Heading for a hybrid navigation solution based on magnetically calibrated measurements

• US 9,939,532 B2
• Filed: 01/09/2015
• Issued: 04/10/2018
• Est. Priority Date: 01/09/2015
• Status: Active Grant

• Current Assignee: Honeywell International Inc.
• Original Assignee: Honeywell International Inc.
• Inventors: Kana, Zdenek, Dunik, Jindrich, Sotak, Milos
• Primary Examiner(s): Mawari, Redhwan K
• Assistant Examiner(s): King, Rodney P.
• Application Number:
  US14/593,266
• Publication Number:
  US 20160202359A1
• Time in Patent Office: 1,187 Days
• Field of Search: 701472
• CPC Class Codes: E21B 44/00 Automatic control systems specially adapted for drilling operations, i.e. self-operating systems which function to carry out or modify a drilling operation without intervention of a human operator, e.g. computer-controlled drilling systems; Systems specially adapted for monitoring a plurality of drilling variables or conditions
• CPC Class Codes: G01B 7/00 Measuring arrangements characterised by the use of electric or magnetic techniques
• CPC Class Codes: G01C 17/38 Testing, calibrating, or compensating of compasses
• CPC Class Codes: G01C 21/08 involving use of the magnetic field of the earth
• CPC Class Codes: G01C 21/1654 with electromagnetic compass
• CPC Class Codes: G01S 19/47 the supplementary measurement being an inertial measurement, e.g. tightly coupled inertial

Abstract

One embodiment is directed towards a method for determining a heading for a hybrid navigation system with magnetometer aiding. The method includes receiving signals from a plurality of GNSS satellites, obtaining three-dimensional inertial measurements from one or more inertial sensors, and obtaining three-dimensional magnetic measurements from one or more magnetometers. Magnetic bias states are estimated for the three-dimensional magnetic measurements with a magnetic calibration filter using the three-dimensional inertial measurements, data from the signals from the plurality of GNSS satellites, and the three-dimensional magnetic measurements. An artificial heading is calculated based on the magnetic bias states. A main navigation solution can be estimated with a main navigation filter using the three-dimensional inertial measurements, data from the signals from a plurality of GNSS satellites, and the artificial heading.

Claims

1. A method for determining a heading for a hybrid navigation system with magnetometer aiding, the method comprising:

receiving signals from a plurality of global navigation satellite system (GNSS) satellites at a location corresponding to an object;

obtaining three-dimensional inertial measurements from one or more inertial sensors corresponding to the object;

obtaining three-dimensional magnetic measurements from one or more magnetometers corresponding to the object;

estimating states for position, velocity, roll, pitch, and heading of the object with a magnetic calibration filter;

estimating states for calibration of the three-dimensional inertial measurements with the magnetic calibration filter;

estimating states for bias and drift of a GNSS clock with the magnetic calibration filter; and

estimating states for pseudorange biases for the signals from the GNSS satellites with the magnetic calibration filter

estimating nine soft iron bias states and three hard iron bias states for biases of the three-dimensional magnetic measurements with the magnetic calibration filter using the three-dimensional inertial measurements, data from the signals from the plurality of GNSS satellites, and the three-dimensional magnetic measurements;

calculating an artificial heading for the object as a function of

ψ

_ma=f(θ

,φ

,m_cal^Bx,m_cal^By,m_cal^Bz,ψ

_dec)

where φ

is the roll estimate from a main navigation filter, θ

is the pitch estimate from the main navigation filter, ψ

_dec is the magnetic declination, and m_cal^Bx, m_cal^By, and m_cal^Bz are calibrated magnetic measurements with components x, y, and z in the body frame, respectively, wherein m_cal^B is calculated as a function of

m_cal^B=f(D_mag,{tilde over (m)}^B,b_mag^B)

where D_mag is the magnetic bias state matrix corresponding to soft iron biases, b_mag^B is the magnetic bias state vector corresponding to hard iron biases, and {tilde over (m)}^B is the three-dimensional magnetic measurements;

estimating a main navigation solution for the object with the main navigation filter using the three-dimensional inertial measurements, data from the signals from a plurality of GNSS satellites, and the artificial heading.

2. The method of claim 1, wherein estimating magnetic bias states includes estimating nine states for soft iron biases and three states for hard iron biases.

3. The method of claim 1, comprising:

obtaining barometric measurements corresponding to the object;

estimating a state for bias of the barometric measurements with the magnetic calibration filter; and

estimating a state for bias of the barometric measurements with the main navigation filter.

4. The method of claim 1, wherein calculating an artificial heading includes calculating the artificial heading based on the magnetic bias states, the three-dimensional magnetic measurements, roll and pitch estimates of the object from the main navigation filter, and a magnetic declination based on a position estimate of the object from the main navigation filter.

5. The method of claim 4, wherein calculating the artificial heading includes calculating the artificial heading, ψ

_ma, as

6. The method of claim 5, wherein m_cal^B is calculated as

m_cal^B=(D_mag)⁻

1({tilde over (m)}^B)−

b_mag^B.

7. The method of claim 1, comprising:

estimating a time correlated bias error of the artificial heading with the main navigation filter.

8. The method of claim 7, wherein estimating the time correlated bias error includes estimating the time correlated bias error with the main navigation filter and its statistics being approximated based on statistics of the magnetic bias states of the object from the magnetic calibration filter and magnetic declination statistics based on position estimate statistics of the object from the main navigation filter.

9. The method of claim 7, comprising:

estimating states for calibration of the three-dimensional inertial measurements with the main navigation filter;

estimating states for bias and drift of a GNSS clock with the main navigation filter; and

estimating states for pseudorange biases for the signals from the GNSS satellites with the main navigation filter,

wherein estimating a main navigation solution includes estimating states for position, velocity, roll, pitch, and heading of the object.

10. The method of claim 1, comprising:

estimating uncorrelated noise statistics of the artificial heading based on magnetometer measurement noise statistics and statistics of attitude error effect on the artificial heading.

11. The method of claim 1, comprising:

estimating a plurality of sub-solutions for the main navigation solution with a plurality of sub-filters using solution separation;

calculating a heading covariance for each of the plurality of sub-solutions;

calculating a heading covariance for the main navigation solution;

calculating a heading covariance for the magnetic calibration filter;

approximating a plurality of sub-solution heading covariances corresponding to the magnetic calibration filter based on the heading covariance for the main navigation solution, the heading covariance for each of the plurality of sub-solutions, and the heading covariance for the magnetic calibration filter; and

determining a protection limit that bounds error in a heading of the main navigation solution based on respective separations between the heading covariance for the magnetic calibration filter and each of the sub-solution heading covariances corresponding to the magnetic calibration filter.

12. The method of claim 11, wherein approximating the plurality of sub-solution heading covariances corresponding to the magnetic calibration filter includes approximating the n sub-solution heading covariance, Cov(ψ

)_n,3-D, according to

13. A navigation system for an object comprising:

one or more processing devices;

one or more global navigation satellite system (GNSS) receivers coupled to the one or more processing devices, the one or more GNSS receivers configured to obtain pseudorange measurements corresponding to a location of the object;

one or more inertial measurement units (IMUs) coupled to the one or more processing devices, the one or more IMUs configured to obtain three-dimensional inertial measurements corresponding to the object;

one or more magnetometers coupled to the one or more processing devices, the one or more magnetometers configured to obtain three-dimensional magnetic measurements of the magnetic field at a location of the object; and

one or more memory devices coupled to the one or more processing devices and including instructions which, when executed by the one or more processing devices, cause the one or more processing devices to;

estimate states for position, velocity, roll, pitch, and heading of the object with a magnetic calibration filter;

estimate states for calibration of the three-dimensional inertial measurements with the magnetic calibration filter;

estimate states for calibration of a GNSS clock with the magnetic calibration filter; and

estimate states for pseudorange biases for the signals from the GNSS satellites with the magnetic calibration filter;

estimate nine soft iron bias states and three hard iron bias states for biases of the three-dimensional magnetic measurements with the magnetic calibration filter using the three-dimensional inertial measurements for a prediction step, and using data from the one or more GNSS receivers and the three-dimensional magnetic measurements as a measurement vector;

calculate an artificial heading for the object as a function of

ψ

_ma=f(θ

,φ

,m_cal^Bx,m_cal^By,m_cal^Bz,ψ

_dec)

where φ

is the roll estimate from a main navigation filter, θ

is the pitch estimate from the main navigation filter, ψ

_dec is the magnetic declination, and m_cal^Bx, m_cal^By, and m_cal^Bz are calibrated magnetic measurements with components x, y, and z in the body frame, respectively, wherein m_cal^B is calculated as a function of

m_cal^B=f(D_mag,{tilde over (m)}^B,b_mag^B)

where D_mag is the magnetic bias state matrix corresponding to soft iron biases, b_mag^B is the magnetic bias state vector corresponding to hard iron biases, and {tilde over (m)}^B is the three-dimensional magnetic measurements; and

estimate a main navigation solution for the object with the main navigation filter using the three-dimensional inertial measurements for a prediction step, and using data from the one or more GNSS receivers and the artificial heading as a measurement vector.

14. The navigation system of claim 13, wherein estimate magnetic bias states includes estimate nine states for soft iron biases and three states for hard iron biases.

15. The navigation system of claim 14, wherein calculate the artificial heading includes calculate the artificial heading, ψ

_ma, as

16. The navigation system of claim 13, wherein the instructions cause the one or more processing devices to:

estimate a time correlated bias of the artificial heading with the main navigation filter, based on statistics of the magnetic bias states and magnetic declination statistics based on position estimate statistics of the object from the main navigation filter and

estimate an uncorrelated noise of the artificial heading based on magnetometer measurement noise statistics and statistics of attitude error effect on the artificial heading.

17. The navigation system of claim 16, wherein the instructions cause the one or more processing devices to:

estimate states for calibration of the three-dimensional inertial measurements with the main navigation filter;

estimate states for bias and drift of a GNSS clock with the main navigation filter; and

estimate states for pseudorange biases of signals from GNSS satellites with the main navigation filter,

wherein estimate a main navigation solution includes estimate states for position, velocity, roll, pitch, and heading of the object.

18. The navigation system of claim 13, wherein the instructions cause the one or more processing devices to:

estimate a plurality of sub-solutions for the main navigation solution with a plurality of sub-filters using solution separation;

calculate a heading covariance for each of the plurality of sub-solutions;

calculate a heading covariance for the main navigation solution;

calculate a heading covariance for the magnetic calibration filter;

approximating a plurality of sub-solution heading covariances corresponding to the magnetic calibration filter based on a ratio between the heading covariance for the main navigation solution and the heading covariance for each of the plurality of sub-solutions being approximately equal to a ratio between the heading covariance for the magnetic calibration filter and each of the sub-solution heading covariances corresponding to the magnetic calibration filter; and

determine a protection limit that bounds error in a heading of the main navigation solution based on respective separations between the heading covariance for the magnetic calibration filter and each of the sub-solution heading covariances corresponding to the magnetic calibration filter.

19. A computer readable medium including instructions which, when executed by one or more processing devices, cause the one or more processing devices to:

estimate magnetic bias states for biases of three-dimensional magnetic measurements with a magnetic calibration filter using three-dimensional inertial measurements for a prediction step, and using data from signals from a plurality of global navigation satellite system (GNSS) satellites and the three-dimensional magnetic measurements as a measurement vector, wherein estimate magnetic bias states includes estimate nine states for soft iron biases and three states for hard iron biases;

calculate an artificial heading, ψ

_ma, for an object as