【摘要】：為了提高紅外小目標(biāo)探測能力，本文以地球靜止軌道凝視探測器對地探測為應(yīng)用背景，提出了兩種對小目標(biāo)進行探測的算法：三維匹配濾波算法和基于投影算法的目標(biāo)檢測方法。針對動平臺固有抖動性，凝視探測器拍攝到的序列圖像中目標(biāo)關(guān)聯(lián)性低這一問題，提出一種新的抖動補償算法。本文的主要研究工作如下： （1）分析了紅外小目標(biāo)圖像特性，給出了算法仿真輸入的理論依據(jù)； （2）根據(jù)紅外云圖的背景特性，采用最小二乘法原理構(gòu)建了基于灰度的背景模型，以用來對序列圖像的抖動量進行估計，并對序列圖像配準(zhǔn)； （3）利用最大信噪比原則和柯西—施瓦茨不等式推導(dǎo)了三維匹配濾波器的一般數(shù)學(xué)公式。對于序列圖像，給出了三維匹配濾波算法的一般流程并且進行了算法仿真，有效地驗證了三維匹配濾波算法對于低信噪比小目標(biāo)的探測具有非常優(yōu)越的性能，但是三維匹配濾波算法對于速度失配的運動目標(biāo)將表現(xiàn)的很差，其要求更加密集的速度方向濾波器，對現(xiàn)有計算機存儲和計算能力提出了較高要求； （4）針對經(jīng)投影算法計算得到的二維圖像，設(shè)計了一種引入分層投票理論的非關(guān)聯(lián)點移除算法，有效地對孤立點和弱相關(guān)點去除，保留了目標(biāo)軌跡；通過引入hash原理設(shè)計計算了對多目標(biāo)軌跡進行分類的參數(shù)，，有效地將多目標(biāo)軌跡進行分類，并且給出了仿真； （5）利用本文研究成果，設(shè)計開發(fā)了基于GUI的紅外小目標(biāo)檢測軟件系統(tǒng)，可以實現(xiàn)抖動序列生成，待配準(zhǔn)幀抖動量計算，三維匹配濾波算法對小目標(biāo)檢測和基于投影算法的目標(biāo)檢測。 本文所研究的基于時空域濾波的紅外小目標(biāo)檢測可以為在軌目標(biāo)檢測提供理論基礎(chǔ)。
[Abstract]:In order to improve the detection ability of small infrared target, the geostationary gaze probe is used as the application background in this paper. Two algorithms are proposed to detect small targets: 3D matched filter and projection based target detection. In view of the inherent jitter of the moving platform and the low correlation of the target in the sequence images taken by the staring detector, a new jitter compensation algorithm is proposed. The main research work of this paper is as follows: (1) the characteristics of infrared small target image are analyzed, and the theoretical basis of algorithm simulation input is given. (2) according to the background characteristics of infrared cloud image, The background model based on gray level is constructed by using the least square method to estimate the jitter of the sequence image and to register the sequence image. (3) based on the principle of maximum signal-to-noise ratio (SNR) and Cauchy Schwartz inequality, the general mathematical formula of 3D matched filter is derived. For the sequence images, the general flow of 3D matched filtering algorithm is given and the algorithm simulation is carried out, which effectively verifies that the 3D matched filtering algorithm has very superior performance for detecting low SNR small targets. But the 3D matched filtering algorithm will be very poor for the velocity mismatched moving target, which requires more intensive velocity direction filter, and puts forward a higher demand for the existing computer storage and computing power. (4) for the two-dimensional images calculated by the projection algorithm, a non-correlation point removal algorithm based on the hierarchical voting theory is designed, which can effectively remove the isolated points and weak correlation points and keep the target track. By introducing the principle of hash, the parameters of multi-target trajectory classification are designed and calculated, the multi-target trajectory is effectively classified, and the simulation is given. (5) using the research results of this paper, The infrared small target detection software system based on GUI is designed and developed, which can generate the jitter sequence, calculate the jitter amount of the frame to be registered, detect the small target with 3D matched filtering algorithm and detect the target based on projection algorithm. In this paper, the small infrared target detection based on spatio-temporal filtering can provide a theoretical basis for in-orbit target detection.
【學(xué)位授予單位】：哈爾濱工業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TP751

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