多通道雷達(dá)信號(hào)自適應(yīng)檢測技術(shù)研究
發(fā)布時(shí)間：2019-06-21 08:30
【摘要】：信號(hào)檢測是信號(hào)處理的主要問題之一。早期的信號(hào)檢測理論主要針對(duì)單通道數(shù)據(jù)。隨著科技的發(fā)展,信號(hào)檢測所要處理的數(shù)據(jù)通常以多通道形式呈現(xiàn),例如相控陣天線的應(yīng)用使雷達(dá)接收數(shù)據(jù)為多通道形式,且以復(fù)值向量或矩陣形式存在。此外,由于雜波和干擾的影響,雷達(dá)面臨的噪聲環(huán)境通常為色噪聲。本文針對(duì)未知色噪聲環(huán)境中的多通道雷達(dá)信號(hào)檢測問題,研究有效的自適應(yīng)檢測方法。主要貢獻(xiàn)如下:第二章給出了復(fù)值多通道信號(hào)檢測對(duì)應(yīng)的Rao準(zhǔn)則和Wald準(zhǔn)則,以及用于衡量復(fù)值參數(shù)估計(jì)性能的克拉美-羅界(Cramér-Rao Bound,CRB)。與現(xiàn)有方法相比,所提方法不需要將復(fù)數(shù)據(jù)按實(shí)部和虛部級(jí)聯(lián)處理,而是把數(shù)據(jù)直接在復(fù)數(shù)域處理,從而降低了設(shè)計(jì)難度及計(jì)算復(fù)雜度。第三章研究了信號(hào)失配時(shí)的點(diǎn)目標(biāo)檢測問題。通過增加虛擬隨機(jī)或確定干擾,基于Wald準(zhǔn)則和GLRT準(zhǔn)則,提出了失配敏感(即對(duì)失配信號(hào)抑制能力強(qiáng))檢測器。在此基礎(chǔ)上,提出了單參數(shù)和雙參數(shù)可調(diào)自適應(yīng)檢測器。通過參數(shù)調(diào)節(jié),可調(diào)檢測器可實(shí)現(xiàn)對(duì)失配信號(hào)的有效檢測。此外,對(duì)上述自適應(yīng)檢測器進(jìn)行了統(tǒng)計(jì)性能分析,得到了檢測器的統(tǒng)計(jì)分布及檢測概率和虛警概率的數(shù)學(xué)解析式。第四章研究了存在干擾時(shí)的點(diǎn)目標(biāo)檢測問題,分析了三種典型干擾類型下的檢測技術(shù)。(1)針對(duì)已知干擾,根據(jù)Rao準(zhǔn)則和Wald準(zhǔn)則,提出了相應(yīng)的自適應(yīng)檢測器。此外,提出了干擾已知時(shí)新的檢測策略,即先干擾抑制后檢測(Interference Cancellation Before Detection,ICBD)。與常規(guī)檢測器設(shè)計(jì)方法相比,該方法更加簡便,并且可工作在訓(xùn)練樣本數(shù)少于待檢測數(shù)據(jù)維數(shù)的環(huán)境中。(2)針對(duì)部分已知干擾,基于廣義似然比檢測器(Generalized Likelihood Ratio Test,GLRT)準(zhǔn)則、Rao準(zhǔn)則和Wald準(zhǔn)則,提出了三種有效檢測器,并分析了三者的統(tǒng)計(jì)性能。(3)針對(duì)完全未知干擾,根據(jù)GLRT準(zhǔn)則和Wald準(zhǔn)則,提出了有效的檢測器,與現(xiàn)有檢測器相比,新檢測器具有更高的檢測概率。第五章研究了存在信號(hào)失配時(shí)的擴(kuò)展目標(biāo)檢測問題。通過人為增加虛擬確定干擾,提出了兩種失配敏感檢測器。然后在此基礎(chǔ)上提出了一種參數(shù)可調(diào)檢測器。根據(jù)設(shè)計(jì)需要,該檢測器可實(shí)現(xiàn)對(duì)失配擴(kuò)展目標(biāo)的有效檢測或者有效抑制。第六章研究了雙子空間信號(hào)(Double-Subspace Signal,DOSS)的檢測問題。DOSS信號(hào)指的是矩陣信號(hào)的行和列均位于已知子空間中。DOSS模型推廣了現(xiàn)有分布目標(biāo)檢測問題中的信號(hào)模型。根據(jù)GLRT準(zhǔn)則、Rao準(zhǔn)則和Wald準(zhǔn)則,以及譜范數(shù)檢測器(Spectral Norm Test,SNT)的思想,提出了多種檢測器。此外,分析了各檢測器對(duì)應(yīng)的多種特例。最后,通過仿真實(shí)驗(yàn)比較了各檢測器在不同參數(shù)設(shè)置下的性能差異。第七章研究了三種目標(biāo)方向信息不確定時(shí)的檢測問題。(1)針對(duì)目標(biāo)方向信息完全未知時(shí)的檢測問題,基于Rao準(zhǔn)則和Wald準(zhǔn)則,提出了兩種有效的檢測器。(2)當(dāng)目標(biāo)回波均來自同一個(gè)方向,且相應(yīng)的信號(hào)導(dǎo)向矢量位于一個(gè)已知子空間時(shí),相應(yīng)的檢測問題稱為方向檢測�；赪ald準(zhǔn)則,提出了一種有效的方向檢測器,并與現(xiàn)有檢測器進(jìn)行了比較。(3)當(dāng)目標(biāo)的空域?qū)蚴噶亢蜁r(shí)域?qū)蚴噶烤挥谝阎涌臻g時(shí),根據(jù)GLRT準(zhǔn)則和Wald準(zhǔn)則及二者的兩步實(shí)現(xiàn),提出了四種有效的廣義方向檢測器,并給出了每種廣義方向檢測器的特例。第八章研究了小樣本條件下的機(jī)載雷達(dá)空時(shí)自適應(yīng)檢測(Space-Time Adaptive Detection,STAD)問題�；趯�(duì)角加載、主分量分析和Krylov子空間技術(shù),提出了訓(xùn)練樣本數(shù)不足時(shí)的多種有效檢測器,分析了各檢測器的漸近統(tǒng)計(jì)分布,并推導(dǎo)了漸近檢測概率和虛警概率的解析式。第九章研究了天線共置多輸入多輸出(Multiple-Input Multiple-Output,MIMO)雷達(dá)的自適應(yīng)檢測問題�；赗ao準(zhǔn)則和Wald準(zhǔn)則,提出了相應(yīng)的自適應(yīng)檢測器,分析了其統(tǒng)計(jì)性能,并與對(duì)應(yīng)的相控陣?yán)走_(dá)自適應(yīng)檢測器進(jìn)行了比較。
[Abstract]:Signal detection is one of the main problems in signal processing. The early signal detection theory is mainly for single-channel data. With the development of science and technology, the data to be processed in the signal detection is usually presented in a multi-channel form, for example, the application of the phased array antenna enables the radar to receive data as a multi-channel form and is present in the form of a complex value vector or a matrix. In addition, due to the influence of clutter and interference, the noise environment facing the radar is usually color noise. In this paper, the problem of multi-channel radar signal detection in an unknown color noise environment is studied, and the effective self-adaptive detection method is studied. The main contribution is as follows: In the second chapter, the Rao criterion and the Wald criterion corresponding to the multi-channel signal detection of complex value are given, and the Cram-Rao Boround (CRB) is used to measure the parameter estimation performance of complex values. Compared with the prior art, the method does not need to process the complex data according to the real part and the virtual department, but the data is directly processed in a plurality of domains, so that the design difficulty and the calculation complexity are reduced. In the third chapter, the problem of point target detection in signal mismatch is studied. By increasing the virtual random or determined interference, a mismatch-sensitive (i.e., a strong-to-mismatch signal suppression capability) detector is proposed based on the Wald criterion and the GLRT criterion. On this basis, a single-parameter and two-parameter adjustable self-adaptive detector is proposed. By means of the parameter adjustment, the adjustable detector can realize the effective detection of the mismatch signal. In addition, the statistical performance analysis of the adaptive detector is carried out, and the statistical distribution of the detector and the mathematical analysis of the detection probability and the false alarm probability are obtained. In the fourth chapter, the problem of the detection of the point object in the presence of the interference is studied, and the detection technology under the three typical interference types is analyzed. (1) For known interference, a corresponding adaptive detector is proposed according to the Rao criterion and the Wald criterion. In addition, a new detection strategy is proposed, that is, interference cancellation before detection (ICBD). Compared with the conventional detector design method, the method is more convenient and can work in an environment where the number of training samples is less than the dimension of the data to be detected. (2) For some known interference, based on the generalized likelihood ratio detector (GLRT) criterion, the Rao criterion and the Wald criterion, three effective detectors are proposed, and the statistical properties of the three are analyzed. (3) For completely unknown interference, a valid detector is proposed according to the GLRT criterion and the Wald criterion. Compared with the existing detector, the new detector has higher detection probability. The fifth chapter studies the problem of extended target detection in the presence of signal mismatch. Two kinds of mismatch sensitive detectors are proposed by artificially increasing the virtual determination interference. Then, a parameter-adjustable detector is proposed. According to the design requirements, the detector can realize the effective detection or the effective suppression of the mismatch expansion target. In chapter 6, the detection of Double-Subspace Signal (DOSS) is studied. The dss signal refers to the rows and columns of the matrix signal being in the known sub-space. The DOSS model extends the signal model in the existing distribution target detection problem. According to the GLRT criterion, the Rao criterion and the Wald criterion, and the idea of the spectral norm detector (SNT), a variety of detectors are proposed. In addition, various special cases corresponding to each detector are analyzed. Finally, the performance difference of each detector under different parameter settings is compared through the simulation experiment. Chapter 7 studies the detection problem when the three target direction information is uncertain. (1) Two effective detectors are proposed based on the Rao criterion and the Wald criterion when the target direction information is completely unknown. (2) When the target echoes come from the same direction and the corresponding signal guide vector is located in a known subspace, the corresponding detection problem is called direction detection. Based on the Wald criterion, an effective direction detector is proposed and compared with the existing detector. (3) Four effective generalized directional detectors are proposed according to the GLRT criterion and the Wald criterion and the two-step implementation of both the GLRT criterion and the Wald criterion, and a special case of each generalized direction detector is given. In chapter 8, the space-time adaptive detection (STAD) problem of airborne radar under the condition of small samples is studied. Based on the diagonal loading, the principal component analysis and the Krylov subspace technique, a variety of effective detectors with insufficient training samples are proposed, the asymptotic statistical distribution of each detector is analyzed, and the analytical expressions of the asymptotic detection probability and the false alarm probability are derived. Chapter 9 studies the self-adaptive detection of multiple-input multiple-output (MIMO) radar. Based on the Rao criterion and the Wald criterion, a corresponding adaptive detector is proposed, and its statistical performance is analyzed and compared with the corresponding phased-array radar adaptive detector.
【學(xué)位授予單位】：國防科學(xué)技術(shù)大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2014
【分類號(hào)】：TN957.51
，
本文編號(hào)：2503933
[Abstract]:Signal detection is one of the main problems in signal processing. The early signal detection theory is mainly for single-channel data. With the development of science and technology, the data to be processed in the signal detection is usually presented in a multi-channel form, for example, the application of the phased array antenna enables the radar to receive data as a multi-channel form and is present in the form of a complex value vector or a matrix. In addition, due to the influence of clutter and interference, the noise environment facing the radar is usually color noise. In this paper, the problem of multi-channel radar signal detection in an unknown color noise environment is studied, and the effective self-adaptive detection method is studied. The main contribution is as follows: In the second chapter, the Rao criterion and the Wald criterion corresponding to the multi-channel signal detection of complex value are given, and the Cram-Rao Boround (CRB) is used to measure the parameter estimation performance of complex values. Compared with the prior art, the method does not need to process the complex data according to the real part and the virtual department, but the data is directly processed in a plurality of domains, so that the design difficulty and the calculation complexity are reduced. In the third chapter, the problem of point target detection in signal mismatch is studied. By increasing the virtual random or determined interference, a mismatch-sensitive (i.e., a strong-to-mismatch signal suppression capability) detector is proposed based on the Wald criterion and the GLRT criterion. On this basis, a single-parameter and two-parameter adjustable self-adaptive detector is proposed. By means of the parameter adjustment, the adjustable detector can realize the effective detection of the mismatch signal. In addition, the statistical performance analysis of the adaptive detector is carried out, and the statistical distribution of the detector and the mathematical analysis of the detection probability and the false alarm probability are obtained. In the fourth chapter, the problem of the detection of the point object in the presence of the interference is studied, and the detection technology under the three typical interference types is analyzed. (1) For known interference, a corresponding adaptive detector is proposed according to the Rao criterion and the Wald criterion. In addition, a new detection strategy is proposed, that is, interference cancellation before detection (ICBD). Compared with the conventional detector design method, the method is more convenient and can work in an environment where the number of training samples is less than the dimension of the data to be detected. (2) For some known interference, based on the generalized likelihood ratio detector (GLRT) criterion, the Rao criterion and the Wald criterion, three effective detectors are proposed, and the statistical properties of the three are analyzed. (3) For completely unknown interference, a valid detector is proposed according to the GLRT criterion and the Wald criterion. Compared with the existing detector, the new detector has higher detection probability. The fifth chapter studies the problem of extended target detection in the presence of signal mismatch. Two kinds of mismatch sensitive detectors are proposed by artificially increasing the virtual determination interference. Then, a parameter-adjustable detector is proposed. According to the design requirements, the detector can realize the effective detection or the effective suppression of the mismatch expansion target. In chapter 6, the detection of Double-Subspace Signal (DOSS) is studied. The dss signal refers to the rows and columns of the matrix signal being in the known sub-space. The DOSS model extends the signal model in the existing distribution target detection problem. According to the GLRT criterion, the Rao criterion and the Wald criterion, and the idea of the spectral norm detector (SNT), a variety of detectors are proposed. In addition, various special cases corresponding to each detector are analyzed. Finally, the performance difference of each detector under different parameter settings is compared through the simulation experiment. Chapter 7 studies the detection problem when the three target direction information is uncertain. (1) Two effective detectors are proposed based on the Rao criterion and the Wald criterion when the target direction information is completely unknown. (2) When the target echoes come from the same direction and the corresponding signal guide vector is located in a known subspace, the corresponding detection problem is called direction detection. Based on the Wald criterion, an effective direction detector is proposed and compared with the existing detector. (3) Four effective generalized directional detectors are proposed according to the GLRT criterion and the Wald criterion and the two-step implementation of both the GLRT criterion and the Wald criterion, and a special case of each generalized direction detector is given. In chapter 8, the space-time adaptive detection (STAD) problem of airborne radar under the condition of small samples is studied. Based on the diagonal loading, the principal component analysis and the Krylov subspace technique, a variety of effective detectors with insufficient training samples are proposed, the asymptotic statistical distribution of each detector is analyzed, and the analytical expressions of the asymptotic detection probability and the false alarm probability are derived. Chapter 9 studies the self-adaptive detection of multiple-input multiple-output (MIMO) radar. Based on the Rao criterion and the Wald criterion, a corresponding adaptive detector is proposed, and its statistical performance is analyzed and compared with the corresponding phased-array radar adaptive detector.
【學(xué)位授予單位】：國防科學(xué)技術(shù)大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2014
【分類號(hào)】：TN957.51
，
本文編號(hào)：2503933
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