一种鲁棒室内定位的时域特征值方法

G. Godaliyadda, H. K. Garg
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引用次数: 1

摘要

室内环境的危险性质和商业室内定位系统的快速增长使得开发强大的定位技术成为一个重要的重点。我们的工作重点是开发超分辨率技术,在视距条件下提供准确的时间延迟估计,并生成位置信息丰富的指纹,可用于非视距条件下的定位。首先对基于子空间分离的超分辨算法进行了详细的行为分析。然后研究了时域特征值(TD-EV)方法,该方法有效地将时域多信号分类(TD-MUSIC)和频域特征值(FD-EV)算法相结合。这样做是为了确保TD-MUSIC算法的带宽通用性、优越的路径可分辨性和抗噪声性,以及FD-EV在受限条件下重新显示淹没在噪声底下的被低估的局部峰值的能力。这使得TD-EV成为在室内环境中普遍存在的严重多径和噪声条件下准确估计时延的主要候选者。此外,这些属性从基于位置的指纹识别技术的伪频谱输出中提供了一个位置信息丰富的指纹。
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A time domain eigen value method for robust indoor localization
The hazardous nature of the indoor environment and the rapid growth of commercial indoor positioning systems have placed a significant emphasis on developing robust localization techniques. Our work focuses on developing super resolution techniques that can provide accurate time delay estimates under line-of-sight (LOS) conditions and generation of location information rich fingerprints that can be utilized for localization under non LOS conditions. First a detailed behavioral analysis of the subspace separation based super resolution algorithms is presented. Then we examine the newly introduced time domain eigen-value (TD-EV) method which effectively combines the time domain multiple signal classification (TD-MUSIC) and the frequency domain eigen-value (FD-EV) algorithms. This is done to secure the bandwidth versatility, superior path resolvability, and noise immunity of TD-MUSIC algorithm and FD-EV's ability to resurface underestimated local peaks submerged beneath the noise floor under constrained conditions. This makes TD-EV a prime candidate for accurate time delay estimation under severe multi-path and noise conditions prevalent in indoor environments. Additionally, these attributes provide a location information rich fingerprint from the resultant pseudo-spectrum output of our method for location based fingerprinting techniques.
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