Patents by Inventor Teresa L. Olson

Teresa L. Olson has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Patent number: 7742620
    Abstract: A method for identifying potential targets as far away as possible is disclosed. In a simple background scene such as a blue sky, a target may be recognized from a relatively long distance, but for some high clutter situations such as mountains and cities, the detection range is severely reduced. The background clutter may also be non-stationary further complicating the detection of a target. To solve these problems, target detection (recognition) of the present invention is based upon temporal fusion (integration) of sensor data using pre-detection or post-detection integration techniques, instead of using the prior art technique of fusing data from only a single time frame. Also disclosed are double-thresholding and reversed-thresholding techniques which further enhance target detection and avoid the shortcomings of the traditional constant false alarm rate (CFAR) thresholding technique.
    Type: Grant
    Filed: March 18, 2004
    Date of Patent: June 22, 2010
    Assignee: Lockhead Martin Corporation
    Inventors: Hai-Wen Chen, Teresa L. Olson, Surachai Sutha
  • Patent number: 7576681
    Abstract: A method and system provide a multi-sensor data fusion system capable of adaptively weighting the contributions from each one of a plurality of sensors using a plurality of data fusion methods. During a predetermined tracking period, the system receives data from each individual sensor and each data fusion method is performed to determine a plurality of reliability functions for the system based on combining each sensor reliability function which are individually weighted based on the S/N (signal-to-noise) ratio for the received data from each sensor, and a comparison of predetermined sensor operation characteristics for each sensor and a best performing (most reliable) sensor. The system may dynamically select to use one or a predetermined combination of the generated reliability functions as the current (best) reliability function which provides a confidence level for the multi-sensor system relating to the correct classification (recognition) of targets and decoys.
    Type: Grant
    Filed: May 16, 2005
    Date of Patent: August 18, 2009
    Assignee: Lockheed Martin Corporation
    Inventors: Hai-Wen Chen, Teresa L. Olson
  • Patent number: 7436884
    Abstract: A data compression system and method provides a best base searching method to determine the best orthogonal basis function for wavelet-based, data compression. A processing device may receive data signals from a source and wavelet-based data compression may be performed on the received data before transmission (to a receiving component) and/or further digital signal processing (DSP) of the data signals. An encoder portion of the processing device performs the data compression using a predetermined algorithm that determines the best orthogonal basis function (base) of the signal transform (used for representing the data signals) by searching a set of bases including (approximately) all orthogonal bases available to provide the minimum number of coefficients for efficient data compression while maintaining a low error rate in reconstructing the original data signals.
    Type: Grant
    Filed: March 25, 2003
    Date of Patent: October 14, 2008
    Assignee: Lockheed Martin Corporation
    Inventors: Hal-Wen Chen, Teresa L. Olson
  • Patent number: 7430303
    Abstract: A method and system detects candidate targets or objects from a viewed scene by simplifying the data, converting the data to gradient magnitude and direction data which is thresholded to simplify the data. Horizontal edges within the data are softened to reduce their masking of adjacent non-horizontal features. One or more target boxes are stepped across the image data and the number of directions of gradient direction data within the box is used to determine the presence of a target. Atmospheric attenuation is compensated. The thresholding used in one embodiment compares the gradient magnitude data to a localized threshold calculated from the local variance of the image gradient magnitude data. Imagery subsets are containing the candidate targets may then be used to detect and identify features and apply a classifier function to screen candidate detections and determine a likely target.
    Type: Grant
    Filed: March 28, 2003
    Date of Patent: September 30, 2008
    Assignee: Lockheed Martin Corporation
    Inventors: Jason Sefcik, Harry C. Lee, Teresa L. Olson
  • Patent number: 7391925
    Abstract: A system and method for estimating noise using measurement based parametric fitting non-uniformity correction is disclosed. Fixed pattern noise (“FPN”) is estimating from an overall noise component within a detection system to enhance candidate target detection and tracking. A sensor in the detection system receives energy, such as radiant flux, that is converted to a digital image. A non-uniformity correction device generates an estimated FPN according to an applicable temperate range and integration time. A memory storing an array of coefficients is accessed to determine the estimated FPN. The valves within the array of coefficients are based on actual FPN measurements that are parametrically fitted.
    Type: Grant
    Filed: December 4, 2003
    Date of Patent: June 24, 2008
    Assignee: Lockheed Martin Missiles & Fire Control
    Inventors: Hai-Wen Chen, Felix M. Fontan, Teresa L. Olson
  • Patent number: 7065465
    Abstract: A multi-sensor data fusion system and method provides adaptive weighting of the contributions from a plurality of sensors in the system using an additive calculation of a sensor reliability function for each sensor. During a predetermined tracking period, data is received from each individual sensor in the system and a sensor reliability function is determined for each sensor based on the SNR (signal-to-noise ratio) for the received data from each sensor. Each sensor reliability function is individually weighted based on the SNR for each sensor and a comparison of predetermined sensor operation characteristics for each sensor and a best performing (most reliable) sensor. Additive calculations are performed on the sensor reliability functions to produce both an absolute and a relative reliability function which provide a confidence level for the multi-sensor system relating to the correct classification (recognition) of targets and decoys.
    Type: Grant
    Filed: March 25, 2003
    Date of Patent: June 20, 2006
    Assignee: Lockheed Martin Corporation
    Inventors: Hai-Wen Chen, Teresa L. Olson
  • Patent number: 6944566
    Abstract: A multi-sensor data fusion system and method provide an additive fusion technique including a modified belief function (algorithm) to adaptively weight the contributions from a plurality of sensors in the system and to produce multiple reliability terms including reliability terms associated with noise for low SNR situations. During a predetermined tracking period, data is received from each individual sensor in the system and a predetermined algorithm is performed to generate sensor reliability functions for each sensor based on each sensor SNR using at least one additional reliability factor associated with noise. Each sensor reliability function may be individually weighted based on the SNR for each sensor and other factors. Additive calculations are performed on the reliability functions to produce at least one system reliability function which provides a confidence level for the multi-sensor system relating to the correct classification (recognition) of desired objects (e.g., targets and decoys).
    Type: Grant
    Filed: March 25, 2003
    Date of Patent: September 13, 2005
    Assignee: Lockheed Martin Corporation
    Inventors: Hai-Wen Chen, Teresa L. Olson
  • Patent number: 6909997
    Abstract: A method and system provide a multi-sensor data fusion system capable of adaptively weighting the contributions from each one of a plurality of sensors using a plurality of data fusion methods. During a predetermined tracking period, the system receives data from each individual sensor and each data fusion method is performed to determine a plurality of reliability functions for the system based on combining each sensor reliability function which are individually weighted based on the S/N (signal-to-noise) ratio for the received data from each sensor, and a comparison of predetermined sensor operation characteristics for each sensor and a best performing (most reliable) sensor. The system may dynamically select to use one or a predetermined combination of the generated reliability functions as the current (best) reliability function which provides a confidence level for the multi-sensor system relating to the correct classification (recognition) of targets and decoys.
    Type: Grant
    Filed: March 25, 2003
    Date of Patent: June 21, 2005
    Assignee: Lockheed Martin Corporation
    Inventors: Hai-Wen Chen, Teresa L. Olson
  • Patent number: 6901152
    Abstract: An automated method of, and computer software and apparatus for, classifying objects visually into one of a plurality of object types comprising receiving a still image including an object, bounding the object within the image, dividing the bound portion of the image into a plurality of profile sections, performing a transform on each of the profile sections selected from discrete cosine transforms and discrete Fourier transforms, and executing a Bayes classifier function to segregate the object into one of the object types.
    Type: Grant
    Filed: April 2, 2003
    Date of Patent: May 31, 2005
    Assignee: Lockheed Martin Corporation
    Inventors: Harry C. Lee, Johnnie J. Sanders, Teresa L. Olson
  • Patent number: 6897446
    Abstract: A target detection and tracking system provides dynamic changing of the integration time (IT) for the system IR sensor within a discrete set of values to maintain a high sensor sensitivity. The system changes the integration time to the same or a different sensor integration time within the discrete set based on the image data output from the sensor satisfying pre-determined system parameter thresholds. The system includes an IT-related saturation prediction function allowing the system to avoid unnecessary system saturation when determining whether an IT change should be made. The tracking portion of the system provides tracking feedback allowing target objects with a low sensor signature to be detected without being obscured by nearby uninterested objects that produce system saturation.
    Type: Grant
    Filed: March 25, 2003
    Date of Patent: May 24, 2005
    Assignee: Lockheed Martin Corporation
    Inventors: Hai-Wen Chen, Steven R. Frey, Jr., Teresa L. Olson
  • Publication number: 20040197010
    Abstract: An automated method of, and computer software and apparatus for, classifying objects visually into one of a plurality of object types comprising receiving a still image including an object, bounding the object within the image, dividing the bound portion of the image into a plurality of profile sections, performing a transform on each of the profile sections selected from discrete cosine transforms and discrete Fourier transforms, and executing a Bayes classifier function to segregate the object into one of the object types.
    Type: Application
    Filed: April 2, 2003
    Publication date: October 7, 2004
    Inventors: Harry C. Lee, Johnnie J. Sanders, Teresa L. Olson
  • Publication number: 20030191610
    Abstract: A multi-sensor data fusion system and method provide an additive fusion technique including a modified belief function (algorithm) to adaptively weight the contributions from a plurality of sensors in the system and to produce multiple reliability terms including reliability terms associated with noise for low SNR situations. During a predetermined tracking period, data is received from each individual sensor in the system and a predetermined algorithm is performed to generate sensor reliability functions for each sensor based on each sensor SNR using at least one additional reliability factor associated with noise. Each sensor reliability function may be individually weighted based on the SNR for each sensor and other factors. Additive calculations are performed on the reliability functions to produce at least one system reliability function which provides a confidence level for the multi-sensor system relating to the correct classification (recognition) of desired objects (e.g., targets and decoys).
    Type: Application
    Filed: March 25, 2003
    Publication date: October 9, 2003
    Inventors: Hai-Wen Chen, Teresa L. Olson
  • Publication number: 20030185247
    Abstract: A data compression system and method provides a best base searching method to determine the best orthogonal basis function for wavelet-based, data compression. A processing device may receive data signals from a source and wavelet-based data compression may be performed on the received data before transmission (to a receiving component) and/or further digital signal processing (DSP) of the data signals. An encoder portion of the processing device performs the data compression using a predetermined algorithm that determines the best orthogonal basis function (base) of the signal transform (used for representing the data signals) by searching a set of bases including (approximately) all orthogonal bases available to provide the minimum number of coefficients for efficient data compression while maintaining a low error rate in reconstructing the original data signals.
    Type: Application
    Filed: March 25, 2003
    Publication date: October 2, 2003
    Inventors: Hal-Wen Chen, Teresa L. Olson
  • Publication number: 20030185420
    Abstract: A method and system detects candidate targets or objects from a viewed scene by simplifying the data, converting the data to gradient magnitude and direction data which is thresholded to simplify the data. Horizontal edges within the data are softened to reduce their masking of adjacent non-horizontal features. One or more target boxes are stepped across the image data and the number of directions of gradient direction data within the box is used to determine the presence of a target. Atmospheric attenuation is compensated. The thresholding used in one embodiment compares the gradient magnitude data to a localized threshold calculated from the local variance of the image gradient magnitude data. Imagery subsets are containing the candidate targets may then be used to detect and identify features and apply a classifier function to screen candidate detections and determine a likely target.
    Type: Application
    Filed: March 28, 2003
    Publication date: October 2, 2003
    Inventors: Jason Sefcik, Harry C. Lee, Teresa L. Olson
  • Publication number: 20030186663
    Abstract: A multi-sensor data fusion system and method provides adaptive weighting of the contributions from a plurality of sensors in the system using an additive calculation of a sensor reliability function for each sensor. During a predetermined tracking period, data is received from each individual sensor in the system and a sensor reliability function is determined for each sensor based on the SNR (signal-to-noise ratio) for the received data from each sensor. Each sensor reliability function is individually weighted based on the SNR for each sensor and a comparison of predetermined sensor operation characteristics for each sensor and a best performing (most reliable) sensor. Additive calculations are performed on the sensor reliability functions to produce both an absolute and a relative reliability function which provide a confidence level for the multi-sensor system relating to the correct classification (recognition) of targets and decoys.
    Type: Application
    Filed: March 25, 2003
    Publication date: October 2, 2003
    Inventors: Hai-Wen Chen, Teresa L. Olson
  • Publication number: 20030184468
    Abstract: A method and system provide a multi-sensor data fusion system capable of adaptively weighting the contributions from each one of a plurality of sensors using a plurality of data fusion methods. During a predetermined tracking period, the system receives data from each individual sensor and each data fusion method is performed to determine a plurality of reliability functions for the system based on combining each sensor reliability function which are individually weighted based on the S/N (signal-to-noise) ratio for the received data from each sensor, and a comparison of predetermined sensor operation characteristics for each sensor and a best performing (most reliable) sensor. The system may dynamically select to use one or a predetermined combination of the generated reliability functions as the current (best) reliability function which provides a confidence level for the multi-sensor system relating to the correct classification (recognition) of targets and decoys.
    Type: Application
    Filed: March 25, 2003
    Publication date: October 2, 2003
    Inventors: Hai-Wen Chen, Teresa L. Olson
  • Publication number: 20030183765
    Abstract: A target detection and tracking system provides dynamic changing of the integration time (IT) for the system IR sensor within a discrete set of values to maintain a high sensor sensitivity. The system changes the integration time to the same or a different sensor integration time within the discrete set based on the image data output from the sensor satisfying pre-determined system parameter thresholds. The system includes an IT-related saturation prediction function allowing the system to avoid unnecessary system saturation when determining whether an IT change should be made. The tracking portion of the system provides tracking feedback allowing target objects with a low sensor signature to be detected without being obscured by nearby uninterested objects that produce system saturation.
    Type: Application
    Filed: March 25, 2003
    Publication date: October 2, 2003
    Applicant: LOCKHEED MARTIN CORPORATION
    Inventors: Hai-Wen Chen, Steven R. Frey, Teresa L. Olson