Stagger Pulse Repetition Interval Pulse Train Deinterleaving Algorithm Based on Sequence Association
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摘要: 针对复杂环境下常规直方图信号分选算法对于参差信号分选能力不佳的问题,该文提出一种基于脉冲间隔与单个脉冲关联的直方图算法。该算法根据脉冲间隔与单个脉冲的对应关系建立了脉冲间隔分布矩阵(PIDM),然后通过对PIDM行列的累加计算,得到一种新的直方图,该直方图可避免传统脉冲重复间隔(PRI)变换算法在分选参差信号时对于参差信号帧周期过多抑制的缺陷,且能够通过PIDM对辐射源脉冲串进行序列提取,进而得到参差子序列的周期值。仿真分析结果表明,在不增加计算复杂度的情况下,该算法对存在多部参差辐射源和固定重频辐射源的混合场景仍可保持良好的分选效果。Abstract: For the conventional histogram signal deinterleaving algorithm’s drawback of stagger signal, a histogram algorithm based on corresponding of pulse interval and single pulse is proposed. This algorithm utilizes the corresponding of pulse pair interval and single pulse to get a matrix named Pulse Interval Distribution Matrix (PIDM), and a novel histogram is obtained via cumulating row of the matrix. This histogram can avoid the suppressing of frame period of staggered pulse train caused by Pulse Repetition Intervals (PRI) transform algorithm when staggering signal deinterleaving, and can extract the subsequence of pulse train through PIDM. Simulation results show the algorithm has excellent performance on environment including multi staggered pulse trains with multi-fixed pulse trains under the circumstance of without adding the complexity of calculating.
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表 1 不同信号环境下对比结果
信号环境 ${P_{{\rm{resolv}}}}$ ${P_{{\rm{distc}}}}$ ${P_{{\rm{distcSTG}}}}$ 1参差信号 90.1/–/– 100/–/– 99.7/–/– 1参差1固定 89.5/93.4/85.7 100/93.4/85.7 98.2/–/– 1参差2固定 90.9/48.1/73.0 100/49.8/96.0 94.2/–/– 2参差2固定 82.7/18.4/70.8 98.6/20.2/94.8 91.3/–/– 2参差3固定 48.6/2.7/54.9 97.5/4.9/96.4 80.7/–/– 注:–表示所使用算法无该功能。 -
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