Three dimensional direction finder with one dimensional sensor array

• US 9,995,817 B1
• Filed: 04/21/2015
• Issued: 06/12/2018
• Est. Priority Date: 04/21/2015
• Status: Active Grant

• Current Assignee: Lockheed Martin Corporation (Martin Marietta Corporation)
• Original Assignee: Lockheed Martin Corporation (Martin Marietta Corporation)
• Inventors: Mittiga, David M.
• Primary Examiner(s): Bhat, Aditya
• Application Number:
  US14/692,192
• Time in Patent Office: 1,148 Days
• Field of Search: None
• CPC Class Codes: G01B 21/22 for measuring angles or tapers; for testing the alignment of axes
• CPC Class Codes: G01S 3/04 Details
• CPC Class Codes: G01S 5/0018 Transmission from mobile station to base station
• CPC Class Codes: G01S 5/0294 Trajectory determination or predictive filtering, e.g. target tracking or Kalman filtering
• CPC Class Codes: G01S 5/16 using electromagnetic waves other than radio waves

Abstract

A tracking computer system may track a target using a single linear array. The system may receive first sensor measurements and one or more additional sensor measurements from the linear array. The system may determine whether a location of the target can be identified based on a cone intersection algorithm. When the target location can be identified based on the cone intersection algorithm, the first and the one or more additional sensor measurements may be applied to the cone intersection algorithm to identify the target location. When target location cannot be identified based on the cone intersection algorithm, the first and the one or more additional sensor measurements may be applied to an angular motion model to determine a best fit arc path corresponding to the target. A true target angle estimate and a target angular velocity may be determined based on the determined best fit arc path.

Claims

1. A direction finding system for tracking a target comprising:

a linear sensor array configured to be attached to a structure;

one or more data storage devices for storing sensor measurements from the linear sensor array, a cone intersection algorithm, and an angular motion model configured to determine a best fit arc path, a true target angle estimate, and a target angular velocity corresponding to the target;

a command and decision unit including one or more computer processors in communication with the one or more data storage devices; and

a memory storing program instructions which, when executed by the one or more computer processors, cause the one or more computer processors to;

receive first sensor measurements from the linear sensor array relating to the target including a first time of capture, a first cone angle, and a first linear sensor array axis orientation;

receive one or more additional sensor measurements from the linear sensor array relating to the target including at least one or more additional times of capture, one or more additional cone angles, and one or more additional linear sensor array axis orientations;

determine whether a location of the target can be identified based on the cone intersection algorithm;

responsive to a determination that the location of the target can be identified based on the cone intersection algorithm, apply the first sensor measurements and the one or more additional sensor measurements to the cone intersection algorithm to identify the location of the target and the true target angle corresponding to the target, wherein the location of the target corresponds to an intersection between the first cone angle and the one or more additional cone angles determined by the cone intersection algorithm;

responsive to a determination that the location of the target cannot be identified based on the cone intersection algorithm, apply the first sensor measurements and the one or more additional sensor measurements to the angular motion model to determine;

the best fit arc path corresponding to the target; and

the true target angle estimate and the target angular velocity for the target based on the determined best fit arc path; and

output one or both of the true target angle estimate and the target angular velocity corresponding to the target for determining target location.

2. The direction finding system of claim 1, wherein the memory storing program instructions to determine whether the location of the target can be identified based on the cone intersection algorithm comprises the memory storing program instructions to determine that a target can be identified based on a cone intersection algorithm when an angle between the first linear sensor array axis orientation and one of the one or more additional linear sensor array axis orientations is greater than a threshold angle.

3. The direction finding system computer of claim 1, wherein the angular motion model being configured to determine a best fit arc path comprises the angular motion model being configured to:

determine a best fit angle based on the first cone angle and the one or more additional cone angles; and

determine a tangent velocity vector corresponding to the best fit angle.

4. The direction finding system of claim 1, wherein the angular motion model being configured to determine a best fit arc path comprises the angular motion model being configured to approximate the best fit arc path based on equations:

p(t)=p₀+vt

|p₀|=1

p₀·

v=0

wherein p is target location, v is velocity, and t is time.

5. The direction finding system of claim 1, wherein the angular motion model being configured to determine the true target angle estimate and the target angular velocity for the target based on the determined best fit arc path comprises the angular motion model being configured to:

generate a system of equations based on the determined best fit arc path and the first sensor measurements and the one or more additional sensor measurements; and

determine a solution to the system of equations based on a numerical method.

6. The direction finding system of claim 5, wherein the numerical method comprises a trust-region dogleg algorithm.

7. The direction finding system of claim 5, wherein the angular motion model being configured to determine the solution to the system of equations based on the numerical method further comprises the angular motion model being configured to analytically determine a Jacobian of the system of equations.

8. The direction finding system of claim 1, wherein the memory stores further program instructions which cause the one or more computer processors to transmit, to a tracker computer, the true target angle estimate and the target angular velocity for the target.

9. A method for tracking a target using a linear sensor array of a direction finding system comprising:

storing, in a computer memory, a cone intersection algorithm, and an angular motion model configured for determining a best fit arc path, a true target angle estimate, and a target angular velocity corresponding to the target;

receiving with a command and decision unit, first sensor measurements from a linear sensor array of the direction finding system corresponding to a target including a first time of capture, a first cone angle, and a first linear sensor array axis orientation;

receiving with the command and decision unit, one or more additional sensor measurements from the linear sensor array corresponding to the target including one or more additional times of capture, one or more additional cone angles, and one or more additional linear sensor array axis orientations;

determining, by one or more computer processors of the command and decision unit, whether a location of the target can be identified based on the cone intersection algorithm;

responsive to a determination that the location of the target can be identified based on the cone intersection algorithm, applying, by the one or more computer processors of the command and decision unit, the first sensor measurements and the one or more additional sensor measurements to the cone intersection algorithm to identify the location of the target and a true target angle corresponding to the target, wherein the location of the target corresponds to an intersection between the first cone angle and the one or more additional cone angles determined by the cone intersection algorithm;

responsive to a determination that the location of the target cannot be identified based on the cone intersection algorithm, applying, by the one or more computer processors of the command and decision unit, the first sensor measurements and the one or more additional sensor measurements to the angular motion model to determine;

the best fit arc path corresponding to the target; and

the true target angle estimate and a target angular velocity for the target based on the determined best fit arc path; and

outputting, by the one or more computer processors of the command and decision unit based on application of the first sensor measurements and the one or more additional sensor measurements to the angular motion model, one or both of the true target angle estimate and the target angular velocity corresponding to the target for determining target location.

10. The method of claim 9, wherein determining whether the location of the target can be identified based on the cone intersection algorithm comprises determining that a target can be identified based on the cone intersection algorithm when an angle between the first linear sensor array axis orientation and one of the one or more additional linear sensor array axis orientations is greater than a threshold angle.

11. The method of claim 9, wherein the angular motion model being configured for determining a best fit arc path comprises the angular motion model being configured for:

determining a best fit angle based on the first cone angle and the one or more additional cone angles; and

determining a tangent velocity vector corresponding to the best fit angle.

12. The method of claim 11, wherein determining the best fit angle based on the first cone angle and the one or more additional cone angles and determining the tangent velocity vector corresponding to the best fit angle comprises:

determining a midpoint axis to the first sensor array axis orientation and the one or more additional sensor array axis orientations; and

determining, based on the midpoint axis, the tangent velocity vector to the midpoint axis.

13. The method of claim 9, wherein the angular motion model being configured for determining a best fit arc path comprises the angular motion model being configured for approximating the best fit arc path based on equations:

p(t)=p₀+vt

|p₀|=1

p₀·

v=0

wherein p is target location, v is velocity, and t is time.

14. The method of claim 9, wherein the angular motion model being configured for determining the true target angle estimate and the target angular velocity for the target based on the determined best fit arc path comprises the angular motion model being configured for:

generating a system of equations based on the determined best fit arc path and the first sensor measurements and the one or more additional sensor measurements; and

determining a solution to the system of equations based on a numerical method.

15. The method of claim 14, wherein the numerical method comprises a trust-region dogleg algorithm.

16. A tracking computer system for actively tracking a target using a linear sensor array mounted to a structure:

one or more data storage devices for storing sensor measurements from the linear sensor array, a cone intersection algorithm, and an angular motion model configured to determine a best fit arc path, a true target angle estimate, and a target angular velocity corresponding to the target;

one or more tracking computer processors in communication with the one or more data storage devices;

a memory storing program instructions which, when executed by the one or more tracking computer processors, cause the one or more computer processors to;

receive first sensor measurements from the linear sensor array relating to the target including a first time of capture, a first cone angle, and a first linear sensor array axis orientation;

receive one or more additional sensor measurements from the linear sensor array relating to the target including one or more additional times of capture, one or more additional cone angles, and one or more additional linear sensor array axis orientations;

determine whether a location of the target can be identified based on the cone intersection algorithm based on whether an angle between the first linear sensor array axis orientation and one of the one or more additional linear sensor array axis orientations is greater than a threshold angle;

responsive to a determination that the location of the target can be identified based on the cone intersection algorithm, apply the first sensor measurements and the one or more additional sensor measurements to the cone intersection algorithm to identify the location of the target and a true target angle corresponding to the target, wherein the location of the target corresponds to an intersection between the first cone angle and the one or more additional cone angles determined by the cone intersection algorithm;

responsive to a determination that the location of the target cannot be identified based on the cone intersection algorithm, apply the first sensor measurements and the one or more additional sensor measurements to the angular motion model to determine;

the best fit arc path corresponding to the target; and

the true target angle estimate and the target angular velocity for the target based on the determined best fit arc path; and

output, based on application of the first sensor measurements and the one or more additional sensor measurements to the angular motion model, one or both of the true target angle estimate and the target angular velocity corresponding to the target for determining target location.

17. The tracking system of claim 16, wherein the angular motion model being configured to determine a best fit arc path comprises the angular motion model being configured to:

determine a best fit angle based on the first cone angle and the one or more additional cone angles; and

determine a tangent velocity vector corresponding to the best fit angle.

18. The tracking system of claim 16, wherein the angular motion model being configured to determine a best fit arc path comprises the angular motion model being configured to approximate the best fit arc path based on equations:

p(t)=p₀+vt

|p₀|=1

p₀·

v=0

wherein p is target location, v is velocity, and t is time.

19. The tracking system of claim 16, wherein the angular motion model being configured to determine the true target angle estimate and the target angular velocity for the target based on the determined best fit arc path comprises the angular motion model being configured to:

generate a system of equations based on the determined best fit arc path and the first sensor measurements and the one or more additional sensor measurements; and

determine a solution to the system of equations based on a numerical method.

20. The tracking system of claim 19, wherein the numerical method comprises a trust-region dogleg algorithm.