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分析了4种具有代表性的基于辐射源方位线(Lines Of Bearing,LOB)的无源定位算法,即Pages-Zamora定位算法、布朗定位算法、概率定位算法和模糊定位算法。在此基础上提出了融合-迭代定位算法,并进行了蒙特卡罗仿真对比实验,对5种算法的定位精度和运算量进行了比较分析。实验结果表明:融合-迭代定位算法的综合性能优于其他定位算法。
Four representative passive localization algorithms based on Lines Of Bearing (LOB) are analyzed, namely Pages-Zamora localization algorithm, Brown localization algorithm, probability localization algorithm and fuzzy localization algorithm. On this basis, a fusion-iterative positioning algorithm is proposed, and a Monte Carlo simulation comparison experiment is carried out. The positioning accuracy and computation of the five algorithms are compared and analyzed. The experimental results show that the comprehensive performance of fusion-iterative positioning algorithm is better than other positioning algorithms.