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通过分析实际机场旅客定位的特点,提出了一种基于免疫优化的改进DV-Hop定位算法。根据机场定位的复杂环境,将传感器置于登机牌中定位机场旅客;进而将节点定位问题转换为一个最小化定位误差的优化问题,并采用智能免疫优化算法进行求解,设计了适合问题求解的免疫算子,提高了定位的准确率。通过某机场仿真实验数据进行测试,实验结果表明,算法具有较高的定位精度,可以快速而又准确的获得机场内所有旅客的具体位置,并且信标节点的比例越高,通信半径越大,定位误差率越低,能满足旅客定位需求。
By analyzing the characteristics of the actual passenger location of the airport, an improved DV-Hop localization algorithm based on immune optimization is proposed. According to the complex environment of airport location, the sensor is placed on the boarding pass to locate the passengers in the airport. Then the node localization problem is transformed into an optimization problem to minimize the localization error, and the intelligent immune optimization algorithm is used to solve the problem. Immune operator, improve the accuracy of positioning. The experimental results show that the algorithm has high positioning accuracy, and can quickly and accurately obtain the specific location of all passengers in the airport. The higher the proportion of beacon nodes, the larger the radius of communication, The lower the positioning error rate, to meet the needs of passenger positioning.