Radar target recognition of maximum posterior probability based on time-series

Dequan Zhou; Guosui Liu; Guangming Sun; Yunhong Wang

Radar target recognition of maximum posterior probability based on time-series

Dequan Zhou^*
, Guosui Liu
, Guangming Sun
, Yunhong Wang

^*Corresponding author for this work

Nanjing University of Science and Technology

Research output: Contribution to journal › Article › peer-review

1 Scopus citations

Abstract

The characteristics of high resolution radar (HRR) profiles were analyzed. An approach of obtaining stationary vectors was proposed. Partition algorithm presented by Vassilios Petridis, which was used to classify time-series, was modified to satisfy multidimensional time-series. Modified partition algorithm was applied to recognize HRR targets. Primary simulation results show that approaches discussed above have good prospects in the field of radar targets recognition.

Original language	English
Pages (from-to)	369-374
Number of pages	6
Journal	Hongwai Yu Haomibo Xuebao/Journal of Infrared and Millimeter Waves
Volume	16
Issue number	5
State	Published - Oct 1997
Externally published	Yes

Cite this

@article{2865ab3d93704c58b270421dc96672f0,

title = "Radar target recognition of maximum posterior probability based on time-series",

abstract = "The characteristics of high resolution radar (HRR) profiles were analyzed. An approach of obtaining stationary vectors was proposed. Partition algorithm presented by Vassilios Petridis, which was used to classify time-series, was modified to satisfy multidimensional time-series. Modified partition algorithm was applied to recognize HRR targets. Primary simulation results show that approaches discussed above have good prospects in the field of radar targets recognition.",

author = "Dequan Zhou and Guosui Liu and Guangming Sun and Yunhong Wang",

year = "1997",

month = oct,

language = "英语",

volume = "16",

pages = "369--374",

journal = "Hongwai Yu Haomibo Xuebao/Journal of Infrared and Millimeter Waves",

issn = "1001-9014",

publisher = "Chinese Optical Society",

number = "5",

}

TY - JOUR

T1 - Radar target recognition of maximum posterior probability based on time-series

AU - Zhou, Dequan

AU - Liu, Guosui

AU - Sun, Guangming

AU - Wang, Yunhong

PY - 1997/10

Y1 - 1997/10

N2 - The characteristics of high resolution radar (HRR) profiles were analyzed. An approach of obtaining stationary vectors was proposed. Partition algorithm presented by Vassilios Petridis, which was used to classify time-series, was modified to satisfy multidimensional time-series. Modified partition algorithm was applied to recognize HRR targets. Primary simulation results show that approaches discussed above have good prospects in the field of radar targets recognition.

AB - The characteristics of high resolution radar (HRR) profiles were analyzed. An approach of obtaining stationary vectors was proposed. Partition algorithm presented by Vassilios Petridis, which was used to classify time-series, was modified to satisfy multidimensional time-series. Modified partition algorithm was applied to recognize HRR targets. Primary simulation results show that approaches discussed above have good prospects in the field of radar targets recognition.

UR - https://www.scopus.com/pages/publications/0031247614

M3 - 文章

AN - SCOPUS:0031247614

SN - 1001-9014

VL - 16

SP - 369

EP - 374

JO - Hongwai Yu Haomibo Xuebao/Journal of Infrared and Millimeter Waves

JF - Hongwai Yu Haomibo Xuebao/Journal of Infrared and Millimeter Waves

IS - 5

ER -

Radar target recognition of maximum posterior probability based on time-series

Abstract

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