Indoor localization algorithm based on mixed H2/H∞ filtering information fusion
In combined indoor localization model of received signal strength indication(RSSI)fingerprint localization and pedestrian dead reckoning(PDR),a fusion localization method based on hybrid H2/H∞ filtering is proposed,aiming at the influence of noise error and model error on fusion localization.Due to multi-path propagation,attenuation,non-line-of-sight(NLOS)influence of indoor signals and sensor precision problems,the system or observation noise often does not conform to the prerequisite of assumptions of Kalman filtering,resulting in poor filtering robustness.H∞ filtering does not make assumptions about noise characteristics and model errors,and has a certain anti-interference ability,but due to result is conservative,the precision is slightly lower.Mixed H2/H∞ filtering takes into account the characteristics of both,and provides an equilibrium in precision and robustness.Fusion positioning performance of three filtering is compared by simulation experiment.Experimental results show that the mixed H2/H∞ filtering effectively improves the precision and robustness of the fingerprint/PDR integrated indoor positioning system.
indoor positioningmulti-source information fusionmixed H2/H∞ filteringfingerprint positioningpedestrian dead reckoning(PDR)
NETL
NSTL
万方数据
维普
