Research On Cooperative Positioning Methods For High Precision Indoor Positioning

At present,location-based service plays an increasingly prominent role in areas such as national defense,transportation,and public security.However,it is estimated that about 70% of people's live time is indoor,thus the demand for indoor positioning is more urgent than outdoors.Although various means such as Wi-Fi,Bluetooth,Ultra Wideband(UWB),and Radio Frequency Identification(RFID)can be applied to indoor positioning,it is difficult to provide the integrated indoor and outdoor high-precision positioning due to the limitation of the cost and the hindering range.The traditional honeycomb network has such prominent advantages as wide coverage and low cost,and has been widely used in the outdoor positioning environment.Currently,the cellular network is considered as a core component of indoor positioning under the condition of integrated communications and navigation in the era of 5G.However,the positioning error of the traditional cellular network is affected by the non-line-of-sight problem and a large error occurs.Therefore,the target that the user needs a high-precision positioning service can not be achieved.That is,the positioning error is about 1m in a simple environment and less than 3m in a multipath environment.Therefore,this paper proposes a positioning collaboration scheme between terminals in heterogeneous networks,and designs and implements indoor collaborative positioning based on spatial analysis to improve the accuracy of positioning algorithm and meet the location requirements in an indoor environment.The main work of the dissertation is as follows:First of all,in view of the lack of line-of-sight(LOS)reference signals and large positioning errors in indoor positioning environment,this paper proposes an indoor cooperative positioning model based on spatial analysis and implements the corresponding algorithm.Based on the traditional collaborative positioning theory,spatial partitions are established according to the characteristics of the indoor scene,so that the nodes in the direct positioning area receive fixed reference point signals satisfying the quantity of positioning conditions.Therefore,a two-stage collaborative positioning algorithm is proposed to solve the problem that the non-line-of-sight environment collaborative zones can not be located according to the different types of spatial linkage.Secondly,two additional reference point selection algorithms are proposed for the extra error introduced by the redundant reference node signals received in the indoor scene.The reference point selection problem is considered under the condition of insufficient number of fixed reference points and redundancy respectively.Further inhibit the coordination of positioning errors.Aimed at the lack of fixed reference points,a reference point selection strategy based on neighborhood weighted reference point selection algorithm is proposed.Aiming at the situation that the fixed reference point is sufficient,the feature based on history selection records is proposed,and the most similar reference point combination scheme is selected.The implementation of the two schemes respectively solves the interference effect of the mobile reference point with large position error and the fixed reference point with large ranging error on the positioning result,and further improves the accuracy of collaborative positioning in the indoor environment.Finally,aiming at the localization of nodes under moving conditions,a collaborative positioning optimization method considering the mobility of nodes is proposed.For the cooperative positioning problem of the target node in the indoor scene under the mobile situation,a cooperative positioning scheme based on the error correction of the signal coverage of the reference node is proposed.Experimental results show that this method can effectively reduce the positioning error when the node moves.