基于人工鱼群粒子滤波的信号源定位
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。...
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| Published in | 电讯技术 Vol. 56; no. 12; pp. 1370 - 1375 |
|---|---|
| Main Author | |
| Format | Journal Article |
| Language | Chinese |
| Published |
河北省控制工程研究中心，天津300130%河北工业大学 控制科学与工程学院,天津,300130
2016
河北工业大学 控制科学与工程学院，天津300130 |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1001-893X |
| DOI | 10.3969/j.issn.1001-893x.2016.12.012 |
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| Abstract | 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。 |
|---|---|
| AbstractList | 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。 TN97; 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。 |
| Abstract_FL | 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 ar-rival( 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 algo-rithm is conducted under Matlab environment. Experimental results show that the maximum error of loca-tion 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. |
| Author | 杜太行 赵黎媛 江春冬 于晗 |
| AuthorAffiliation | 河北工业大学控制科学与工程学院,天津300130 河北省控制工程研究中心,天津300130 |
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| Author_FL | ZHAO Liyuan DU Taihang YU Han JIANG Chundong |
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| Keywords | 移动监测车 信号源定位 angle of arrival( AOA) mobile monitoring vehicle 粒子滤波 人工鱼群算法 particle filter 波达角 signal source location artificial fish school algorithm |
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| Publisher | 河北省控制工程研究中心，天津300130%河北工业大学 控制科学与工程学院,天津,300130 河北工业大学 控制科学与工程学院，天津300130 |
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| Title | 基于人工鱼群粒子滤波的信号源定位 |
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