【摘要】：在雷達系統(tǒng)中,恒虛警率問題是每個雷達設(shè)計者必須要面對的重要問題之一。恒虛警檢測技術(shù)是雷達目標(biāo)檢測系統(tǒng)中控制虛警率的最重要手段。本文在深入理解目標(biāo)檢測理論與恒虛警率處理方法的基礎(chǔ)上,主要研究了在高斯雜波背景下的自適應(yīng)恒虛警檢測技術(shù)。這其中包括均勻高斯背景、存在雜波邊緣的非均勻環(huán)境以及多目標(biāo)情況下的檢測問題。本文重點研究的恒虛警率處理方法有均值類恒虛警率、有序統(tǒng)計類恒虛警率以及雜波圖恒虛警率處理方法。其中,對于均值類恒虛警率處理方法,主要研究了單元平均恒虛警率方法、單元平均選大恒虛警率方法和單元平均選小恒虛警率方法。本文簡單介紹了每種方法的基本原理以及實現(xiàn)過程,并分析了這些方法在均勻高斯環(huán)境、雜波邊緣環(huán)境以及多目標(biāo)環(huán)境下的特點,之后對這些方法在不同環(huán)境下的目標(biāo)檢測性能進行計算機數(shù)值仿真分析,最后討論了這些方法的恒虛警率損失。雜波圖處理方法為空域雜波變化劇烈而時域上變化平穩(wěn)的環(huán)境下的目標(biāo)檢測提供了一種很好的方法。本文采用雜波圖點技術(shù)和雜波圖面技術(shù)對慢速移動目標(biāo)和快速移動目標(biāo)的檢測性能進行仿真分析,并且對比分析這兩種方法的優(yōu)缺點。在理論仿真之后,本文對實測數(shù)據(jù)進行處理。根據(jù)處理結(jié)果,進一步驗證了每種檢測方法的特點。最后,本文提出了一種自適應(yīng)恒虛警算法選擇的方法,該方法是在均值類CFAR和雜波圖方法的基礎(chǔ)上提出來的。首先建立待檢測區(qū)域的雜波圖,然后根據(jù)雜波圖判斷出雜波的分布情況,即判斷雜波平穩(wěn)區(qū)、雜波邊緣的弱雜波區(qū)與雜波邊緣的強雜波區(qū),最后根據(jù)雜波的分布情況選用最合適的CFAR處理方法。從實驗結(jié)果中看出,本文提出的方法能有效地減少雷達檢測中的虛警和漏警,顯著地提高系統(tǒng)的性能。
[Abstract]:In radar system, constant false alarm rate is one of the important problems that every radar designer must face. CFAR detection technology is the most important means to control false alarm rate in radar target detection system. Based on the deep understanding of target detection theory and CFAR processing method, this paper mainly studies the adaptive CFAR detection technology in the background of Gao Si Clutter. This includes uniform Gao Si background, non-uniform environment with clutter edge and detection problem in the case of multi-target. In this paper, the methods of constant false alarm rate are studied, such as mean constant false alarm rate, ordered statistical constant false alarm rate and clutter graph constant false alarm rate processing method. Among them, for the mean constant false alarm rate treatment method, the unit average constant false alarm rate method, the unit average selection large constant false alarm rate method and the unit average selection small constant false alarm rate method are mainly studied. In this paper, the basic principle and implementation process of each method are briefly introduced, and the characteristics of these methods in uniform Gao Si environment, cluttered edge environment and multi-target environment are analyzed. Then the target detection performance of these methods in different environments is analyzed by computer numerical simulation. Finally, the constant false alarm rate loss of these methods is discussed. The wavelet pattern processing method provides a good method for target detection in the environment where the spatial clutters change violently and the time domain changes smoothly. In this paper, the detection performance of slow moving target and fast moving target is simulated and analyzed by using clutter map point technology and clutter surface technology, and the advantages and disadvantages of the two methods are compared and analyzed. After the theoretical simulation, the measured data are processed in this paper. According to the processing results, the characteristics of each detection method are further verified. Finally, an adaptive CFAR algorithm selection method is proposed, which is based on the mean CFAR and hash graph methods. Firstly, the hash map of the area to be detected is established, and then the distribution of the clutter is judged according to the hash map, that is, the stable region of the clutter, the weak hash region of the edge of the clutter and the strong clutter region of the edge of the clutter. Finally, the most suitable CFAR processing method is selected according to the distribution of clutters. The experimental results show that the proposed method can effectively reduce the false alarm and missed alarm in radar detection, and significantly improve the performance of the system.
【學(xué)位授予單位】：西安電子科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TN957.52

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相關(guān)期刊論文 前1條

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本文編號：2486438