of the object.

The first to fourth communication units 60, 70, 80 and 90 are electrically connected to the GPS module 20, the EC (sensor) module 30 and the IMU (sensor) module 40, ) Information.

The first to fourth communication units can communicate using RS232, I2C, CAN, and USB communication methods, respectively. However, the communication methods are merely exemplary and do not limit the communication method.

The controller 50 may be a microprocessor or a control board including the microprocessor.

The control unit 50 receives information (or sensing information) about the moving acceleration and direction (direction) of the object in real time from the GPS module 20, the EC module 30, and the IMU module 40 .

The controller 50 calculates an azimuth angle (FAz, Forward Azimuth) for the three GSP receivers, an azimuth angle for the EC module, and an X-axis and an Y-axis for the IMU module in order to calculate a real-time azimuth angle of the object received from the GPS module 20. [ The axis accelerometer value is used.

In other words, Equation 1 of the GPS azimuth and the initial azimuth angle? (GPSi_yaw) is shown.

(1)

Here, Lat is the abbreviation of latitude and Long is the abbreviation of longitude.

The controller 50 also evaluates whether the value is a valid GPS data value using the classification and the weight from the value received from the GPS module 20. [ That is, the validity of the value received from the GPS module 20 is determined based on the horizontal position error (HDOP) and the fix quality of GPS data.

That is, when the horizontal position error (HDOP) and the fix quality of GPS data are combined, it is ideal when HDOP is 1 to 2 and FIX is 2 to 5, 2, the case where FIX is 1, the case where HDOP is 3 to 5 and the case where FIX is 2 to 5 is very excellent, the case where HDOP is 3 to 5 and FIX is 1, the case where HDOP is 6 to 10 When FIX is 2 to 5, it is judged to be good. Otherwise, all are judged to be bad.

The controller 50 may calculate an azimuth angle with respect to the GPS and the EC using the azimuth angle and the weight of the GPS module, the azimuth angle and the weight of the EC module, and is expressed by Equation (2).

(2)

Here, n is the total number of GPS, is idealValue weight at the ideal state, h _fused is fused and GPS heading EC, _EC h is the azimuth of the EC, w _allGPS , W _EC is the weight of EC, h _allGPS is the total heading of n GPSs, w _i is the weight assigned to the i-th GPS, and h _i is the azimuth of i-th GPS.

Meanwhile, if the GPS data acquired from the three GPSs are not valid or missing, the controller 50 may assign the product of the azimuth angle h _EC and the weight W _{EC to} h _fused .

The controller 50 also receives the values of the X-axis accelerometer and the X-axis accelerometer IMU (Acc _x , Acc _y ) from the values received from the IMU module 40 )).

In addition, the control unit 50 calculates an azimuth for GPS and EC calculated using three low-cost GPS receivers, a single EC module, and a single IMU module, and an improved azimuth from IMU (Acc _x , Acc _y ) The azimuth angle of the object can be accurately calculated by calculating the final fusion azimuth angle (psi_CI) using the extended Kalman filter (EKF) to which the covariance intersection point (CI) is applied.

In other words, the fusion of the accelerometer values of a single IMU module and the Extended Kalman Filter (EKF) are performed while the three GPS receivers and the single EC module are fused, and the EKF input is lat _i , long _i , and GPSi_yaw and localized accelerometers measure the local gravity vector is combined covariance matrix of the IMU (PCI), EKF output as lat _i _EKF, long _i _EKF, psi _i _EKF and covariance is a matrix P_EKF, input to the EKF output The final fusion heading value is calculated as psi_CI by performing the CI and repeating the output so that the output values become lat_CI, long_CI, psi_CI and the covariance matrix (PCI).

Of course, the above calculations are repeatedly performed on newly detected GPS, EC, and IMU values for an object (farm machinery) in motion.

The data storage unit 100 stores all the data received from the GPS module 20, the EC module 30 and the IMU module 40 and the GPS bearing rope, EC azimuth, GPS- EC azimuth, and final fusion azimuth are stored in real time.

FIG. 2 is a flowchart illustrating a method of calculating a real-time azimuth angle of an object using an extended Kalman filter (EKF-CI) to which a covariance intersection point according to an embodiment of the present invention is applied, FIG. 3 is a cross- Fig. 1 is a flowchart for deriving a final fusion azimuth angle of an object using an applied extended Kalman filter (EKF-CI).

As shown in the figure, the method for calculating the real-time azimuth angle of an object using the EKF-Cl according to an embodiment of the present invention calculates a front azimuth angle of the GPS from the GPS data of the object received from the GPS module 20 in the controller 50 (S10); (S20) evaluating the validity of the GPS data based on the horizontal position error (HDOP) and the correction quality (FIX) value in the controller (50); (S30) of calculating an EC azimuth angle of the object through the geomagnetism data received from the EC (Electronic Compass) module 30 in the control unit 50; Calculating (S40) an azimuth angle with respect to GPS and EC of the object from the azimuth angle and weight of the GPS module, the azimuth angle and weight of the EC module in the controller 50; Calculating (S50) an accelerometer value of the object (X axis and Y axis) from the value received from the IMU module 40 in the controller 50; The control unit 50 calculates an actual final convergence azimuth angle psi_CI using an extended Kalman filter (EKF) to which a covariance intersection point CI is applied based on the azimuth angle for the GPS and the EC and the accelerometer value received from the IMU module Step S60; And repeating the above-described steps S10 to S60 for the GPS, EC, and IMU module reception values detected by the controller 50.

 The extended Kalman filter is a well-known algorithm, and a further detailed description will be omitted.

In the step S10 of calculating the GPS azimuth using the forward azimuth (FAz) from the real time GPS data of the object received from the GPS module 20 in the controller 50, The initial azimuth angle of the GPS receiver is calculated according to Equation (1).

In the step S20 of evaluating the validity of the GPS data in the controller 50, the control unit may calculate a horizontal dilution of precision (HDOP) and a fix quality of GPS data), and assigns a weight to valid GPS data.

When HDOP is 1 to 2 and FIX is 2 to 5, it is determined that HDOP is 1 to 2 and FIX is 1, and HDOP is 3 to 5, It is judged that the HDOP is 3 to 5 and the FIX is 1. When the HDOP is 6 to 10 and the FIX is 2 to 5, Otherwise, it is preferable that all of them are judged to be bad and excluded.

Also, in the step of calculating the azimuth angle with respect to the GPS and the EC, an azimuth angle with respect to the GPS and the EC is calculated from the azimuth and the initial azimuth, the weight, and the azimuth of the EC calculated by the controller, .

In addition, when the GPS data received from the GPS module is not valid, the control unit preferably applies only the azimuth to the EC.

In the step S30 of calculating the real-time EC azimuth angle of the object through the geomagnetism data received from the EC (Electronic Compass) module 30 in the control unit 50, the control unit 50 controls the EC (Electronic Compass) 30 from the geomagnetism data values received.

Also, in the step of calculating the accelerometer value, the control unit calculates the values of the X-axis accelerometer and the X-axis accelerometer from the received values of the IMU module (IMU (Acc _x , Acc _y )) is preferably calculated.

In the step S40 of calculating the azimuths of the object with respect to the GPS and the EC in real time based on the azimuth, weight and EC azimuth of the GPS in the controller 50, the controller 50 calculates the azimuth and the initial azimuth , The weight value, and the azimuth angle with respect to the GPS and the EC from the azimuth angle of the EC are calculated according to Equation (2).

Here, the controller 50 is not valid or the GPS data acquired from the three GPS, if the missing has only a bearing for the EC h _fused be applied as allocated by "_ GPSEC yaw".

In step S50 of calculating the real-time accelerometer value of the object from the value received from the IMU module 40 in the control unit 50, the control unit 50 calculates the X-axis acceleration value from the value received from the IMU module 40, (Acc _x , Acc _y ) of the X-axis accelerometer and the X-axis accelerometer.

The control unit (50) performs an expansion using a covariance intersection (CI) based on the azimuth for GPS and EC calculated from the GPS data and geomagnetism data received from the GPS module and the EC module and the accelerometer value received from the IMU module In the step S60 of calculating the final convergence azimuth angle psi_CI using the Kalman filter EKF-CI, the control unit 50 calculates the final convergence azimuth angle psi_CI using the three low-cost GPS, the single EC, and the GPS (Psi_CI) using an extended Kalman filter (EKF) with a covariance intersection (CI) to calculate the azimuth to the EC and the azimuth from the IMU (Acc _x , Acc _y ) The azimuth angle can be accurately calculated.

That is, the fusion of the accelerometer the value of a single IMU again in a state that combines the three GPS and a single EC and extended Kalman filter; but perform (EKF Extended Kalman Filter), EKF input lat _i, long _i, GPSi_yaw (GPS if not valid for the local gravity of the above-described GPSEC _yaw applicable) and local accelerometer measurements IMU vector combination covariance matrix (PCI) and, EKF output lat _i _EKF, long _i _EKF, psi _i _EKF and the covariance matrix P_EKF, and the final fusion header value is calculated as psi_CI by repeatedly performing the CI with the EKF output as input and repeating the output values as lat_CI, long_CI, psi_CI and covariance matrix (PCI).

In addition, the azimuth angle of the object is calculated in real time by repeatedly calculating the updated values of the GPS, EC, and IMU modules for the moving object (farm machinery) (S10 to S60).

It is to be understood that the invention is not limited to the form set forth in the foregoing description. Accordingly, the true scope of the present invention should be determined by the technical idea of the appended claims. It is also to be understood that the invention includes all modifications, equivalents, and alternatives falling within the spirit and scope of the invention as defined by the appended claims.

110: Azimuth calculation device of object using extended Kalman filter (EKF-Cl)
10:
20: GPS module
30: EC module
40: IMU module
50:
60: first communication section
70:
80: Third communication section
90: fourth communication section
100: Data storage unit

Claims (9)

Calculating a GPS azimuth using a forward azimuth of GPS from real time GPS data of an object received from a GPS module in a control unit;
Evaluating the validity of GPS data on the basis of horizontal position error (HDOP) and fix quality of GPS (FIX) values in the controller;
Calculating a real-time EC azimuth angle of an object through geomagnetism data received from an EC (Electronic Compass) module in the control unit;
Calculating an azimuth angle of the object with respect to GPS and EC in real time based on the azimuth angle and the EC azimuth of the GPS in the control unit;
Calculating a real-time accelerometer value of the object from the value received from the IMU module in the control unit;
Calculating a final convergence azimuth angle (psi_CI) using an extended Kalman filter (EKF) to which a covariance intersection (CI) is applied based on an azimuth angle for the GPS and the EC module and an accelerometer value received from the IMU module; And
And repeating the above steps for received values from the GPS module, the EC module, and the IMU module newly detected by the control unit,
In the step of evaluating the validity of the GPS data, the controller determines validity of the value received from the GPS module on the basis of a horizontal position error (HDOP) and a fix quality of GPS data, And a weight is assigned to the data,
In calculating the azimuth for GPS and EC, the azimuth angle with respect to GPS and EC from the azimuth and initial azimuth, the weight, and the azimuth of EC calculated by the controller is calculated by the following equation A method for calculating the real-time azimuth angle of an object using an extended Kalman filter (EKF-Cl) with a covariance intersection feature.
(2)

Here, n is the total number of GPS, idealValue the weight at the ideal state, h _fused has all the weights, w _EC of the fused GPS and EC head, h _EC calculates the azimuth of the EC, w _allGPS is combined GPS azimuth is EC of weight, h is n _allGPS Close All headings of GPS, w _i - i-th GPS weights assigned to, h _i is the calculated azimuth angle of the i-th GPS.
The method according to claim 1,
In the step of calculating the GPS azimuth using the forward azimuth angle, a GPS azimuth and an initial heading value for a plurality of GPSs are calculated using a forward azimuth (Faz) according to the following equation Real-time azimuth calculation method using an extended Kalman filter (EKF-Cl) with covariance intersection.
(1)

Here, Lat is the abbreviation of latitude and Long is the abbreviation of longitude.
delete The method according to claim 1,
It is determined that the HDOP is 1 to 2 and the FIX is 2 to 5 and that the HDOP is 1 to 2 and that FIX is 1 and that when HDOP is 3 to 5 and FIX is 2 to 5, 5, it is determined that the HDOP is excellent. When the HDOP is 3 to 5 and the FIX is 1, the HDOP is 6 to 10 and the FIX is 2 to 5, (EKF-Cl) to which a covariance intersection point is applied, wherein all of the objects are judged to be bad and excluded.
delete The method according to claim 1,
Wherein the controller applies only the azimuth angle to the EC when the GPS data received from the GPS module is invalid, using the extended Kalman filter (EKF-Cl) to which the covariance intersection is applied.
The method according to claim 1,
In the step of calculating the accelerometer value, the controller calculates values (Acc _x , Acc _y ) of an X-axis accelerometer and an X-axis accelerometer from values received from the IMU module, Calculating a real-time azimuth angle of an object using an extended Kalman filter (EKF-Cl) to which a covariance intersection point is applied.
The method according to claim 1,
In calculating the final convergence azimuth (psi_CI), the control unit calculates an azimuth for the GPS and EC calculated using a plurality of GPSs, a single EC, and a single IMU and an improved azimuth from the accelerometer value Calculating a final convergence azimuth angle (psi_CI) using an extended Kalman filter (EKF) to which a covariance intersection point (CI) is applied; calculating a real-time azimuth angle of an object using an extended Kalman filter (EKF-Cl) .
9. The method of claim 8,
A plurality of GPS and combines the accelerometer the value of a single IMU again in a fusion with the azimuth state for a single EC and extended Kalman filter; but perform (EKF Extended Kalman Filter), EKF input lat _i, long _i, GPSi_yaw and and localized accelerometers measure the local gravity vector is combined covariance matrix of the IMU (PCI), EKF output lat _i _EKF, long _i _EKF, psi _i _EKF and covariance is a matrix P_EKF, CI to the EKF output to the input And the final convergence heading value is calculated as psi_CI by repeatedly performing an operation such that the output values are lat_CI, long_CI, psi_CI, and the covariance matrix PCI, by using the extended Kalman filter (EKF-Cl) Time azimuth calculation method.

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