MIMO雷达信号检测的若干问题研究
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摘要
目前在通信中已经广泛采用MIMO技术来克服多径效应的影响和提高传输率。在综合脉冲孔径雷达(Synthetic Impulse and Aperture Radar，SIAR)的启发下，利用通信界成熟的MIMO技术，MIMO技术被应用于雷达技术中，产生了两种类型的MIMO雷达。一种是Eran Fishler提出的收发全分集MIMO雷达。在常规雷达中，目标的起伏会使回波闪烁，引起雷达性能的下降，因而是被视为有害的。收发全分集MIMO雷达却相反，它正是利用了目标的起伏来改善雷达的性能。这种雷达的优势包括硬件简单、有效口径大、通过空间分集对抗目标衰落等。另外一种是由林肯实验室的学者首先提出的发射分集的MIMO雷达。在这种雷达中，收发阵列天线单元布置与相控阵雷达相同，因此可以把它看成是相控阵雷达的扩展。它的特点是发射相互正交的信号，而在接收端采用波束形成的方法进行处理。这种雷达的优点主要是利用发射信号的多样性提高雷达参数的可辨识性，提高角度分辨力。相比较而言，发射分集的MIMO雷达技术与现在使用的雷达技术更加接近，在工程上比较容易实现。
围绕两种类型的MIMO雷达，本文对检测相关问题展开研究。主要包括以下几个方面：
(1)研究了收发全分集MIMO雷达的原理特点和信号模型。针对经典的慢起伏雷达目标截面积RCS模型，X~2分布模型，理论分析了收发全分集MIMO雷达的检测性能，通过比较传统的相控阵，得出结论：收发全分集MIMO雷达在低信噪比时，检测性能优于相控阵；高信噪比时，检测性能略差于相控阵。
(2)将隐马尔可夫模型(Hidden Markov Model，HMM)应用于收发全分集的MIMO雷达目标检测。收发全分集MIMO雷达的天线阵元布置间距很大，接收天线从不同的角度观测目标，目标的回波在不同的角度上呈现各向异性，各个方向回波强度变化大；杂波的回波则呈现各向同性，各个方向回波强度基本相同。针对发全分集MIMO雷达的这一特点，可以用隐马尔可夫模型对目标和杂波回波分别建模，实现对目标回波和杂波的分离。
(3)研究了基于正交波形的发射分集MIMO雷达的原理。首先分析了这种雷达系统的特点，信号模型。构建了基于正交波形的发射分集MIMO雷达仿真系统，用仿真系统验证了发射分集MIMO雷达在抗截获性能、检测弱目标的能力、速度分辨力、距离分辨力等方面相对于传统相控阵雷达的优势。对仿真系统的处理流程进行分析，以信噪比为指标研究了系统的检测性能，结论是：采用频分的线性调
频信号时，通过长时间积累，发射分集MIMO雷达与相控阵雷达的检测信噪比相同，可以获得相同的检测性能。
(4)将空时自适应处理(Space-time Adaptive Processing，STAP)应用于正交波形的发射分集MIMO雷达。针对发射分集MIMO雷达发射正交信号的特点，将空时自适应处理技术进行了扩展，提出了波形-空间-时间三维信号处理方法，研究了三维信号空间中的目标、杂波、干扰信号模型。
(5)将Hough变换应用于发射信号分集的MIMO雷达检测问题中。首先针对常规Hough变换计算量大的问题，提出改进的方法，采用斜率-截距参数空间，通过平移参数空间单元格的方法来实现Hough变换，对具有相同到达时间的一组数据同时处理，降低了计算量。更进一步提出利用回波信号的相位实现相干积累，在低信噪比时提高检测性能。最后研究了将Hough变换应用于MIMO雷达长时间积累中的方法。
MIMO technique has been widely employed in communication system to combatmulti-path effect and improve transmission rate.Inspired by the SIAR(SyntheticImpulse and Aperture Radar) and MIMO communication technique,two kinds ofMIMO radar are put forward recently.The first one is based on both transmitting andreceiving diversities that is firstly presented by Eran Fishler.It is referred to TR-MIMOradar(Transmitting Receiving MIMO radar) or S-MIMO(Statistical MIMO radar).Inconventional radar,detection performance will be impacted when target RCSfluctuating.However,in TR-MIMO radar,a target's RCS spatial variations can beexploited to improve system performance.TR-MIMO has simple hardware structureand big effective aperture.Furthermore,it can combat target RCS fluctuating throughspace diversity.The other kind of MIMO radar is based on only transmitting diversitythat is firstly put forward by D.J.Rabideau.It is referred to T-MIMO(TransmittingMIMO) which has the same antenna configuration with the phased array radar.Therefore,it can be considered to be an extension of phased array radar.On transmit,the elements(or subarrays) of T-MIMO radar transmits omnidirectional,orthogonallycoded waveforms.On receive,the DBF(Digital beamforming) is employed.It has beenshown that waveform diversity enables the MIMO radar superiority in severalfundamental aspects,such as significantly improved parameter identifiability andangular resolving power.
In this dissertation,the target detection for these two kinds of MIMO radar isinvestigated,and the main research focus on the following issues:
1.The principles and characteristics of TR-MIMO radar are studied.Basing onthe classic RCS model,x~2,the detection performance of TR-MIMO radar is analyzed.And then,the detection performance of TR-MIMO radar is compared with that ofphased array radar when the RCS modeling is SwerlingⅠ.It is conclude that at lowsignal noise ratio(SNR),the MIMO system outperforms the phased-array system.
2.A new detection algorithm for MIMO radar based on the Hidden Markovmodels(HMM) is proposed.The distance among antennas is large in TR-MIMO radar.So,the target is observed from different aspects.Therefore,the returns of targetexhibit anisotropic,which is opposite to the returns of clutter.According to thischaracteristic,the target can clutter can be modeled with different HMMs respectivelyto realize the separation of them.
3.The principles and characteristics of T-MIMO radar are studied.Thecharacteristic and the signal model of the system are investigated firstly.A simulationplatform for T-MIMO radar is built,through which the MIMO radar performance and itsadvantages over the traditional phased radar are verified,such as anti-interception ofradar signal,weak target detection in strong clutter,and low velocity target detection.Furthermore,the detection performance is studied through signal noise ratio.It isconcluded that when the LFM signal is employed,the MIMO system has the sameperformance with conventional radar.
4.A preliminary investigation into space-time-waveform adaptive for T-MIMOradar is presented.Existing space-time adaptive processing(STAP) algorithm isextended to the waveform-time-space adaptive processing(WTSAP) case.The signalmodel required to generate simulated data is developed.Simulation results show asignificant improvement in detector performance as compared to conventional phasedarray radar.
5.The Hough Transform(HT) algorithm is applied to MIMO radar detection.Amodified algorithm is proposed to overcome the computational complexity.Theslope-intercept space is employed and the HT is realized through shifting the parameterspace cells.The computational load is reduced when processing the data with the samearrival time.Furthermore,the phase information of returns are exploited to realizecoherent integration,the detection performance can be improved when signal noise ratiois low.Finally,the method of using HT in long time integration is studied.
围绕两种类型的MIMO雷达，本文对检测相关问题展开研究。主要包括以下几个方面：
(1)研究了收发全分集MIMO雷达的原理特点和信号模型。针对经典的慢起伏雷达目标截面积RCS模型，X~2分布模型，理论分析了收发全分集MIMO雷达的检测性能，通过比较传统的相控阵，得出结论：收发全分集MIMO雷达在低信噪比时，检测性能优于相控阵；高信噪比时，检测性能略差于相控阵。
(2)将隐马尔可夫模型(Hidden Markov Model，HMM)应用于收发全分集的MIMO雷达目标检测。收发全分集MIMO雷达的天线阵元布置间距很大，接收天线从不同的角度观测目标，目标的回波在不同的角度上呈现各向异性，各个方向回波强度变化大；杂波的回波则呈现各向同性，各个方向回波强度基本相同。针对发全分集MIMO雷达的这一特点，可以用隐马尔可夫模型对目标和杂波回波分别建模，实现对目标回波和杂波的分离。
(3)研究了基于正交波形的发射分集MIMO雷达的原理。首先分析了这种雷达系统的特点，信号模型。构建了基于正交波形的发射分集MIMO雷达仿真系统，用仿真系统验证了发射分集MIMO雷达在抗截获性能、检测弱目标的能力、速度分辨力、距离分辨力等方面相对于传统相控阵雷达的优势。对仿真系统的处理流程进行分析，以信噪比为指标研究了系统的检测性能，结论是：采用频分的线性调
频信号时，通过长时间积累，发射分集MIMO雷达与相控阵雷达的检测信噪比相同，可以获得相同的检测性能。
(4)将空时自适应处理(Space-time Adaptive Processing，STAP)应用于正交波形的发射分集MIMO雷达。针对发射分集MIMO雷达发射正交信号的特点，将空时自适应处理技术进行了扩展，提出了波形-空间-时间三维信号处理方法，研究了三维信号空间中的目标、杂波、干扰信号模型。
(5)将Hough变换应用于发射信号分集的MIMO雷达检测问题中。首先针对常规Hough变换计算量大的问题，提出改进的方法，采用斜率-截距参数空间，通过平移参数空间单元格的方法来实现Hough变换，对具有相同到达时间的一组数据同时处理，降低了计算量。更进一步提出利用回波信号的相位实现相干积累，在低信噪比时提高检测性能。最后研究了将Hough变换应用于MIMO雷达长时间积累中的方法。
MIMO technique has been widely employed in communication system to combatmulti-path effect and improve transmission rate.Inspired by the SIAR(SyntheticImpulse and Aperture Radar) and MIMO communication technique,two kinds ofMIMO radar are put forward recently.The first one is based on both transmitting andreceiving diversities that is firstly presented by Eran Fishler.It is referred to TR-MIMOradar(Transmitting Receiving MIMO radar) or S-MIMO(Statistical MIMO radar).Inconventional radar,detection performance will be impacted when target RCSfluctuating.However,in TR-MIMO radar,a target's RCS spatial variations can beexploited to improve system performance.TR-MIMO has simple hardware structureand big effective aperture.Furthermore,it can combat target RCS fluctuating throughspace diversity.The other kind of MIMO radar is based on only transmitting diversitythat is firstly put forward by D.J.Rabideau.It is referred to T-MIMO(TransmittingMIMO) which has the same antenna configuration with the phased array radar.Therefore,it can be considered to be an extension of phased array radar.On transmit,the elements(or subarrays) of T-MIMO radar transmits omnidirectional,orthogonallycoded waveforms.On receive,the DBF(Digital beamforming) is employed.It has beenshown that waveform diversity enables the MIMO radar superiority in severalfundamental aspects,such as significantly improved parameter identifiability andangular resolving power.
In this dissertation,the target detection for these two kinds of MIMO radar isinvestigated,and the main research focus on the following issues:
1.The principles and characteristics of TR-MIMO radar are studied.Basing onthe classic RCS model,x~2,the detection performance of TR-MIMO radar is analyzed.And then,the detection performance of TR-MIMO radar is compared with that ofphased array radar when the RCS modeling is SwerlingⅠ.It is conclude that at lowsignal noise ratio(SNR),the MIMO system outperforms the phased-array system.
2.A new detection algorithm for MIMO radar based on the Hidden Markovmodels(HMM) is proposed.The distance among antennas is large in TR-MIMO radar.So,the target is observed from different aspects.Therefore,the returns of targetexhibit anisotropic,which is opposite to the returns of clutter.According to thischaracteristic,the target can clutter can be modeled with different HMMs respectivelyto realize the separation of them.
3.The principles and characteristics of T-MIMO radar are studied.Thecharacteristic and the signal model of the system are investigated firstly.A simulationplatform for T-MIMO radar is built,through which the MIMO radar performance and itsadvantages over the traditional phased radar are verified,such as anti-interception ofradar signal,weak target detection in strong clutter,and low velocity target detection.Furthermore,the detection performance is studied through signal noise ratio.It isconcluded that when the LFM signal is employed,the MIMO system has the sameperformance with conventional radar.
4.A preliminary investigation into space-time-waveform adaptive for T-MIMOradar is presented.Existing space-time adaptive processing(STAP) algorithm isextended to the waveform-time-space adaptive processing(WTSAP) case.The signalmodel required to generate simulated data is developed.Simulation results show asignificant improvement in detector performance as compared to conventional phasedarray radar.
5.The Hough Transform(HT) algorithm is applied to MIMO radar detection.Amodified algorithm is proposed to overcome the computational complexity.Theslope-intercept space is employed and the HT is realized through shifting the parameterspace cells.The computational load is reduced when processing the data with the samearrival time.Furthermore,the phase information of returns are exploited to realizecoherent integration,the detection performance can be improved when signal noise ratiois low.Finally,the method of using HT in long time integration is studied.
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