Research On Indoor Localization And Target Tracking Technology Based On WiFi

In recent years,with the rapid development of indoor wireless network application technology and the popularity of wireless access(AP)devices,indoor positioning technology based on Wi Fi signals has become a research hotspot in academic and industrial circles.At present,the indoor positioning algorithms proposed in the literature emerge in an endless stream,but generally two main methods are indispensable: The first one is an indoor positioning method based on position fingerprints.The method has high feasibility and low complexity,and the effect of positioning is better in the environment who has not too much changes.The positioning accuracy increases with the increase of the collection density of the position fingerprint,so when a certain positioning accuracy is ensured,the positioning efficiency will decrease with the increase of the positioning area;the second is the distance-based indoor positioning method.The positioning accuracy of the method depends on the accuracy of the distance measurement.When the distance between the transmitter end and the receiver can be accurately measured,the positioning method can obtain a better positioning result.In addition,the method does not require prior personnel labor input to collect a large number of offline data,and the method can adapt to the changes in the environment.However,the indoor environment is complex,and the paths of the Wi Fi signal to the receiver are variable.So it is difficult to find the accurate relationship between the received signal strength and distance.Although the indoor positioning method based on position fingerprint can obtain high indoor positioning accuracy,there is a tradeoff between the amount of fingerprint information and positioning accuracy.Although the distance-based trilateral positioning method can get rid of a large number of preparations in the offline phase,there is a certain error in the estimation of the distance between the transmitter and the receiver.So,it is difficult to obtain ideal indoor positioning effect by simply using position fingerprint or distance estimation method.Therefore,an improved indoor positioning method is proposed in this paper.Firstly,the position fingerprint information of the main indoor location is collected in the off-line stage,and the position fingerprint information is divided according to the strongest received signal strength,the orientation of the receiver and the time of position to reduce the fingerprint matching time.At the same time,using the collected Wi Fi information to fit the RSS-distance formula.Then,in the online phase,the WiFi signal received by the receiver and sensor information are used for fingerprint establishment,matching,distance estimation,and the trilateral positioning.Finally,using the results of the trilateral positioning,the weighted average of the first K results of fingerprint positioning is calculated to obtain the location information of the receiver.Through the simulation in various indoor environments,the effectiveness of the proposed positioning algorithm is verified.The research of indoor target tracking technology has also received more and more attention.This paper mainly uses the filtering technology to study the indoor target tracking problem,combining indoor environment and equipment characteristics.First,the principle of Kalman filter and particle filter is introduced,and the algorithm flow of the filter and its applicable scene are given.Secondly,combined with the positioning results of the indoor positioning method proposed in this paper,a particle filtering algorithm for indoor moving target tracking is given.Then,considering the diversity of indoor target motion patterns,interactive multi-model particle filter technology was introduced to track indoor targets.Finally,according to the environment and equipment characteristics of indoor tracking,a further improved tracking method is proposed,the method identifies the target motion model through the sensor data of the device,and then applies the Kalman filter and the particle filter to the linear motion model and the nonlinear motion model,respectively.At last,the tracking simulations demonstrated that the proposed method can track the indoor moving target within 1 meters of error.