非均匀线阵MIMO雷达多目标参数联合估计方法研究

发布时间：2018-02-06 00:57

本文关键词： MIMO雷达参数联合估计非均匀阵列互质阵嵌套阵　出处：《吉林大学》2017年硕士论文　论文类型：学位论文

【摘要】：多输入多输出(MIMO)雷达作为一种新型雷达体制,凭借其与传统雷达体制相比所具备的诸多优势,已引起国内外学者的广泛关注。作为目标定位和成像的关键技术,目标参数估计是MIMO雷达的重要研究方向,具有十分重要的研究意义。然而,传统的MIMO雷达系统均采用均匀线阵(ULA)配置,以发射分集MIMO雷达为例,其最大可识别目标数为接收阵列阵元数减一,由于空间分辨力正比于接收阵列孔径,当接收阵列阵元数配置不足时,其空间分辨力及最大可识别目标数将十分受限。非均匀线阵(NLA)是近年来出现的一种新的阵型,常见的NLA有互质阵(Coprime Array)、嵌套阵(Nested Array)等。NLA的阵元间距不相等,而是满足特定条件且为载波波长一半的整数倍,由于其具有较大的阵列孔径且包含大量的虚拟阵元,已成为阵列信号处理研究的热点之一。本文将MIMO雷达的阵列配置为非均匀线阵,可显著提高其最大可识别目标数、空间分辨力及目标参数估计精度。通过将不同类型MIMO雷达配置为互质阵和嵌套阵,本文研究了非均匀线阵MIMO雷达的多目标参数联合估计问题。本文的研究工作得到国家自然科学基金项目(No:61371158和No:61071140)的资助。本文的创新性研究工作如下:通过将发射分集MIMO雷达的接收阵列分别配置为互质阵和嵌套阵,提出了两种改进型发射分集MIMO雷达,建立了信号模型并提出了相应的目标方向识别算法。仿真实验表明,当目标数远远大于接收阵列阵元数时,两种改进型发射分集MIMO雷达均可实现多目标的精确定位,与传统发射分集MIMO雷达相比具有更高的角度分辨力。通过将双基地MIMO雷达的发射阵列和接收阵列均配置为嵌套阵,提出了一种改进型双基地MIMO雷达,建立了信号模型并提出了一种目标出发角(DOD)和到达角(DOA)联合估计算法。仿真实验表明,在出现多目标情况下,改进型双基地MIMO雷达具有更高的二维角度分辨力。通过将极化双基地MIMO雷达的收发阵列均配置为互质阵并在时域采用互质采样方式,提出了一种改进型极化双基地MIMO雷达,建立了信号模型并分别提出了基于平行因子-三线性分解(PARAFAC-TALS)和平行因子-四线性分解(PARAFAC-QALS)的目标多参数联合估计算法,可实现目标DOD、DOA、极化参数和多普勒频率联合估计。为进一步扩展阵列孔径,将极化双基地MIMO雷达的收发阵列均配置为嵌套阵并在时域采用嵌套采样方式,分别提出了基于PARAFAC-TALS和PARAFAC-QALS的多目标DOD、DOA、极化参数和多普勒频率联合估计算法。仿真实验表明,所提出的两种方法可获得更高的空间分辨力和多参数估计精度。
[Abstract]:As a new radar system, multi-input and multi-output MIMO-radar has many advantages compared with the traditional radar system. As the key technology of target location and imaging, target parameter estimation is an important research direction of MIMO radar, and has a very important research significance. The traditional MIMO radar system adopts uniform linear array (ULA) configuration. Taking the transmit diversity MIMO radar as an example, the maximum identifiable target number is the number of received array elements minus one. Because the spatial resolution is proportional to the aperture of the receiving array, when the number of elements of the receiving array is insufficient. The spatial resolution and the maximum number of identifiable targets will be very limited. Non-uniform linear array (NLAs) is a new formation in recent years. The common NLA are coprime Arrayn and nested Array.NLAs have unequal cell spacing. It is an integer multiple of the carrier wavelength half of the carrier wavelength, because it has a large array aperture and contains a large number of virtual array elements. In this paper, the array of MIMO radar is configured as a non-uniform linear array, which can significantly improve the maximum number of recognizable targets. Spatial resolution and precision of target parameter estimation. Different types of MIMO radars are configured into mutual-prime matrix and nested matrix. In this paper, the joint estimation of multi-target parameters for nonuniform linear array MIMO radar is studied. The research work of this paper has been carried out by the National Natural Science Foundation of China (. No:61371158 and No: 61071140). The innovative research work of this paper is as follows: the receiving array of transmit diversity MIMO radar is configured into mutual prime array and nested array respectively. Two kinds of improved transmit diversity MIMO radar are proposed, the signal model is established and the corresponding target direction recognition algorithm is proposed. The simulation results show that the number of targets is much larger than the number of array elements. Two kinds of improved transmit diversity MIMO radar can achieve accurate location of multiple targets. Compared with the traditional transmit diversity MIMO radar, it has higher angular resolution. Both the transmitting and receiving arrays of bistatic MIMO radar are configured as nested arrays. An improved bistatic MIMO radar is proposed, a signal model is established and a joint estimation algorithm of the starting angle of the target and the angle of arrival (DOD) is proposed. In the case of multiple targets. The improved bistatic MIMO radar has higher two-dimensional angular resolution. By configuring the transceiver array of polarimetric bistatic MIMO radar into mutual mass array and adopting mutual-mass sampling method in time domain. An improved polarimetric bistatic MIMO radar is proposed. The signal model is established and proposed based on parallel factor-trilinear decomposition (PARAFAC-TALS) and parallel factor-quadrulinear decomposition (PARAFAC-QALS). The algorithm of multi-parameter joint estimation of target is presented in this paper. The DODDOA, polarization parameter and Doppler frequency estimation can be realized for the further expansion of the array aperture. The transceiver array of polarimetric bistatic MIMO radar is configured into nested array and nested sampling is adopted in time domain. The joint estimation algorithms of DODO, polarization parameters and Doppler frequency are proposed based on PARAFAC-TALS and PARAFAC-QALS, respectively. The proposed two methods can obtain higher spatial resolution and multi-parameter estimation accuracy.
【学位授予单位】：吉林大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN958

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