CAJ | 학술논문

针对单脉冲雷达处理同一分辨单元内密集多目标回波时收敛较慢的问题，提出了一种将 Metropolis算法和最小描述长度（MDL）准则相结合的密集多目标分辨算法。构建 Metropolis 算法中的更新函数和迭代规则，促使待估参数的不同马尔可夫链间的融合；根据融合判定规则选取抽样样本，估计出对应的目标参数；利用 MDL 准则实现密集目标的准确分辨。该算法不仅提升了收敛速度，而且具有较高的参数估计精度，提高了算法在多目标下的分辨性能。仿真结果验证了所提算法的有效性和可行性。
침대단맥충뢰체처리동일분변단원내밀집다목표회파시수렴교만적문제，제출료일충장 Metropolis산법화최소묘술장도（MDL）준칙상결합적밀집다목표분변산법。구건 Metropolis 산법중적경신함수화질대규칙，촉사대고삼수적불동마이가부련간적융합；근거융합판정규칙선취추양양본，고계출대응적목표삼수；이용 MDL 준칙실현밀집목표적준학분변。해산법불부제승료수렴속도，이차구유교고적삼수고계정도，제고료산법재다목표하적분변성능。방진결과험증료소제산법적유효성화가행성。
When multiple targets' echoes fall into the same resolution cell of monopulse radar , the echoes are distinguished at a slow rate of convergence using the available processing algorithm . Aiming at this problem , a new processing algorithm is presented , which combines the Metropolis algorithm with minimum description length ( MDL) criteria . Constructing the update function and the rule of iteration can improve the convergence of the different markov chains of parameters estimation . Then , by using the fusion decision rule , valid samples are selected to calculate the parameters . Lastly , the numbers of multiple unresolved targets are calculated by using minimum description length criteria . The proposed algorithm has not only a higher rate of convergence , but also a better resolution capability under multiple targets with a more accurate parametric estimation . The efficacy and feasibility of the method are verified by simulation .