基于快时间反转变换的雷达目标检测算法

A Radar Target Detection Algorithm Based on Fast-time Reversing Transform

随机脉冲重复间隔雷达具备优良的抗干扰能力,可用于干扰环境下高速机动目标的检测任务。然而,针对这一问题的研究却并不充分。该问题的难点主要在于距离徙动、多普勒频率徙动和非均匀的慢时间采样。针对该问题,文中创新性地提出了一种具备低计算复杂度优点的高速机动目标检测算法。该算法首先通过快时间反转变换来校正距离徙动,然后再采用非均匀相位补偿技术,克服慢时间采样的非均匀性,完成对目标运动参数的估计,进而消除多普勒频率徙动并实现目标回波能量相参积累,随后通过恒虚警检测完成目标检测。最后,通过理论分析评估了所提算法的计算复杂度,并通过仿真实验验证了所提算法的有效性和低计算量优势。

Random pulse repetition interval radars,which possess good anti-jamming abilities,can be utilized for detecting high-speed maneuvering target in electromagnetic interference environments.However,this problem has not been sufficiently studied yet.The difficulties of this problem mainly lay in range migration,Doppler frequency migration,and non-uniform sampling pulses.To tackle this problem,a novel target detection algorithm with the advantage of low computational complexity is proposed in this paper.In the proposed algorithm,fast-time reversing transform is first applied to correct range migration,and then non-uniform phase compensation technique is utilized to overcome non-uniform sampling pulses and to estimate the motion parameters of the target,thus yielding both elimination of Doppler frequency migration and coherent integration of target energy.After the two steps,the Constant False Alarm Rate(CFAR)detection method is employed to achieve target detection.Finally,the computational complexity of the proposed algorithm is evaluated via theoretical analyses,and simulation results illustrate the effectiveness and low computational complexity of the proposed algorithm.