Design And Implementation Of Pedestrian Inertial Navigation System On IPhone

The location information plays a growing role in people’s daily life, and thelocation-based services (LBS) are in higher demand. Currently, GPS has beencommonly used in outdoor environments. However, signal is susceptible to obstacles,GPS is not suitable for indoor applications. For indoor navigation system, there havebeen some popular technologies and solutions, such as ultrasonic, infrared, radiofrequency identification (RFID), and ultra-wideband (UWB) positioning technology.These positioning technologies have their own advantages and disadvantages, andhow to make better use of these technologies to solve their growing demand fornavigation quickly and accurately has become the current hot issues that must besolved.iPhone has currently become a popular smartphone, integrated with inertialsensors and powerful operating system (iOS). The outstanding characteristics makeiPhone suitable for development of an indoor navigation system using inertia. Whenwalking, waist trajectory in vertical direction is approximately an inverted pendulummodel. Step length can be estimated through gait cycle segmentation and verticaldisplacement of waist. Magnetic data can be used to determine the walking direction.Magnetic force can be decomposed into horizontal and vertical vectors anddetermining traveling direction is through horizontal component vector of themagnetic force. Combining step length and direction can obtain travelingdisplacement vector. Thus the implementation of two-dimensional indoor navigationcan be achieved. Based on the powerful features of iPhone, the thesis presents ascheme of pedestrian inertial navigation system on iPhone and introduces the methodof testing acceleration, magnetic data and data processing algorithms.In order to verify the proposed inertial navigation algorithm, the thesis designsthe corresponding navigation software on iPhone platform. The experimental resultsshow that the proposed indoor navigation scheme and software can display the user’sposition on the map in real time. The measurement results show high level ofaccuracy, and the error is about5%within a short period of time.