【摘要】：基于一維距離像或高分辨距離像(High Range Resolution Profile,HRRP)的艦船目標(biāo)識(shí)別技術(shù)是雷達(dá)數(shù)據(jù)處理領(lǐng)域的一個(gè)重要研究方向。海上艦船作為一種移動(dòng)目標(biāo),其一維距離像所具有的平移敏感性、姿態(tài)敏感性以及幅度敏感性問(wèn)題是該領(lǐng)域的技術(shù)難點(diǎn)。本論文針對(duì)如何提高基于HRRP的艦船目標(biāo)識(shí)別率以及如何搭建一個(gè)實(shí)用型的艦船目標(biāo)識(shí)別平臺(tái)來(lái)展開(kāi)研究,主要工作如下:(1)介紹了該領(lǐng)域的研究背景和意義,并對(duì)一維距離像的特征提取、多特征融合以及分類器設(shè)計(jì)的國(guó)內(nèi)外研究現(xiàn)狀作了簡(jiǎn)單介紹。(2)研究了一維距離像的數(shù)據(jù)預(yù)處理技術(shù)。首先,對(duì)原始HRRP數(shù)據(jù)進(jìn)行低通濾波以降低海雜波背景的噪聲干擾,提高信噪比。然后,對(duì)濾波后的HRRP數(shù)據(jù)進(jìn)行歸一化處理,減少了HRRP的幅度敏感性。最后,通過(guò)估計(jì)船頭和船尾的位置來(lái)提取目標(biāo)區(qū)域,解決了HRRP的平移敏感性問(wèn)題。(3)針對(duì)HRRP的姿態(tài)敏感性問(wèn)題,本論文根據(jù)傳統(tǒng)的特征提取方法,提取多個(gè)具有姿態(tài)不敏感的特征來(lái)進(jìn)行艦船目標(biāo)識(shí)別。為了提高識(shí)別率,本論文提出一種基于緊致性測(cè)度加權(quán)的艦船類型識(shí)別算法,通過(guò)該算法可反映出不同特征在識(shí)別過(guò)程中的權(quán)重差異。另外,本論文對(duì)傳統(tǒng)的基于Fisher準(zhǔn)則的特征選擇方法進(jìn)行改進(jìn),提出了一種基于特征互補(bǔ)性的特征選擇方法,從所提取的特征集中選擇出一個(gè)最優(yōu)特征子集,并通過(guò)實(shí)驗(yàn)證明了該算法可以使用更少的特征得到更高的識(shí)別率。(4)為盡可能的模擬真實(shí)場(chǎng)景下的艦船目標(biāo)識(shí)別過(guò)程,本論文設(shè)計(jì)了一個(gè)集多功能于一體的識(shí)別平臺(tái)。該平臺(tái)實(shí)現(xiàn)的主要功能有:航跡以及HRRP數(shù)據(jù)的接收或發(fā)送、數(shù)據(jù)的實(shí)時(shí)顯示、成像數(shù)據(jù)的處理、數(shù)據(jù)庫(kù)存儲(chǔ)查詢、系統(tǒng)設(shè)置等功能。
[Abstract]:Ship target recognition based on one dimensional range profile or high resolution range profile (High Range Resolution Profile,HRRP) is an important research direction in the field of radar data processing. As a moving target, the translation sensitivity, attitude sensitivity and amplitude sensitivity of one dimensional range profile are the technical difficulties in this field. This paper focuses on how to improve the rate of ship target recognition based on HRRP and how to build a practical platform for ship target recognition. The main work is as follows: (1) the research background and significance of this field are introduced. The feature extraction, multi-feature fusion and classifier design of one-dimensional range profile are briefly introduced. (2) the data preprocessing technology of one-dimensional range profile is studied. Firstly, the original HRRP data are filtered by low pass filter to reduce the noise interference of sea clutter background and improve the signal-to-noise ratio (SNR). Then, the filtered HRRP data is normalized to reduce the amplitude sensitivity of HRRP. Finally, the translation sensitivity of HRRP is solved by estimating the position of bow and stern. (3) aiming at the attitude sensitivity of HRRP, the traditional feature extraction method is used in this paper. A number of pose insensitive features are extracted for ship target recognition. In order to improve the recognition rate, this paper proposes a warship type recognition algorithm based on compactness measure weighting, which can reflect the weight difference of different features in the recognition process. In addition, this paper improves the traditional feature selection method based on Fisher criterion, proposes a feature selection method based on feature complementarity, and selects an optimal feature subset from the extracted feature set. Experiments show that the algorithm can use fewer features to achieve a higher recognition rate. (4) in order to simulate the process of ship target recognition in real scene as much as possible, this paper designs a multi-functional recognition platform. The main functions of the platform are as follows: receiving or sending the track and HRRP data, displaying the data in real time, processing the imaging data, storing and querying the database, setting up the system, etc.
【學(xué)位授予單位】：杭州電子科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：E925;TN957.52

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