IL130592A - Clutter rejection using adaptive estimation of a clutter probability density function - Google Patents

Clutter rejection using adaptive estimation of a clutter probability density function

Info

Publication number
IL130592A
IL130592A IL13059298A IL13059298A IL130592A IL 130592 A IL130592 A IL 130592A IL 13059298 A IL13059298 A IL 13059298A IL 13059298 A IL13059298 A IL 13059298A IL 130592 A IL130592 A IL 130592A
Authority
IL
Israel
Prior art keywords
target
track
feature
image
class
Prior art date
Application number
IL13059298A
Other languages
English (en)
Other versions
IL130592A0 (en
Original Assignee
Raytheon Co
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Raytheon Co filed Critical Raytheon Co
Publication of IL130592A0 publication Critical patent/IL130592A0/xx
Publication of IL130592A publication Critical patent/IL130592A/en

Links

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S3/00—Direction-finders for determining the direction from which infrasonic, sonic, ultrasonic, or electromagnetic waves, or particle emission, not having a directional significance, are being received
    • G01S3/78—Direction-finders for determining the direction from which infrasonic, sonic, ultrasonic, or electromagnetic waves, or particle emission, not having a directional significance, are being received using electromagnetic waves other than radio waves
    • G01S3/782—Systems for determining direction or deviation from predetermined direction
    • G01S3/785—Systems for determining direction or deviation from predetermined direction using adjustment of orientation of directivity characteristics of a detector or detector system to give a desired condition of signal derived from that detector or detector system
    • G01S3/786—Systems for determining direction or deviation from predetermined direction using adjustment of orientation of directivity characteristics of a detector or detector system to give a desired condition of signal derived from that detector or detector system the desired condition being maintained automatically
    • G01S3/7864—T.V. type tracking systems
    • G01S3/7865—T.V. type tracking systems using correlation of the live video image with a stored image
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/24—Classification techniques
    • G06F18/241—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches
    • G06F18/2415—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches based on parametric or probabilistic models, e.g. based on likelihood ratio or false acceptance rate versus a false rejection rate
    • G06F18/24155—Bayesian classification
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/20—Image preprocessing
    • G06V10/255—Detecting or recognising potential candidate objects based on visual cues, e.g. shapes
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/764—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Multimedia (AREA)
  • Data Mining & Analysis (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Evolutionary Computation (AREA)
  • Artificial Intelligence (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Electromagnetism (AREA)
  • Databases & Information Systems (AREA)
  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Medical Informatics (AREA)
  • Software Systems (AREA)
  • Remote Sensing (AREA)
  • Probability & Statistics with Applications (AREA)
  • Computing Systems (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Evolutionary Biology (AREA)
  • General Engineering & Computer Science (AREA)
  • Radar Systems Or Details Thereof (AREA)
  • Analysing Materials By The Use Of Radiation (AREA)
  • Image Processing (AREA)
IL13059298A 1997-10-30 1998-10-22 Clutter rejection using adaptive estimation of a clutter probability density function IL130592A (en)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US08/961,377 US5909190A (en) 1997-10-30 1997-10-30 Clutter rejection using adaptive estimation of clutter probability density function
PCT/US1998/022541 WO1999026079A1 (en) 1997-10-30 1998-10-22 Clutter rejection using adaptive estimation of a clutter probability density function

Publications (2)

Publication Number Publication Date
IL130592A0 IL130592A0 (en) 2000-06-01
IL130592A true IL130592A (en) 2002-09-12

Family

ID=25504399

Family Applications (1)

Application Number Title Priority Date Filing Date
IL13059298A IL130592A (en) 1997-10-30 1998-10-22 Clutter rejection using adaptive estimation of a clutter probability density function

Country Status (9)

Country Link
US (1) US5909190A (de)
EP (1) EP0948749B1 (de)
JP (1) JP3207862B2 (de)
DE (1) DE69809533T2 (de)
DK (1) DK0948749T3 (de)
IL (1) IL130592A (de)
TR (1) TR199901523T1 (de)
TW (1) TW434414B (de)
WO (1) WO1999026079A1 (de)

Families Citing this family (18)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6466894B2 (en) 1998-06-18 2002-10-15 Nec Corporation Device, method, and medium for predicting a probability of an occurrence of a data
US6397234B1 (en) * 1999-08-20 2002-05-28 The United States Of America As Represented By The Secretary Of The Navy System and apparatus for the detection of randomness in time series distributions made up of sparse data sets
US6377206B1 (en) 2000-04-06 2002-04-23 Lockheed Martin Corporation Method for clutter rejection in digital imagery
US7277558B2 (en) * 2001-11-27 2007-10-02 Lockheed Martin Corporation Method and system for estimating the position of moving objects in images
US7561971B2 (en) * 2002-03-28 2009-07-14 Exagen Diagnostics, Inc. Methods and devices relating to estimating classifier performance
US6943724B1 (en) 2002-10-30 2005-09-13 Lockheed Martin Corporation Identification and tracking of moving objects in detected synthetic aperture imagery
US6864828B1 (en) 2003-02-18 2005-03-08 Lockheed Martin Corporation Method and apparatus for collection and processing of interferometric synthetic aperture radar data
GB0502369D0 (en) * 2005-02-04 2005-03-16 British Telecomm Classifying an object in a video frame
EP1859411B1 (de) * 2005-03-17 2010-11-03 BRITISH TELECOMMUNICATIONS public limited company Verfolgen von objekten in einer videosequenz
US7567203B2 (en) * 2005-04-11 2009-07-28 Raytheon Canada Limited Classification system for radar and sonar applications
US7315485B1 (en) * 2005-12-20 2008-01-01 United States Of America As Represented By The Secretary Of The Navy System and method for target classification and clutter rejection in low-resolution imagery
US20070253625A1 (en) * 2006-04-28 2007-11-01 Bbnt Solutions Llc Method for building robust algorithms that classify objects using high-resolution radar signals
WO2007144570A1 (en) * 2006-06-13 2007-12-21 Bae Systems Plc Improvements relating to target tracking
US8466398B2 (en) * 2009-11-30 2013-06-18 Ioannis BOULTIS Diffraction fields for guiding an object to a target
CN107330441B (zh) * 2017-05-26 2019-07-09 天津大学 火焰图像前景提取算法
CN111624571B (zh) * 2020-05-19 2022-10-28 哈尔滨工业大学 基于自适应紧框架的非均匀Weibull背景统计分布参数估计方法
US11222232B1 (en) * 2020-06-19 2022-01-11 Nvidia Corporation Using temporal filters for automated real-time classification
US11978266B2 (en) 2020-10-21 2024-05-07 Nvidia Corporation Occupant attentiveness and cognitive load monitoring for autonomous and semi-autonomous driving applications

Family Cites Families (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4739401A (en) 1985-01-25 1988-04-19 Hughes Aircraft Company Target acquisition system and method
US5341142A (en) 1987-07-24 1994-08-23 Northrop Grumman Corporation Target acquisition and tracking system
US5065444A (en) 1988-02-08 1991-11-12 Northrop Corporation Streak removal filtering method and apparatus
US4937878A (en) * 1988-08-08 1990-06-26 Hughes Aircraft Company Signal processing for autonomous acquisition of objects in cluttered background
US5612928A (en) * 1992-05-28 1997-03-18 Northrop Grumman Corporation Method and apparatus for classifying objects in sonar images
JPH09145829A (ja) * 1995-11-28 1997-06-06 Mitsubishi Electric Corp レーダ信号処理装置

Also Published As

Publication number Publication date
TR199901523T1 (xx) 2000-10-23
IL130592A0 (en) 2000-06-01
WO1999026079A1 (en) 1999-05-27
TW434414B (en) 2001-05-16
EP0948749A1 (de) 1999-10-13
DE69809533D1 (de) 2003-01-02
DK0948749T3 (da) 2003-02-17
US5909190A (en) 1999-06-01
JP2000508429A (ja) 2000-07-04
EP0948749B1 (de) 2002-11-20
JP3207862B2 (ja) 2001-09-10
DE69809533T2 (de) 2003-09-04

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Legal Events

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