Radar Target Recognition Based on Semiparametric Density Estimation of SLC
In order to solve the problem of the decline of accuracy when using the nonparametric method—Stochastic Learning of the Cumulative (SLC) to estimate the density of High-Resolution Range Profile (HRRP) in radar target recognition under the condition that the samples are not enough, a radar target rec...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
China Science Publishing & Media Ltd. (CSPM)
2012-12-01
|
| Series: | Leida xuebao |
| Subjects: | |
| Online Access: | http://radars.ie.ac.cn/EN/abstract/abstract63.shtml# |
| _version_ | 1797426418052759552 |
|---|---|
| author | Cui Shan-shan Zhou Jian-jiang Zhu Jie-hao |
| author_facet | Cui Shan-shan Zhou Jian-jiang Zhu Jie-hao |
| author_sort | Cui Shan-shan |
| collection | DOAJ |
| description | In order to solve the problem of the decline of accuracy when using the nonparametric method—Stochastic Learning of the Cumulative (SLC) to estimate the density of High-Resolution Range Profile (HRRP) in radar target recognition under the condition that the samples are not enough, a radar target recognition approach based on the semiparametric density estimation of SLC is proposed in this paper. This method has the ability to make use of empirical knowledge which is known as the approximate Gamma distribution of amplitudes in each HRRP range cells, and the Gamma density estimate is then corrected by multiplying with SLC of a correction factor. Obviously, both advantages of parametric method and nonparametric method of SLC are merged in the semiparametric density estimation of SLC. Simulation results based on the HRRP dataset of five aircraft models demonstrate the effectiveness of the proposed approach. |
| first_indexed | 2024-03-09T08:30:56Z |
| format | Article |
| id | doaj.art-9cbddf85a8a74e14948109b403e5d1be |
| institution | Directory Open Access Journal |
| issn | 2095-283X 2095-283X |
| language | English |
| last_indexed | 2024-03-09T08:30:56Z |
| publishDate | 2012-12-01 |
| publisher | China Science Publishing & Media Ltd. (CSPM) |
| record_format | Article |
| series | Leida xuebao |
| spelling | doaj.art-9cbddf85a8a74e14948109b403e5d1be2023-12-02T20:14:57ZengChina Science Publishing & Media Ltd. (CSPM)Leida xuebao2095-283X2095-283X2012-12-011441441910.3724/SP.J.1300.2012.20097Radar Target Recognition Based on Semiparametric Density Estimation of SLCCui Shan-shan0Zhou Jian-jiang1Zhu Jie-hao2College of Electronic and Information Engineering, Nanjing University of Aeronautics and AstronauticsCollege of Electronic and Information Engineering, Nanjing University of Aeronautics and AstronauticsCollege of Electronic and Information Engineering, Nanjing University of Aeronautics and AstronauticsIn order to solve the problem of the decline of accuracy when using the nonparametric method—Stochastic Learning of the Cumulative (SLC) to estimate the density of High-Resolution Range Profile (HRRP) in radar target recognition under the condition that the samples are not enough, a radar target recognition approach based on the semiparametric density estimation of SLC is proposed in this paper. This method has the ability to make use of empirical knowledge which is known as the approximate Gamma distribution of amplitudes in each HRRP range cells, and the Gamma density estimate is then corrected by multiplying with SLC of a correction factor. Obviously, both advantages of parametric method and nonparametric method of SLC are merged in the semiparametric density estimation of SLC. Simulation results based on the HRRP dataset of five aircraft models demonstrate the effectiveness of the proposed approach.http://radars.ie.ac.cn/EN/abstract/abstract63.shtml#Radar target recognitionHigh-Resolution Range Profile (HRRP)Density estimationSemiparametric density estimation of SLC (Stochastic Learning of the Cumulative) |
| spellingShingle | Cui Shan-shan Zhou Jian-jiang Zhu Jie-hao Radar Target Recognition Based on Semiparametric Density Estimation of SLC Leida xuebao Radar target recognition High-Resolution Range Profile (HRRP) Density estimation Semiparametric density estimation of SLC (Stochastic Learning of the Cumulative) |
| title | Radar Target Recognition Based on Semiparametric Density Estimation of SLC |
| title_full | Radar Target Recognition Based on Semiparametric Density Estimation of SLC |
| title_fullStr | Radar Target Recognition Based on Semiparametric Density Estimation of SLC |
| title_full_unstemmed | Radar Target Recognition Based on Semiparametric Density Estimation of SLC |
| title_short | Radar Target Recognition Based on Semiparametric Density Estimation of SLC |
| title_sort | radar target recognition based on semiparametric density estimation of slc |
| topic | Radar target recognition High-Resolution Range Profile (HRRP) Density estimation Semiparametric density estimation of SLC (Stochastic Learning of the Cumulative) |
| url | http://radars.ie.ac.cn/EN/abstract/abstract63.shtml# |
| work_keys_str_mv | AT cuishanshan radartargetrecognitionbasedonsemiparametricdensityestimationofslc AT zhoujianjiang radartargetrecognitionbasedonsemiparametricdensityestimationofslc AT zhujiehao radartargetrecognitionbasedonsemiparametricdensityestimationofslc |