| 顾及有色噪声的自适应粒子滤波UWB定位算法 |
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| 引用本文： | 张园,谭兴龙,赵长胜,李晓明.顾及有色噪声的自适应粒子滤波UWB定位算法[J].测绘通报,2019,0(8):30-33. |
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| 作者姓名： | 张园 谭兴龙 赵长胜 李晓明 |
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| 作者单位： | 江苏师范大学,江苏徐州,221116;江苏师范大学,江苏徐州,221116;江苏师范大学,江苏徐州,221116;江苏师范大学,江苏徐州,221116 |
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| 基金项目： | 江苏省自然科学基金青年基金（BK20150236） |
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| 摘 要： | 传统卡尔曼滤波算法要求噪声模型符合高斯分布，在UWB室内定位中，由于载体本身的机制等干扰，观测噪声不仅仅是白噪声，也存在有色噪声的情况，而粒子滤波可以处理有色噪声的问题。本文通过增加似然分布自适应调整来改进粒子滤波用于目标跟踪的精度，同时研究在白噪声、有色噪声下似然分布自适应调整粒子滤波和拓展卡尔曼滤波在UWB中的优势与不同。试验结果表明：观测噪声为白噪声时，拓展卡尔曼滤波和粒子滤波均可以较好地实现对行人的定位跟踪；观测噪声为有色噪声时，自适应粒子滤波定位效果优于粒子滤波、拓展卡尔曼滤波。
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| 关 键 词： | 有色噪声 卡尔曼滤波 粒子滤波 似然分布自适应 UWB |
| 收稿时间： | 2019-03-17 |
| 修稿时间： | 2019-05-09 |
Adaptive particle filter UWB location algorithms considering colored noise |
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| ZHANG Yuan,TAN Xinglong,ZHAO Changsheng,LI Xiaoming.Adaptive particle filter UWB location algorithms considering colored noise[J].Bulletin of Surveying and Mapping,2019,0(8):30-33. |
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| Authors: | ZHANG Yuan TAN Xinglong ZHAO Changsheng LI Xiaoming |
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| Institution: | Jiangsu Normal University, Xuzhou 221116, China |
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| Abstract: | The traditional Kalman filter algorithm requires that the noise model conforms to the Gauss distribution. In UWB indoor positioning, the observation noise is not only white noise, but also colored noise. Particle filter can deal with the problem of colored noise. The accuracy of particle filter for target tracking is improved by adding adaptive adjustment of likelihood distribution. The advantages and differences of adaptive adjustment of likelihood distribution particle filter and extended Kalman filter in UWB under white noise and colored noise are also studied. The experimental results show that when the observation noise is white, the extended Kalman filter and particle filter can achieve better pedestrian location and tracking; when the observation noise is colored, the adaptive particle filter is better than particle filter and extended Kalman filter. |
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| Keywords: | colored noise Kalman filter particle filter likelihood distribution adaptive UWB |
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