International Journal of Electrical and Electronics Research ISSN 2348-6988 (online) Vol. 3, Issue 1, pp: (118-132), Month: January - March 2015, Available at: www.researchpublish.com Page | 118 Research Publish Journals Compact GPS/Inertial Platform for Wireless Motion Data Capture and Trajectory Reconstruction Gianluca Borgese 1 , Calogero Pace 2 , Luigi Rizzo 3 , Giuseppe Artese 4 , Michele Perrelli 5 , Roberto Beneduci 6 1,2,3 Department of Computer Engineering, Modeling, Electronics and Systems Science (DIMES), University of Calabria, Arcavacata di Rende (CS), 87036, Italy 4,5 Department of Town-and-Country Planning, University of Calabria, Arcavacata di Rende (CS), 87036, Italy 6 Department of Mathematics, University of Calabria, Arcavacata di Rende (CS), 87036, Italy Abstract: This work illustrates an educational project flow of an electronic system. This system is developed to support applications in which there are the need to measure motion parameters and transmit them to a remote unit for real-time teleprocessing. In order to be useful in many operative contexts, the system is flexible, compact, and lightweight. It integrates a tri-axial inertial sensors, a GPS module, a wireless transceiver and can drive a pocket camera. Data acquisition and packetization are handled in order to increase data throughput on radio bridge and to minimize power consumption. A trajectory reconstruction algorithm, implementing the Kalman- filter technique, allows to obtain real-time body tracking using only inertial sensors. Thanks to a graphical user interface it is possible to remotely control the system operations and to display the motion data. Following this detailed design procedure it is possible to reproduce this platform easily adapting it to your own aim. Keywords: GPS, Kalman filter, MEMS inertial sensors, wireless communication. I. INTRODUCTION Nowadays, in many research fields such as body motion recognition (BMR), fall detection (FD), aerial photogrammetry (AP), inertial navigation (IN), etc, there is the necessity to acquire and wireless transmit all body motion parameters (axial accelerations, angular rates, global position, speed, etc.) to a remote host system for tracking and control purposes. With regard to BMR [1], [2] and FD [3], there are several areas of interest (e.g.: 3D virtual reality, biomedical applications, robotics) in which it is extremely important to detect human body movements, in order to measure, recognize or reproduce them using a robot. AP [4] and IN [5], [6] fields are older than BMR and FD, but a number of different and innovative applications can still be found, such as pedestrian navigation in harsh environments [7], agriculture automated vehicles [8], [9], or animal motion analysis [10]. Although several kind of similar systems can be found in the market [11], [12], they are usually highly specialized for a particular application and not very flexible. Some systems use high performance and high cost devices, others are not wireless-based or are too heavy. The main idea followed in this work was to design a low-cost, complete and flexible system which can be customized for several applications. This system should be powerful, compact and lightweight. II. SYSTEM DESIGN STRATEGY To reach these features it is necessary to carefully design the system architecture and to select the components in order to save space and to decrease system weight as much as possible. In the market there are many kind of high performance inertial measurement units (IMU), such as the HoneyWell HG900 but they do not fulfil our requirements of small size, low weight and low cost. In our prototype we chose the ADIS16350 module, a MEMS IMU that integrates a tri-axial