| In recent years,location-based service(LBS)has greatly provided more convenience to people's daily lives.With the widespread deployment of indoor Wi-Fi,the daily life is tagged that Wi-Fi is available in every family in the 21st century.The widespread deployment of indoor Wi-Fi has made wireless signals more popular,and it also provides feasibility for the location calculation.In indoor scenes,the global positioning system(GPS)cannot provide accurate location services for people as outdoors as a result of the large number of obstacles and cramped space.More accurate positioning information should be provided to satisfy demands of positioning applications indoor,such as monitoring,supermarket product positioning,calling positioning,traffic condition monitoring and the like.The location information has gradually become an urgent problem in the indoor positioning research.The accuracy of indoor positioning based on conventional radio-frequency signals depends on the signal quality of the receiver.At the same time,signals used for positioning usually contain noise and various errors.The spread conditions of line of sight are much better than indoor conditions,which allow for higher accuracy in open spaces.In the early days,an indoor positioning method based on received signal strength information(RSSI)was rapidly developed.However,the value of this signal is an estimated result with unstable numerical fluctuation and errors,as a result,the positioning accuracy cannot be guaranteed.Compared with RSSI,channel state information(CSI)can also be obtained from common commercial Wi-Fi.CSI has a more fine-grained degree of perception and contains information such as multipath effect,power attenuation and the like.In this case,indoor positioning technology based on CSI signals has become a good choice to solve indoor positioning problems.In this paper,the indoor positioning technology based on channel state information is systematically studied.Based on existing researches,an indoor positioning method based on CSI fingerprint information is proposed,managing to overcome shortcomings of current indoor positioning technologies.In this paper,principles of existing indoor positioning technologies are briefly introduced.Different from traditional technologies using RSSI for positioning,this paper analyzes the characteristics of CSI signals and manage to analyze the influence of human bodies on signals.Secondly,according to characteristics of wireless signal amplitude,an indoor positioning algorithm based on CSI signal channel combination was designed,in which the amplitude data in the communication link was combined.The fingerprint library was established through combined data samples.The weight was calculated through library then uses the Spearman rank correlation coefficient and assigned the weight to the WKNN algorithm to calculate the final positioning information.The system positioning performance of single channel and combined channel,and some existing methods and number of sampling points are compared and analyzed.According to phase characteristics of wireless signals,an indoor positioning algorithm based on phase difference correction of CSI signal is designed.The algorithm focuses on the noise reduction and filtering of phase signals,at the same time,phase data between groups and intra-group data were processed together.At last,the BP neural network is used to train the data to obtain the positioning information.Last but not least,the algorithm mentioned in this paper was verified in the actual scenario.The experimental results showed that the positioning accuracy of two positioning algorithms was significantly higher than that using RSSI signals for positioning.The positioning accuracy is improved compared with other positioning algorithms. |
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