基于多普勒频偏估计的单帧图像低速运动目标检测方法

常用的图像域运动目标检测跟踪方法对虚警率较敏感，当虚警率较高时，目标检测跟踪的实时性受限。为了降低目标初始检测的虚警率，进而提高目标检测跟踪的实时性，该文提出一种基于多普勒频偏估计的单帧图像低速运动目标检测算法，通过发射多普勒不敏感的LFM脉冲对，忽略多普勒效应对成像结果的影响，但在图像域检测的同时，利用目标回波的多普勒频偏信息进行静目标和杂波亮点的剔除，基于单帧数据，减小运动目标检测的虚警率，实现单帧图像的运动目标检测，从而为目标跟踪奠定良好基础。该算法首先进行图像域的恒虚警检测，再利用宽带时域波束形成和复相关频率测量法，对检测亮点处的波束输出信号进行多普勒测频，仅通过单帧图像就可有效剔除静目标和杂波亮点。同时为了改善宽带时域波束形成的性能，利用2阶锥规划设计滤波器的系数，用9阶FIR滤波器实现了0.01倍采样点的小数时延，提高了多普勒频偏的估计精度。最后通过计算机仿真和水池试验验证了所提算法的有效性。

Low-speed Moving Target Detection of Single Frame Image Based on Doppler Shift Estimation

The regular algorithms of target detection and tracking in image domain are very sensitive to the false alarm rate, and the real time performance of target detection and tracking is limited with high false alarm rate. In order to reduce the false alarm rate of original target detection and improve the real time performance, an algorithm of low-speed moving target detection of single frame image based on Doppler shift estimation is proposed. Through transmitting LFM plus pair signal which is non-sensitive to the Doppler shift, the influence on image by Doppler shift can be ignored. But during the detection in image domain, the Doppler shift of target echo is used to remove static targets and clutter highlights. The false alarm rate of moving target detection is reduced based on single frame data, the moving target detection is achieved through a single frame image to make a good foundation for target tracking later. First, the CFAR determination in image domain is carried out in the algorithm. Then, the Doppler shift of the beamforming signal at the highlights detected is estimated through time-domain broadband beamforming and complex correlation frequency measurement. The static targets and clutter highlights are removed effectively through single frame image. In order to improve the performance of time-domain broadband beamforming, the filter coefficients are designed by second order cone programming. The 0.01 times sampling point of the fractional delay is achieved by a 9-order FIR filter and the estimation accuracy of the Doppler shift is improved. The validity of the proposed method is verified by the computer simulation and pool experiment.