NDLI: Sound and dynamics of targets — Fusion technologies in radar target classification

Content Provider	IEEE Xplore Digital Library
Author	Kouemou, G. Neumann, C. Opitz, F.
Copyright Year	2008
Description	Author affiliation: EADS Deutschland GmbH, Ulm (Kouemou, G.; Neumann, C.; Opitz, F.)
Abstract	The challenge of modern sensor systems is besides the tracking of targets more and more their classification. The knowledge of the target class has significant influence on the identification, threat evaluation and weapon assignment process of large systems. Especially, considering new types of threats in anti asymmetric warfare the knowledge of a target class has an important drawback. Also the target class is used to optimize track and resource management of todaypsilas agile sensor systems. A technology is presented that fuses different classifiers to decide between persons, tracked vehicles, wheeled vehicles, helicopters, propeller aircrafts and clutter for a 2 dimensional, electronically scanned radar system. A first classifier analyses the Doppler sound of the target to decide its target class. Therefore, a cepstrum based feature extractor and a hidden Markov model (HMM) is applied. Similar to techniques that have been well proven in speech and image recognition, the time-varying nature of radar Doppler data is exploited. A second type of classifier extracts dynamic features of the target found by the underlying target tracking methodology. Through a fusion of these classifiers a highly reliable classification result is established.
Starting Page	1
Ending Page	7
File Size	689918
Page Count	7
File Format	PDF
ISBN	9783800730926
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-06-30
Publisher Place	Germany
Access Restriction	Subscribed
Rights Holder	ISIF (Intl Society of Information Fusion)
Subject Keyword	Radar tracking Hidden Markov models Doppler effect Target tracking Vehicles Bayesian methods Support vector machine classification
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

A robust Doppler classification technique based on hidden Markov models

Naïve Bayesian radar micro-doppler recognition

Support Vector Machine based micro-Doppler signature classification of ground targets

Support Vector Machine based micro-Doppler signature classification of ground targets

Exploitation of track accuracy information in fusion technologies for radar target classification using Dempster-Shafer Rules

Impact of Wavelet based signal processing methods in radar classification systems using Hidden Markov Models

Multiframe Bayesian tracking of cluttered targets with random motion

Radar target classification in littoral environment with HMMs combined with a track based classifier

Data fusion algorithms for sea target tracking using coastal radar model

Sound and dynamics of targets — Fusion technologies in radar target classification

Similar Documents

A robust Doppler classification technique based on hidden Markov models

Naïve Bayesian radar micro-doppler recognition

Support Vector Machine based micro-Doppler signature classification of ground targets

Support Vector Machine based micro-Doppler signature classification of ground targets

Exploitation of track accuracy information in fusion technologies for radar target classification using Dempster-Shafer Rules

Impact of Wavelet based signal processing methods in radar classification systems using Hidden Markov Models

Multiframe Bayesian tracking of cluttered targets with random motion

Radar target classification in littoral environment with HMMs combined with a track based classifier

Data fusion algorithms for sea target tracking using coastal radar model

Sound and dynamics of targets — Fusion technologies in radar target classification