Environment detection with Kalman filter for CFAR detectors

Seong Won Hong; Dong Seog Han

doi:10.1109/APCC.2012.6388245

Environment detection with Kalman filter for CFAR detectors

Seong Won Hong, Dong Seog Han

School of Electronics Engineering

Kyungpook National University

Research output: Contribution to conference › Paper › peer-review

1 Scopus citations

Abstract

The constant false alarm rate (CFAR) detector is a representative detection method for radar systems. Its detection performance is severely depending on clutter environments such as homogeneous and non-homogeneous. Depending on the environment, we have to adopt different CFAR algorithms. Thus, in this paper, we propose the environment detection algorithm using the Kalman filter. By using this algorithm, we can select the optimal CFAR detector for each environment.

Original language	English
Pages	509-510
Number of pages	2
DOIs	https://doi.org/10.1109/APCC.2012.6388245
State	Published - 2012
Event	18th Asia-Pacific Conference on Communications: "Green and Smart Communications for IT Innovation", APCC 2012 - Jeju Island, Korea, Republic of Duration: 15 Oct 2012 → 17 Oct 2012

Conference

Conference	18th Asia-Pacific Conference on Communications: "Green and Smart Communications for IT Innovation", APCC 2012
Country/Territory	Korea, Republic of
City	Jeju Island
Period	15/10/12 → 17/10/12

Keywords

clutter-edge
constant false alarm rate
detection
Kalman filter
multiple targets

Access to Document

10.1109/APCC.2012.6388245

Cite this

@conference{f654e5702aa2405cac610bb138a80237,

title = "Environment detection with Kalman filter for CFAR detectors",

abstract = "The constant false alarm rate (CFAR) detector is a representative detection method for radar systems. Its detection performance is severely depending on clutter environments such as homogeneous and non-homogeneous. Depending on the environment, we have to adopt different CFAR algorithms. Thus, in this paper, we propose the environment detection algorithm using the Kalman filter. By using this algorithm, we can select the optimal CFAR detector for each environment.",

keywords = "clutter-edge, constant false alarm rate, detection, Kalman filter, multiple targets",

author = "Hong, {Seong Won} and Han, {Dong Seog}",

year = "2012",

doi = "10.1109/APCC.2012.6388245",

language = "English",

pages = "509--510",

note = "18th Asia-Pacific Conference on Communications: {"}Green and Smart Communications for IT Innovation{"}, APCC 2012 ; Conference date: 15-10-2012 Through 17-10-2012",

}

TY - CONF

T1 - Environment detection with Kalman filter for CFAR detectors

AU - Hong, Seong Won

AU - Han, Dong Seog

PY - 2012

Y1 - 2012

N2 - The constant false alarm rate (CFAR) detector is a representative detection method for radar systems. Its detection performance is severely depending on clutter environments such as homogeneous and non-homogeneous. Depending on the environment, we have to adopt different CFAR algorithms. Thus, in this paper, we propose the environment detection algorithm using the Kalman filter. By using this algorithm, we can select the optimal CFAR detector for each environment.

AB - The constant false alarm rate (CFAR) detector is a representative detection method for radar systems. Its detection performance is severely depending on clutter environments such as homogeneous and non-homogeneous. Depending on the environment, we have to adopt different CFAR algorithms. Thus, in this paper, we propose the environment detection algorithm using the Kalman filter. By using this algorithm, we can select the optimal CFAR detector for each environment.

KW - clutter-edge

KW - constant false alarm rate

KW - detection

KW - Kalman filter

KW - multiple targets

UR - http://www.scopus.com/inward/record.url?scp=84872535312&partnerID=8YFLogxK

U2 - 10.1109/APCC.2012.6388245

DO - 10.1109/APCC.2012.6388245

M3 - Paper

AN - SCOPUS:84872535312

SP - 509

EP - 510

T2 - 18th Asia-Pacific Conference on Communications: "Green and Smart Communications for IT Innovation", APCC 2012

Y2 - 15 October 2012 through 17 October 2012

ER -

Environment detection with Kalman filter for CFAR detectors

Abstract

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Cite this