UAV power line position and load parameter estimation

• US 9,037,314 B2
• Filed: 06/20/2011
• Issued: 05/19/2015
• Est. Priority Date: 06/21/2010
• Status: Active Grant

• Current Assignee: Optimal Ranging Inc
• Original Assignee: Optimal Ranging Inc
• Inventors: Waite, James W., Gudmundsson, Thorkell, Gargov, Dimitar
• Primary Examiner(s): Beaulieu, Yonel
• Assistant Examiner(s): KLEINMAN, LAIL A
• Application Number:
  US13/164,611
• Publication Number:
  US 20120016538A1
• Time in Patent Office: 1,429 Days
• Field of Search: 701/3, 701/300, 324/76.39, 324/330, 324/331
• US Class Current: 701/3
• CPC Class Codes: B64U 2201/10 autonomous, i.e. by navigating independently from ground or air stations, e.g. by using inertial navigation systems [INS]
• CPC Class Codes: G01B 7/00 Measuring arrangements characterised by the use of electric or magnetic techniques
• CPC Class Codes: G01C 21/005 with correlation of navigation data from several sources, e.g. map or contour matching G01C21/30 takes precedence
• CPC Class Codes: G01C 21/20 Instruments for performing navigational calculations G01C21/24, G01C21/26 take precedence
• CPC Class Codes: G05D 1/10 Simultaneous control of position or course in three dimensions G05D1/12 takes precedence
• CPC Class Codes: G05D 1/101 specially adapted for aircraft

Abstract

A system and method for providing autonomous navigation for an Unmanned Air Vehicle (UAV) in the vicinity of power lines is presented. Autonomous navigation is achieved by measuring the magnitude and phase of the electromagnetic field at an unknown location within a space under excitation by a set of power cables of the power line with one or more orthogonal electromagnetic sensors formed on the UAV; modeling a set of expected complex electromagnetic strengths of the set of power cables at the currently estimated position and orientation of the UAV based on a model of the set of power cables; and estimating parameters related to a position and orientation of the UAV, and load parameters of each cable based on the residual error between the measured set of complex electromagnetic field values and the set of expected electromagnetic field values corresponding to a combined model of the set of power cables.

Claims

1. A method for providing autonomous navigation for an Unmanned Air Vehicle (UAV) in the vicinity of power lines, comprising:

measuring a set of complex magnetic field values of a magnetic field emitted by each of the power lines using one or more magnetic field sensors mounted on the UAV as the UAV is traversing the magnetic field at a position and an orientation relative to each of the power lines;

modeling, by a processor, a set of expected complex magnetic field values of the magnetic field when the UAV is at the position and the orientation relative to each of the power lines based on a first model of the power lines;

estimating an estimated position and an estimated orientation of the UAV relative to each of the power lines and magnitude and phase of current flowing in each of the power lines, based on a residual error between the measured set of complex magnetic field values and the set of expected complex magnetic field values corresponding to the first model of the power lines;

measuring a set of complex electric field values of an electric field emitted by each of the power lines using one or more electric field sensors mounted on the UAV;

modeling, by the processor, a set of expected complex electric field values of the electric field emitted by each of the power lines based on a second model when the UAV is at the position and the orientation and when the UAV is at the estimated position and the estimated orientation relative to each of the power lines;

updating the position and orientation based on the modeling of a set of expected complex electric field values;

estimating a phase offset of the current flowing in each of the power lines relative to a power grid timebase, based on a residual error between the measured set of complex electric field values and the set of expected electric field values corresponding to the second model of the power lines; and

navigating the UAV using the parameters related to the position and the orientation of the UAV relative to each of the power lines.

2. The method of claim 1, further comprising:

estimating power grid synchronized load parameters of each of the power lines,

wherein the power grid synchronized load parameters of each of the power lines includes amplitude and phase of voltage applied current to each of the power lines, and a phase offset between the current flowing in each of the power lines and the voltage applied to each of the power lines.

3. The method of claim 2, further comprising:

validating the position and the orientation of the UAV relative to each of the power lines, the magnitude and the phase of the current flowing in each of the power lines, positions of the power lines, the power grid synchronized load parameters, and the phase offset of the current flowing in each of the power lines relative to the power grid timebase, using the residual error between the measured set of complex electric field values and the set of expected complex electric field values corresponding to a combined model.

9. The method of claim 1, wherein the set of complex magnetic field values include magnitude and phase of the magnetic field, and

wherein the set of complex electric field values include magnitude and phase of the electric field.

10. The method of claim 1, wherein any of the one or more magnetic field sensors and the one or more electric field sensors includes a 3-axis sensor being mounted along three substantially orthogonal directions on the UAV.

11. The method of claim 1, wherein the parameters related to the position and orientation of the UAV relative to each of the power lines include at least one of a horizontal offset, a vertical offset, a yaw angle of the UAV relative to each of the power lines, a pitch angle of the UAV relative to each of the power lines, and distance between two adjacent power lines.

12. The method of claim 1, wherein the first model relates the current flowing in each of the power lines to the emitted magnetic field.

13. The method of claim 1, wherein the position and the orientation of the UAV relative to each of the power lines used for modeling the expected complex magnetic field values are calculated by applying a numerical optimization method to a plurality of measurements by the magnetic field sensors.

14. The method of claim 1, wherein a Kalman filter is used to estimate the parameters related to the position and orientation of the UAV relative to each of the power lines.

15. The method of claim 2, wherein the second model calculates the magnitude and the phase of the emitted electric field.

16. The method of claim 1, wherein the distance between the UAV and the power lines is in a range from about 5 meters to 40 meters.

17. The method of claim 1, wherein a set of Kalman filters are used to estimate the parameters related to the position and the orientation of the UAV relative to each of the power lines, and the magnitude and phase of the current flowing in each of the power lines.

18. The method of claim 3, wherein the combined model includes a combination of the first and second models.

4. A method for estimating a location of an Unmanned Air Vehicle (UAV) in the vicinity of power lines and power grid synchronized load parameters of each of the power lines as the UAV traversing a magnetic field and an electric field emitted by the power lines, the method comprising:

measuring a set of complex magnetic field values of the magnetic field using one or more magnetic field sensors mounted on the UAV at a position and an orientation of the UAV relative to each of the power lines;

measuring a set of complex electric field values of the electric field of each of the power lines using one or more electric field sensors mounted on the UAV;

modeling, by a processor, a set of expected complex magnetic field values of each of the power lines when the UAV is at the position and the orientation relative to each of the power lines based on a first model of the set of power cables;

modeling, by the processor, a set of expected complex electric field values of each of the power lines using when the UAV is at the position and orientation relative to each of the power lines based on a second model of the power lines;

jointly estimating parameters related to 3-d position of each of the power lines relative to the UAV, complex electric current in each of the power lines, the power grid synchronized load parameters, and phase offset of current flowing in each of the power lines relative to a power grid timebase, based on a residual error between the measured set of complex magnetic field values and the set of expected complex magnetic field values, and a residual error between the measured set of complex electric field values and the set of expected complex electric field values corresponding to a combined model of the power lines; and

navigating the UAV using the parameters related to the 3-d position and the orientation of the UAV relative to each of the power lines.

5. The method of claim 4, wherein embedded 3-d features of the power lines are detected when there is reduced correspondence between a 2-d model and 3-d field measurements, the embedded 3-d features including towers, intersections, catenaries, or direction changes.

19. The method of claim 4, wherein the parameters related to 3-d position of the UAV relative to each of the power lines include at least one of a horizontal offset, a vertical offset, a yaw angle of the UAV relative to each of the power lines, a pitch angle of the UAV relative to each of the power lines, and distance between two adjacent power lines.

6. A navigation system for an Unmanned Air Vehicle (UAV), comprising:

a plurality of electric field sensors configured to measure a set of complex electric field values of an electric field emitted by each of the power lines aboveground, the plurality of the electric field sensors being mounted on the UAV;

a plurality of magnetic field sensors configured to measure a set of complex magnetic field values of a magnetic field emitted by power lines aboveground, the plurality of magnetic field sensors being mounted along three substantially orthogonal directions on the UAV;

circuitry coupled to receive signals from the plurality of electric field sensors and the plurality of magnetic field sensors, and to provide quadrature signals indicating the set of measured complex electric field values and the set of measured complex magnetic field values;

a position and orientation autopilot for indicating position and orientation over ground of the UAV relative to each of the power lines as it traverses the magnetic field emitted by the power lines; and

a processor coupled to receive the set of measured complex magnetic field values and the set of measured complex electric field values, and to calculate parameter values related to the position of each of the power lines, phase offset of current flowing in each of the power lines relative to a power grid timebase, and magnitude and phase of electric current flowing in each of the power lines;

wherein the processor includes software for performing the following;

modeling a set of expected complex magnetic field values of each of the power lines when the UAV is at the position and orientation relative to each of the power lines based on a first model of the power lines;

modeling a set of expected complex electric field values of the electric field emitted by each of the power lines based on a second model of the power lines when the UAV is at the position and the orientation and the estimated position and orientation relative each of the power lines;

jointly estimating parameters related to the position of the UAV relative to each of the power lines and the magnitude and phase of the electric current in each of the power lines, based on a residual error between the measured set of complex magnetic field values and the set of expected complex magnetic field values corresponding to the first model of the power lines, and a residual error between the measured set of complex electric field values and the set of expected complex electric field values corresponding to the second model of the power lines; and

navigating the UAV using the parameters related to the position and the orientation of the UAV relative to each of the power lines.

7. The navigation system of claim 6, wherein the processor is further configured to estimate the power grid synchronized load parameters of each of the power lines, and

wherein the power grid synchronized load parameters of each of the power lines includes amplitude and phase of voltage applied to each of the power lines, and a phase offset between the current flowing in each of the power lines and the voltage applied to each of the power lines.

8. The navigation system of claim 7, wherein the residual error between the measured set of complex electric field values and the set of expected complex electric field values corresponding to a combined model of the power lines is used to validate the position of the UAV relative to each of the power lines, magnitude and phase of the current flowing in each of the power lines, positions of the power lines, the power grid synchronized load parameters, and the phase offset of the current flowing in each of the power lines relative to the power grid timebase.

20. The navigation system of claim 6, wherein the parameters related to the position of the UAV relative to each of the power lines include at least one of a horizontal offset, a vertical offset, a yaw angle of the UAV relative to each of the power lines, a pitch angle of the UAV relative to each of the power lines, and distance between two adjacent power lines.