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A high robustness positioning algorithm for fingerprint localization system

机译:指纹定位系统的高鲁棒性定位算法

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Fingerprint localization algorithm is widely used in indoor scenario positioning. Received Signal Strength (RSS) is commonly used as the signal feature of fingerprint algorithm. But RSS could be changed due to the temperature or environment reason, which makes it an unreliable signal feature. This paper proposes a novel positioning algorithm based on the formal K Nearest Neighbor (KNN) algorithm. The proposed algorithm enhances the robustness of positioning system take example by the Receiver Autonomous Integrity Monitoring (RAIM) receive technique of Global Navigation Satellite System (GNSS) technologies. Simulation shows the novel algorithm is helpful to avoid the influence of RSS dramatic changes.
机译:指纹定位算法广泛应用于室内场景定位。接收信号强度(RSS)通常用作指纹算法的信号特征。但是,由于温度或环境原因,可能会更改RSS,这使其成为不可靠的信号功能。提出了一种基于形式K最近邻算法的新颖定位算法。该算法以全球导航卫星系统(GNSS)的接收机自主完整性监控(RAIM)接收技术为例,提高了定位系统的鲁棒性。仿真表明,该新算法有助于避免RSS急剧变化的影响。

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