Abstract
The effort to detect a target conflicts with the covertness in anti-submarine warfare. The underwater detection rate is extremely low and sound waves are the only detection method unlike the airborne operational environment. The data of an underwater target based on noise levels are more difficult to interpret when the acceleration inputs are included. Hence, the authors propose a complementary algorithm for the tracking problem in an active sonar system. The bearing-range data of the target yield the measurement residuals, and the residuals are used as inputs to the clustering method. The clustering method estimates the acceleration and the noise level. The estimates aid in positional compensation and enhance the tracking performance. The fuzzy c-means clustering is utilised for the clustering and maintains the filter sustainable. Finally, some examples are provided to show the effectiveness of the proposed method.
| Original language | English |
|---|---|
| Pages (from-to) | 1042-1050 |
| Number of pages | 9 |
| Journal | IET Radar, Sonar and Navigation |
| Volume | 8 |
| Issue number | 9 |
| DOIs | |
| Publication status | Published - 2014 Dec 1 |
Fingerprint
All Science Journal Classification (ASJC) codes
- Electrical and Electronic Engineering
Cite this
}
Fuzzy c-means-based intelligent tracking algorithm for an underwater manoeuvring target. / Son, Hyun Seung; Park, Jin Bae; Joo, Young Hoon.
In: IET Radar, Sonar and Navigation, Vol. 8, No. 9, 01.12.2014, p. 1042-1050.Research output: Contribution to journal › Article
TY - JOUR
T1 - Fuzzy c-means-based intelligent tracking algorithm for an underwater manoeuvring target
AU - Son, Hyun Seung
AU - Park, Jin Bae
AU - Joo, Young Hoon
PY - 2014/12/1
Y1 - 2014/12/1
N2 - The effort to detect a target conflicts with the covertness in anti-submarine warfare. The underwater detection rate is extremely low and sound waves are the only detection method unlike the airborne operational environment. The data of an underwater target based on noise levels are more difficult to interpret when the acceleration inputs are included. Hence, the authors propose a complementary algorithm for the tracking problem in an active sonar system. The bearing-range data of the target yield the measurement residuals, and the residuals are used as inputs to the clustering method. The clustering method estimates the acceleration and the noise level. The estimates aid in positional compensation and enhance the tracking performance. The fuzzy c-means clustering is utilised for the clustering and maintains the filter sustainable. Finally, some examples are provided to show the effectiveness of the proposed method.
AB - The effort to detect a target conflicts with the covertness in anti-submarine warfare. The underwater detection rate is extremely low and sound waves are the only detection method unlike the airborne operational environment. The data of an underwater target based on noise levels are more difficult to interpret when the acceleration inputs are included. Hence, the authors propose a complementary algorithm for the tracking problem in an active sonar system. The bearing-range data of the target yield the measurement residuals, and the residuals are used as inputs to the clustering method. The clustering method estimates the acceleration and the noise level. The estimates aid in positional compensation and enhance the tracking performance. The fuzzy c-means clustering is utilised for the clustering and maintains the filter sustainable. Finally, some examples are provided to show the effectiveness of the proposed method.
UR - http://www.scopus.com/inward/record.url?scp=84918581194&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84918581194&partnerID=8YFLogxK
U2 - 10.1049/iet-rsn.2013.0353
DO - 10.1049/iet-rsn.2013.0353
M3 - Article
AN - SCOPUS:84918581194
VL - 8
SP - 1042
EP - 1050
JO - IET Radar, Sonar and Navigation
JF - IET Radar, Sonar and Navigation
SN - 1751-8784
IS - 9
ER -