Practical Step Length Estimation Combining FM Radio Signal and Accelerometer
- 所属单位：北京航空航天大学
- 发表刊物：IEEE Transactions on Instrumentation and Measurement
- 关键字：Frequency modulation, machine learning (ML),pedestrian dead reckoning (PDR), regression model, step length estimation (SLE)
- 摘要：Among various indoor positioning methods, pedestrian dead reckoning (PDR) has become one of the mainstream methods for requiring neither expensive infrastructure nor laborious surveys. Step length estimation (SLE) is one of the key components of PDR. Most of the existing SLE methods utilize acceleration or angular velocity to estimate the step length, which are susceptible to the measurement noise of low cost inertial sensors as well as different walking speeds and persons. In this article, we propose an SLE method based on the adaptive combination of frequency-modulated (FM) radio signal and acceleration, which considers both accuracy and practicality.First, based on the propagation model theory of radio signals,we derive the relationship between the received signal strengthindicator (RSSI) of FM signal and step length, which provides the theoretical basis for the proposed SLE algorithm. Second, FM signal features related to step length are extracted. Third, since the availability of FM signal depends on the type of scenes, an availability assessment strategy is proposed, enabling the utility in various scenes. Finally, with the assistance of
availability assessment results, we apply support vector regression
(SVR) to realize SLE by combining the FM signal features and
acceleration features adaptively. Field experiments conducted by
14 experimenters in different indoor scenes validate that the
introduction of FM signal features effectively reduces the SLE
errors, thus improving the positioning performance.
- 论文类型：期刊论文
- 一级学科：信息与通信工程
- 文献类型：期刊
- 是否译文：否
- 收录刊物：SCI
附件：
2023-TIM Practical Step Length Estimation Combining FM Radio Signal and Accelerometer.pdf
