一种距离模糊下三维空间高超声速弱目标HT-TBD算法

A Hough Transform TBD Algorithm in Three-Dimensional Space for Hypersonic Weak Target under Range Ambiguity

针对雷达测距模糊条件下临近空间高超声速弱目标的检测跟踪问题,提出一种基于分时多重频多假设的分级降维HT-TBD算法。首先,为重构因距离模糊而丢失的目标时空相关性,利用多种脉冲重复频率分时交替工作并对各时刻的距离模糊量测在所有多假设区间进行距离延拓;然后,为了在保证检测性能的同时减小计算量,将延拓后的三维点迹依次降维映射至径向距离-时间、方位角-时间和仰角-时间平面进行三级二维Hough变换,并在每级采用非相参积累和二值积累相结合的双重积累方式进行点迹筛选以在充分利用点迹能量信息的同时尽量减小强干扰的影响。仿真结果表明,该算法可在距离模糊条件下对临近空间高超声速弱目标进行有效检测跟踪,并同时实现距离解模糊。

To address the problem of detection and tracking for the near-space hypersonic weak targets under range ambiguity,a novel hierarchical and dimension-decreasing Hough transform track-before-detect（ TBD） algorithm is proposed based on the multiple pulse repetition frequencies（ PRF） and range multi-hypothesis processing with timesharing. Firstly,to rebuild the lost space-time relativity of the target points under range ambiguity,different PRFs are utilized alternately at different times and measurements with range ambiguity are extended to all range multi-hypothesis intervals. Then,the three-dimensional measurements after range extension are mapped into the range-time plane,azimuthtime plane and elevation-time plane by turns before two-dimensional Hough transform in each plane to ensure the great detection performance and decrease the calculation load. In addition,point selection is conducted by the double integration means of the non-coherent integration and binary integration to decrease the impact from the strong interference and utilize the energy information of points simultaneously. Simulation results demonstrate the effectiveness of the proposed algorithm.