本文關(guān)鍵詞： 目標(biāo)檢測(cè) 恒虛警 自動(dòng)剔除 Switching-CFAR 非均勻噪聲　出處：《華東師范大學(xué)學(xué)報(bào)(自然科學(xué)版)》2017年03期 　論文類型：期刊論文

【摘要】：針對(duì)傳統(tǒng)恒虛警(Constant False-Alarm Rate,CFAR)檢測(cè)器在非均勻噪聲環(huán)境下檢測(cè)性能較差的問題,本文提出了一種基于排序的自動(dòng)剔除Switching-CFAR(Automatic Censoring Switching-CFAR Detector Based on Sorting,ACS-CFAR)檢測(cè)器.選擇參考窗中間單元為測(cè)試單元,其余單元按照幅值升序排列,根據(jù)兩個(gè)分界點(diǎn)位置參數(shù),選擇合適的參考單元集進(jìn)行背景噪聲功率估計(jì)以及結(jié)合參考單元數(shù)和目標(biāo)恒虛警率計(jì)算相關(guān)系數(shù),得到最優(yōu)檢測(cè)門限.經(jīng)過仿真對(duì)比,ACS-CFAR檢測(cè)器在均勻噪聲環(huán)境下檢測(cè)率為98.73%,接近于單元平均恒虛警(CA-CFAR)檢測(cè)器;在非均勻噪聲環(huán)境下檢測(cè)率為98.16%,優(yōu)于可變索引恒虛警(VI-CFAR)和自動(dòng)刪除平均恒虛警(ACCA-CFAR)檢測(cè)器,虛警率誤差均控制在0.10%以內(nèi).結(jié)果表明,本文提出的ACS-CFAR檢測(cè)器在均勻噪聲環(huán)境以及雜波和多目標(biāo)干擾環(huán)境下均具有較好的檢測(cè)性能.
[Abstract]:In order to solve the problem that the detection performance of traditional constant false alarm constant False-Alarm (CFAR) detector is poor in non-uniform noise environment, a sort of Switching-CFAR(Automatic Censoring Switching-CFAR Detector Based on sorting ACS-CFAR detector is proposed in this paper. The middle unit of the reference window is selected as the test unit. The other units are arranged in ascending order of amplitude. According to the location parameters of two boundary points, the appropriate reference unit set is selected to estimate the background noise power, and the correlation coefficient is calculated by combining the number of reference units and the constant false alarm rate of the target. The optimal detection threshold is obtained. The detection rate of ACS-CFAR detector in uniform noise environment is 98.733.It is close to the average CFAR CA-CFAR detector. The detection rate in non-uniform noise environment is 98.16, which is superior to VI-CFAR (variable index CFAR) and ACCA-CFAR (automatic delete CFAR) detector. The error of false alarm rate is controlled within 0.10%. The proposed ACS-CFAR detector has better detection performance in uniform noise environment and clutter and multi-target interference environments.
【作者單位】： 安徽工程大學(xué)計(jì)算機(jī)與信息學(xué)院;奇瑞汽車股份有限公司前瞻技術(shù)研究院;
【基金】：國家自然科學(xué)基金(91120307) 安徽省自然科學(xué)基金(TSKJ2015B12) 安徽工程大學(xué)計(jì)算機(jī)應(yīng)用技術(shù)重點(diǎn)實(shí)驗(yàn)室開放基金(JSJKF201514)
【分類號(hào)】：TN957.51

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