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- W2907653979 abstract "Traditional IMU based PDR systems suffer fromrapidly growing drift effects due to the inherent bias of theinertial sensor. Many existing solutions to mitigate this problemuse aiding sensors or information as heuristics or map data. Wepropose a new optimization framework to solve the PDR estimationproblem where the sensors biases are explicitly included asstate variables and therefore be used to correct for bias effectsin the PDR. By using a smoothing approach and exploiting therigid structure of a MIMU array one can solve for the slowlyvarying sensor biases. This paper presents the method and givesan exemplary result of a walking trial. Good agreements in theposition and orientation with an optical reference system werefound. Moreover, accelerometer and gyroscope biases could beestimated accordingly. Further research includes the performanceof more experiments under various conditions such that amore quantitative evaluation can be obtained. In addition, anexploration of a (pseudo) realtime filter version would be valuablesuch that the system can be applied online." @default.
- W2907653979 created "2019-01-11" @default.
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- W2907653979 date "2018-09-01" @default.
- W2907653979 modified "2023-09-26" @default.
- W2907653979 title "MIMU PDR with bias estimation using an optimization-based approach." @default.
- W2907653979 hasPublicationYear "2018" @default.
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