Systems and method for dynamic stabilization of target data detected from a moving platform

• US 8,330,810 B2
• Filed: 01/26/2009
• Issued: 12/11/2012
• Est. Priority Date: 02/27/2008
• Status: Active Grant

• Current Assignee: Honeywell International Inc.
• Original Assignee: Honeywell International Inc.
• Inventors: Hamza, Rida, Martinez, Steven
• Primary Examiner(s): GILES, NICHOLAS G
• Application Number:
  US12/359,916
• Publication Number:
  US 20090212994A1
• Time in Patent Office: 1,415 Days
• Field of Search: 701/205, 701/207, 701/210, 701/213, 701/214, 701/215, 701/217, 701/218, 701/220, 701/466, 701/408, 701/411, 701/468, 701/469, 701/470, 701/472, 701/492, 701/500, 348/113, 348/116, 348/117, 348/118, 348/119
• US Class Current: 348/116
• CPC Class Codes: G01S 13/723 by using numerical data
• CPC Class Codes: G06T 7/277 involving stochastic approaches, e.g. using Kalman filters

Abstract

Systems and methods for detecting a present location of a target from a moving platform are provided. One system includes a movement module for estimating the present location of the target, a prediction module for estimating future locations of the target, and a first processor. The first processor is configured to receive present location estimates, receive future location estimates, store the future location estimates to create a first future location estimate, and determine the present location of the target based on the present location estimate and/or the first future location estimate. One method includes receiving an estimate of the present location of the moving platform, receiving an estimate of a future location of the moving platform, and determining the present location of the target based on the estimate of the present location and/or the estimate of the future location.

Claims

1. A system for detecting a target from a moving platform, comprising:

a single camera configured to generate first data representing an object having one or more sides, the first data representing the one or more major sides of the target,

a movement module configured to estimate the present location of the target with respect to the moving platform, wherein the movement module comprises

a memory storing second data representing a template of the target which includes sides of the target corresponding to at least each major side of the target,

a second processor coupled to the camera and the memory, the second processor configured to;

receive the first data and the second data, and

determine that the object is the target if the one or more sides in the first data of the object match a set of sides contained in the second data in the template;

a prediction module coupled to the movement module and configured to estimate future locations of the target based on estimates received from the movement module and movement characteristics of the moving platform; and

a first processor coupled to the movement module and the prediction module, the first processor configured to;

receive present location estimates from the movement module,

receive future location estimates from the prediction module,

store the future location estimates to create a first future location estimate, and

determine the present location of the target based on the present location estimate from the first data calculated by the movement module, the first future location estimate from the prediction module, or both utilizing an auto regressive moving average.

2. The system of claim 1, wherein the prediction module comprises:

a navigation system configured to detect the velocity of the platform and generate its movement characteristics;

a third processor coupled to the navigation system and configured to;

receive the present location estimates,

receive the movement characteristics, and

predict a location of the platform with respect to the target based on the present location estimate and the movement characteristics.

3. The system of claim 1, wherein the first processor comprises a Kalman filter architecture.

4. The system of claim 1, wherein the first processor comprises a weighted-average filter architecture.

5. The system of claim 4, wherein the prediction module is configured to estimate future locations of the target using a vector velocity of the platform.

6. The system of claim 1, wherein the platform is an aircraft and the target is a runway.

7. The system of claim 1, wherein the platform is a motor vehicle.

8. A filter configured to determine a present relative location of a target from a moving platform, comprising:

a single means for passively sensing the target;

means for receiving an estimate of a present location of the moving platform utilizing only the data from the single means for passively sensing the target;

means for receiving an estimate of a future location of the moving platform;

memory configured to store the estimate of the future location of the moving platform; and

means for determining the present location of the target based on the estimate of the present location of the moving platform, the estimate of the future location of the moving platform, or both utilizing an auto regressive moving average.

9. The filter of claim 8, wherein the filter comprises a Kalman filter architecture.

10. The filter of claim 8, wherein the filter comprises a weighted-average filter architecture.

11. The filter of claim 8, wherein the means for determining the present location of the target comprises means for determining which of the estimate of the present location of the moving platform or the estimate of the future location of the moving platform is more accurate.

12. The filter of claim 11, wherein the means for determining which of the estimate of the present location of the moving platform or the estimate of the future location of the moving platform is more accurate comprises means for applying a weighted factor to the more accurate one of the estimate of the present location of the moving platform or the estimate of the future location of the moving platform.

13. A method for determining a present location of a target from a moving platform, the method comprising the steps of:

sensing the target by a single passive sensor;

receiving an estimate of a present location of the moving platform utilizing only data from the single passive sensor;

receiving an estimate of a future location of the moving platform; and

determining the present relative location of the stationary target based on the estimate of the present location of the moving platform, the estimate of the future location of the moving platform, or both utilizing an auto regressive moving average.

14. The method of claim 13, wherein the step of determining the present location of the target comprises the step of determining which of the estimate of the present location of the moving platform or the estimate of the future location of the moving platform is more accurate.

15. The method of claim 13 wherein the step of determining which of the estimate of the present location of the moving platform or the estimate of the future location of the moving platform is more accurate comprises the step of applying a weighted factor to the more accurate one of the estimate of the present location of the moving platform or the estimate of the future location of the moving platform.