對(duì)海雷達(dá)目標(biāo)識(shí)別中全極化HRRP的特征提取與選擇

范學(xué)滿; 胡生亮; 賀靜波

doi:10.11999/JEIT160722

對(duì)海雷達(dá)目標(biāo)識(shí)別中全極化HRRP的特征提取與選擇

doi: 10.11999/JEIT160722

基金項(xiàng)目:

國(guó)家自然科學(xué)基金(61401493)，國(guó)家部委基金(9140A01010415JB11002)

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- 文章訪問(wèn)數(shù): 1735
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- 被引次數(shù): 0
出版歷程
- 收稿日期: 2016-07-07
- 修回日期: 2016-11-01
- 刊出日期: 2016-12-19

Feature Extraction and Selection of Full Polarization HRRP in Target Recognition Process of Maritime Surveillance Radar

Funds:

The National Natural Science Foundation of China (61401493), The National Ministries Foundation of China (9140A01010415JB11002)

摘要

摘要: 充分、有效地利用目標(biāo)全極化HRRP的特征信息是提高對(duì)海雷達(dá)目標(biāo)識(shí)別率的研究熱點(diǎn)之一。該文利用CST軟件仿真建立了7類海上目標(biāo)在不同方位角下的全極化HRRP數(shù)據(jù)庫(kù)。在此基礎(chǔ)上，提取了4類共39個(gè)特征。提出一種基于歸一化互信息(NMI)并利用模擬退火(SA)算法進(jìn)行優(yōu)化的全局最優(yōu)特征選擇算法，并命名為NMI-SA?；贖RRP數(shù)據(jù)集以及9個(gè)UCI數(shù)據(jù)集，利用k-近鄰分類器將該算法與另外3種常用的特征選擇算法進(jìn)行對(duì)比，結(jié)果表明新算法選擇的特征具有良好的可分性和較低的冗余度，最終用于分類時(shí)的正確率總體優(yōu)于其余3種算法。最后，用該算法對(duì)全極化HRRP的39個(gè)特征進(jìn)行重點(diǎn)分析，選擇出25個(gè)辨別力強(qiáng)、冗余度低的特征。
- 全極化HRRP /
- 特征提取 /
- 特征選擇 /
- 互信息 /
- 模擬退火
Abstract: Making full and effective use of target polarization information from High Resolution Range Profile (HRRP) is a hot issue for improving the recognition performance of maritime surveillance radar. A HRRP database with seven maritime targets classes from various aspect angles is established, on which thirty-nine features from four categories are defined. A novel feature selection method based on the Normalized Mutual Information (NMI) and Simulated Annealing (SA) algorithm is presented, named as NMI-SA. The effectiveness of the NMI-SA is proved by comparison with three other methods using HRRP dataset and eight from UCI machine learning repository. Finally, the NMI-SA is applied to the HRRP dataset to find twenty-five high discriminant and low redundancy features.
- Fully polarized HRRP /
- Feature extraction /
- Feature selection /
- Mutual information /
- Simulated annealing

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