基于平行因子的双基圆阵MIMO雷达定位与测速方法研究

发布时间：2018-03-23 11:54

本文选题：平行因子　切入点：多目标　出处：《西安电子科技大学》2015年硕士论文

【摘要】：多输入多输出(MIMO)雷达是一种新体制雷达,它将MIMO技术引入雷达系统,从而增加自由度并提高分辨率,具有广宽的应用前景。双基地MIMO雷达系统既有双基地雷达探测隐身目标、隐蔽侦查等特点,同时又能获得MIMO技术带来的优势。在雷达系统中多目标角度和多普勒估计是探测目标信息的重要一环。学者们通常采用对角度与多普勒分别估计并进行配对的方法来实现多目标参数估计,然而多目标情况下的参数配对问题较为复杂,不利于工程实践。因此多目标下双基地MIMO雷达的角度和多普勒估计与配对问题受到了广泛关注。在双基地MIMO雷达系统中,传统的MUSIC和Capon角度估计方法需进行二维谱峰搜索,计算复杂度高,同时需要进行角度多普勒配对。ESPRIT算法能够实现对目标角度和多普勒同时估计,但是在收发阵列均为线阵时只能得到雷达目标的两维角度信息,无法对目标进行三维空间定位。同时线阵在不同角度的测角精度不同,双圆阵的提出解决了这个问题,但在发射接收均为双圆阵情况下导向矢量并不具有旋转不变性,传统ESPRIT方法无法直接使用。本文针对在多目标情况下双基圆阵MIMO雷达的定位测速问题,提出了一种基于平行因子的双基圆阵MIMO雷达角度与多普勒估计方法。该方法将得到的接收信号构建为平行因子模型,利用COMFAC方法求解模型,同时根据该模型下求得的导向矢量的结构特点,最终估计出目标的接收角度、发射角度和多普勒,进而得到目标位置与速度信息,该方法可以同时得到角度与多普勒五维信息,参数自动配对,实现了多目标在空间中三维定位和测速。本文推导了双基圆阵MIMO雷达的多目标角度、多普勒和定位精度的克拉美罗界,由于克拉美罗界是参数估计结果在理论上能够达到的最低方差,反应了是算法在理论上可以到达的最好的参数估计性能,故将其作为与本文所提算法的参数估计误差分析的对比,利用计算机仿真实验对基于平行因子的双基地MIMO雷达角度与多普勒联合估计方法在不同信噪比、不同阵列尺寸情况下的性能进行对比分析。通过对仿真结果的分析,本文方法在双基圆阵MIMO雷达下可以实现角度多普勒五维参数估计,能够同时分辨多个目标,实现了多目标情况下角度多普勒自动配对,提高了定位与测速精度。
[Abstract]:Multiple-Input-Multiple-Output (Mimo) radar is a kind of new system radar. It introduces MIMO technology into radar system, thus increasing the degree of freedom and improving the resolution. The bistatic MIMO radar system has a wide application prospect. Bistatic MIMO radar system can detect stealth targets by bistatic radar. The characteristics of covert investigation, At the same time, the advantages of MIMO technology can be obtained. In radar system, multi-target angle and Doppler estimation is an important part of detecting target information. Method to realize multiobjective parameter estimation, However, the problem of parameter matching in the case of multi-target is more complex, which is not conducive to engineering practice. Therefore, the angle and Doppler estimation and pairing of bistatic MIMO radar in multi-target systems are paid more and more attention. Traditional MUSIC and Capon angle estimation methods need 2-D spectral peak search, which has high computational complexity. At the same time, it needs angle Doppler matching. Esprit algorithm can estimate the target angle and Doppler simultaneously. But when the transceiver array is linear, it can only get the two dimensional angle information of the radar target, so it can not locate the target in three dimensional space. At the same time, the angle accuracy of the linear array is different at different angles, so the double circle array can solve this problem. However, the steering vector is not rotation-invariant when the transmitting and receiving is double circular array, and the traditional ESPRIT method can not be used directly. In this paper, the localization and velocity measurement of double circular array MIMO radar under multi-target condition is studied. An angle and Doppler estimation method based on parallel factor for dual-base circular array MIMO radar is proposed in this paper. The received signal is constructed as a parallel factor model, and the model is solved by using the COMFAC method. At the same time, according to the structural characteristics of the guidance vector obtained under the model, the receiving angle, the transmitting angle and the Doppler of the target are estimated, and then the position and velocity information of the target are obtained. The method can obtain the five-dimensional information of the angle and the Doppler at the same time. In this paper, the multi-target angle, Doppler and Clemero boundary of the dual-base circular array MIMO radar are derived, and the parameters are automatically matched to realize the multi-target positioning and velocimetry in space, and the multi-target angle, Doppler and positioning accuracy of the dual-base circular array MIMO radar are derived. Because the Clemero bound is the lowest variance of the parameter estimation results in theory, it reflects the best parameter estimation performance that the algorithm can achieve in theory. Therefore, it is compared with the parameter estimation error analysis of the proposed algorithm, and the parallel factor based bistatic MIMO radar angle and Doppler joint estimation method is used in different signal-to-noise ratio (SNR) by computer simulation experiment. The performance of different array sizes is compared and analyzed. Through the analysis of simulation results, the method can estimate the five dimensional parameters of angle Doppler in double circular array MIMO radar, and can distinguish multiple targets at the same time. The automatic matching of angle Doppler is realized in the case of multiple targets, and the accuracy of positioning and velocity measurement is improved.
【学位授予单位】：西安电子科技大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TN958

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