通信学报 ›› 2016, Vol. 37 ›› Issue (1): 28-34.doi: 10.11959/j.issn.1000-436x.2016004

• 学术论文 • 上一篇    下一篇

稳定分布噪声下基于粒子滤波的双站伪多普勒定位方法

邱天爽,戚寅哲   

  1. 大连理工大学电子信息与电气工程学部,辽宁 大连 116024
  • 出版日期:2016-01-25 发布日期:2016-01-27
  • 基金资助:
    国家自然科学基金资助项目;国家自然科学基金资助项目;国家自然科学基金资助项目;国家科技支撑计划基金资助项目

Dual-station pseudo-Doppler localization method based on particle filtering with stable distribution noise

shuang QIUTian,zhe QIYin   

  1. Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian 116024, China
  • Online:2016-01-25 Published:2016-01-27
  • Supported by:
    The National Natural Science Foundation of China;The National Natural Science Foundation of China;The National Natural Science Foundation of China;The National Key Technology R&D Program

摘要:

传统的伪多普勒测向算法在高信噪比和高斯噪声环境下能较为精确地计算出到达方位角,但对于稳定分布噪声的顽健性较差。针对以上不足,提出了一种基于粒子滤波的双站伪多普勒定位方法。用粒子滤波对2个接收机的来波方位角进行联合估计,并通过非线性映射得到信源位置坐标估计,实现了方位角计算与双站定位的集成。仿真实验表明,当稳定分布参数 a 为1.4(中等脉冲程度)时,所提方法在低信噪比下的顽健性要显著优于传统方法,在高信噪比时估计精度与传统方法相当;当信噪比为10 dB时,所提方法在a<1.9的情况下定位精度远高于传统方法。

关键词: 稳定分布噪声, 粒子滤波, 双站定位, 伪多普勒, 测向

Abstract:

Traditional pseudo-Doppler bearing estimation algorithm could accurately calculate the angle of arrival (AOA) with Gaussian noise and high signal to noise ratio (SNR), but it was less robust with stable distribution noise. To over-come these shortcomings, a dual-station pseudo-Doppler localization method based on the particle filtering was proposed. The method employed particle filtering approach to jointly estimate the AOA of both stations, then applied a non-linear mapping to acquire the source location, forming an int tion of AOA calculation and dual-station localization. Simula-tions demonstrate that when the characteristic exponent of the stable distribution is in a medium degree, for example a=1.4, the proposed method is much more robust than the traditional method in low SNR circumstances, while main-taining the estimation accuracy of the traditional method when SNR is high. When SNR equals 10 dB, the positioning accuracy of the proposed method is much higher than the traditional method with a<1.9 .

Key words: stable distribution noise, particle filtering, dual-station localization, pseudo-Doppler, bearing estimation

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