The Research Of Indoor Position Algorithm Based On RSSI And PDR Technology

In modern society,positioning technology has become one of the research hotspots in the field of information and communication.Because the global positioning system GPS(Global Position System)signal has weaker penetrating power to the building,the GPS signal cannot cover the interior of the building well.Therefore,the GPS location technology that is already very mature outdoors cannot be applied to indoor positioning.At the same time,the indoor environment is complex,and more shelters and complex activities of indoor personnel have increased the difficulty of indoor positioning.Currently,although the positioning accuracy and deployment difficulty of indoor positioning technology based on wireless signals have basically satisfied indoor positioning requirements,such as Bluetoothbased indoor positioning technology,Wi Fi-based indoor positioning technology,etc.,but due to the complex indoor environment,wireless signals are vulnerable to Disturbance causes the positioning result to fluctuate and affect the positioning accuracy.Therefore,how to improve the anti-jamming capability of indoor positioning technology is the key problem in indoor positioning.Because it is difficult to solve this problem using a single positioning technology,the use of multiple positioning technologies for joint positioning has become the current trend of indoor positioning technology.This dissertation focuses on the research of RSSI-based location fingerprinting technology and PDR location technology for pedestrian tracking,and proposes a fusion strategy for both technologies,which improves the positioning accuracy and system stability.Aiming at the instability of wireless signal propagation in indoor environment,the model of wireless channel propagation path loss cannot accurately reflect the correspondence between distance and signal strength in the actual indoor environment,and the problem of positioning accuracy degradation due to indoor environment changes during actual positioning,etc.,this paper is based on RSSI.The various steps in the location fingerprint indoor positioning algorithm proposed corresponding improvement methods.First,the RSSI correction method is proposed for the environmental deviation caused by the deviation of the Beacon base station itself and the actual environment in which it is located,and the relationship between the RSSI value and the distance in the actual environment is corrected.Afterwards,the KNN algorithm based on spatial filtering is proposed to solve the problem of large amount of calculation of the KNN fingerprint matching algorithm in the location fingerprinting algorithm,which effectively reduces the computational complexity of the algorithm.Finally,for the problem that the KNN fingerprint matching algorithm does not consider the contribution of each reference node to the position when the target terminal is finally calculated,a weighted KNN fingerprint matching algorithm is proposed,which improves the positioning accuracy and is verified by simulation experiments.In order to improve the positioning accuracy and algorithm stability of pedestrian track estimation and location technology,this paper designs a step-frequency detection algorithm and proposes a new step-size estimation model.Firstly,a step-frequency detection algorithm based on the sliding window is designed for the acceleration signal measured by the acceleration sensor in the step-frequency detection.The acceleration signal contains the gravity component of the earth,and there are problems such as sensor noise measurement and body shaking when the pedestrian walks.In the sliding window,the acceleration signal is removed and filtered by the acceleration signal,and the peak frequency detection method and zero cross point method are combined to detect the step frequency.Then,aiming at the problem of large errors in the traditional step size estimation model when the pedestrian step length changes in the step size estimation,a new step size estimation model is proposed,which enhances the relationship between acceleration and step size,and thus better Respond to changes in the pace of pedestrians and improve the positioning accuracy.Finally,experimental verification was performed.Finally,in order to improve the anti-jamming ability of the location fingerprinting technology to the indoor environment,this paper proposes a fusion strategy based on RSSI location fingerprinting and pedestrian track estimation and location technology.In the initial stage of positioning,the RSSI position fingerprinting technique improved in this paper is used to obtain the initial position,and then the pedestrian position is estimated using the improved pedestrian track estimation technique.When the RSSI signal intensity is higher than the threshold,the RSSI position fingerprinting technology is used for the pedestrian track.Calculated positioning results are corrected.Experimental results show that the fusion algorithm can effectively improve the positioning accuracy and stability.