基于空時融合隱馬爾科夫模型的艦艇編隊目標(biāo)識別方法
doi: 10.11999/JEIT140589
基金項目:
上海市科學(xué)技術(shù)委員會資助課題(11DZ2260800)和省部級基金資助課題
Ship Formation Target Recognition Based on Spatial and Temporal Fusion Hidden Markov Model
-
摘要: 基于末制導(dǎo)雷達搜索艦艇編隊目標(biāo)時獲得的目標(biāo)大角域高分辨距離像(HRRP)信息，該文建立了描述單個HRRP樣本內(nèi)向量之間統(tǒng)計關(guān)系的各態(tài)歷經(jīng)空間隱馬爾可夫模型(SHMM)和描述HRRP樣本之間統(tǒng)計關(guān)系的從左到右時間隱馬爾可夫模型(THMM)。與對一類目標(biāo)全方位角訓(xùn)練數(shù)據(jù)只建立一個THMM模型的方法相比，該方法充分利用目標(biāo)的大角域HRRP信息，提高了識別性能。通過對5類艦船目標(biāo)的仿真和3類民用船只的外場實測數(shù)據(jù)分析表明該方法的有效性。
-
關(guān)鍵詞:
- 雷達高分辨距離像 /
- 空間隱馬爾可夫模型 /
- 時間隱馬爾可夫模型 /
- 編隊目標(biāo)識別
Abstract: Based on the target large angle domain High Resolution Range Profile (HRRP) information of the ship formation obtained by the terminal guidance radar during its search phase, this study establishes an ergodic Spatial Hidden Markov Model (SHMM) which describes statistical relationship between the vectors in a single HRRP sample and a left to right Temporal HMM (THMM) which describes statistical relationship between HRRP samples. In comparison with the method that it only establishes a THMM model with the training data of all-round angle of one target, the proposed method makes full use of the target HRRP information of large angle domain and can improve the recognition performance. Through the simulation of the five types of ship target and the field measured data analysis of three kinds of civilian vessels show that the effectiveness of the proposed method. -
計量
- 文章訪問數(shù): 2165
- HTML全文瀏覽量: 153
- PDF下載量: 650
- 被引次數(shù): 0
下載:
