程院兵, 顾红, 苏卫民. 双基地MIMO雷达发射波束形成与多目标定位[J]. 电波科学学报, 2012, 27(2): 275-281.
      引用本文: 程院兵, 顾红, 苏卫民. 双基地MIMO雷达发射波束形成与多目标定位[J]. 电波科学学报, 2012, 27(2): 275-281.
      CHENG Yuan-bing, GU Hong, SU Wei-min. Transmit beamforming and multi-target localization in bistatic MIMO radar[J]. CHINESE JOURNAL OF RADIO SCIENCE, 2012, 27(2): 275-281.
      Citation: CHENG Yuan-bing, GU Hong, SU Wei-min. Transmit beamforming and multi-target localization in bistatic MIMO radar[J]. CHINESE JOURNAL OF RADIO SCIENCE, 2012, 27(2): 275-281.

      双基地MIMO雷达发射波束形成与多目标定位

      Transmit beamforming and multi-target localization in bistatic MIMO radar

      • 摘要: 针对双基地多输入多输出(MIMO)雷达目标定位问题,首先提出一种子波束合成(SBS)算法进行发射波束形成,在此基础上提出一种基于并行因子分解(PFD)的多目标定位算法。SBS算法通过对多个发射信号分别加权形成子波束,在空间叠加使发射能量聚焦在感兴趣空域,提高了接收端信噪比。基于PFD的定位算法根据匹配滤波输出的代数结构,利用迭代算法和角度恢复算法估计目标发射角(DOD)和接收角(DOA),且能自动配对,同时避免了二维谱峰搜索、协方差矩阵估计和多次特征分解造成累积误差。结合以上两种算法可有效提高目标定位精度。仿真结果证明了所提算法的有效性和优越性。

         

        Abstract: To solve the problem of target localization in bistatic MIMO radar, firstly, a sub-beam synthesis (SBS) method is proposed for transmit beamforming. Then, aparallel factor decomposition (PFD) based algorithm is presented to locate multi-target.In SBS method, the transmitted waveforms are weighted to form subbeams, which add in the space and focus the transmit energy on the interested space, and improve the signal to noise ratio (SNR).In PFD based algorithm, according to the algebraic structure of the output of matched filter, the target direction of departures (DODs) and direction of arrivals (DOAs) can be estimated with automatic pairing through the iterative algorithm and angle regression methods. This method avoids two-dimensional (2-D) spectrum peak searching, covariance matrix estimating and the accumulation error caused by several eigen-decompositions. Combining the above two approaches, the localization accuracy can be improved significantly.The simulation results are presented to demonstrate the effectiveness and superiority of the proposed method.

         

      /

      返回文章
      返回