Research On Indoor Localization Technology Based On Information Fusion Of BLE/MIMU

In recent years,the location-based-service(LBS)came into being with the combination of mobile network and satellite positioning technology,which brought a lot of convenience to human's production and life.At present,location-based services in outdoor scenes have matured,while location-based services in indoor scenes are still in the early stage of development.Therefore,both academic and industrial circles have studied the indoor localization technology,and launched a number of representative technologies,such as UWB,Bluetooth and inertial system.Low-Energy-Bluetooth(BLE)has the advantages of low cost,low power consumption and easy deployment,and is widely used in indoor localization.Bluetooth positioning includes two methods: location fingerprint and RSSI ranging.Among them,RSSI-ranging localization method is simple,convenient and easy to realize.However,due to indoor multipath interference,RSSI ranging and positioning has the problems of low accuracy and poor robustness to be solved.Inertial navigation system is independent,stable and has strong anti-interference ability.Miniature-Inertial-MeasurementUnit(MIMU)with small volume and low cost has been developed and used for indoor positioning.However,due to the measurement error of inertial unit,the error of pure inertial navigation localization will accumulate with time.Single localization technology has its own insurmountable defects.It is a current research hotspot to improve the performance of localization system by fusing the data of various localization sensors.Bluetooth And inertial system technology have complementary advantages,and their information fusion localization can improve the localization accuracy and robustness.This paper studies the indoor pedestrian localization technology based on Bluetooth/MIMU information fusion.The main work of this paper is summarized as follows:Firstly,Bluetooth RSSI-ranging is studied,and a ranging model based on Rice channel is proposed,which Preliminary reduces multipath interference and improves ranging accuracy by about 18% and stability by about 17%.In Bluetooth localization algorithm,a strategy of limiting the effective range of observation is proposed,which reduces the error introduction of measurement update and further reduces the multipath interference.The modified model and algorithm improve the positioning accuracy of Bluetooth by about 35%,reaching the level of about 1.5m.Secondly,the pedestrian navigation system based on strap-on strapdown inertial navigation system is studied,and optimized algorithm strategies are adopted,including:gravity initial alignment,fourth-order Runge-Kutta quaternion updating algorithm,MIMU system error model based on first-order Gaussian-Markov process and zero-speed correction algorithm,etc.In the process of positioning calculation,a measurement update algorithm including zero velocity information and yaw tangent information is proposed,which can control the accumulated error of inertial navigation to about 2%.Thirdly,the information fusion localization of Bluetooth and inertial navigation system is studied,and a decentralized fusion algorithm of two-stage cascaded-EKF is proposed by adopting the feature layer fusion strategy.This algorithm reduces the coupling between the calculation amount of positioning solution and subsystems,reduces the accumulated error and fluctuation of positioning,and makes the positioning accuracy reach the level of about 0.26 m.