| 摘要: |
| 针对传统粒子滤波算法精度不高、难以满足移动监测车对无线电信号源定位需求的问题，提出了一种基于人工鱼群粒子滤波的信号源定位方法。将人工鱼群算法的优化思想引入到粒子滤波中，通过觅食行为和聚群行为驱动粒子向最优位置移动，改善粒子的分布。结合移动监测车对信号源定位的需要，建立了信号源波达角定位（AOA）的数学模型，在Matlab环境下对人工鱼群粒子滤波算法的信号源定位进行了仿真。实验结果表明，在保证实时性的前提下，该方法定位结果的最大误差为0.101%，定位精度远大于粒子滤波定位方法的估计精度，是一种有效、可行的定位方法。 |
| 关键词: 移动监测车 信号源定位 粒子滤波 人工鱼群算法 波达角 |
| DOI： |
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| 基金项目:工业和信息化部课题（12-MC-KY-14） |
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| Signal source location based on artificial fish school particle filter algorithm |
| DU Taihang,ZHAO Liyuan,JIANG Chundong,YU Han |
| () |
| Abstract: |
| A signal source location method based on artificial fish school particle filter algorithm is proposed to solve the problem of the low precision of particle filter. It employs the optimization idea of artificial fish school algorithm and uses the alternation of behaviors of preying and swarming,which makes particles move towards the optimum area,so particle distribution is improved. Then the mathematical model of angle of arrival(AOA) location is established according to the need of mobile monitoring vehicles for target location. Finally,the simulation analysis of signal source location based on artificial fish school particle filter algorithm is conducted under Matlab environment. Experimental results show that the maximum error of location results of the proposed method is 0.101% on the premise of real-time need,and the location accuracy of the proposed method is better than that of particle filter. It is an effective and feasible location method. |
| Key words: mobile monitoring vehicle signal source location particle filter artificial fish school algorithm angle of arrival(AOA) |
《电讯技术》编辑部 