Pedestrian Dead Reckoning pada Ponsel Cerdas sebagai Sistem Penentuan Posisi dalam Ruangan

Azkario Rizky Pratama, Widyawan Widyawan

Abstract


Abstract— Nowadays, personal positioning systems are more necessary to build many location-based services. Pedestrian Dead Reckoning (PDR), which is a pedestrian positioning technique using the accelerometer sensor to recognize pattern of steps, is an alternative method that has advantages in terms of infrastructure-independent. However, the variation of walking pattern on each individual will make some difficulties for the system to detect displacement. This is really interested authors to develop a sensor-based positioning system that applied generally to all individuals. In the test, 15 test subjects was taken with the distance of each 10m, 20m and 30m.
Experiment begins with the feasibility test of accelerometer sensor. In this work, a smartphone with average sampling rate 63.79 Hz and standard deviation of 1.293 is used to records the acceleration. Then, the acceleration data are analyzed to detect step and to estimate the travelled distance using several methods. Detection of steps are able to make an average error of 2.925%, while the most nearly correct displacement estimation is using Scarlet experimental method which is make a distance average error of 1.39metres at all the traveled distance.

Intisari— Sistem penentuan posisi personal kini semakin banyak dibutuhkan untuk membangun berbagai macam layanan berbasis lokasi (location based services). Pedestrian Dead Reckoning (PDR), yang merupakan teknik penentuan posisi pejalan kaki dengan memanfaatkan sensor akselerometer untuk mengenali pola langkah, memiliki kelebihan dalam hal ketidaktergantungannya pada infrastruktur tertentu. Namun, variasi pola berjalan pada setiap individu akan menyulitkan sistem ini untuk mendeteksi perpindahan. Hal ini merupakan sebuah pendorong bagi penulis untuk mengembangkan sebuah sistem penentuan posisi berbasis sensor yang berlaku umum bagi seluruh individu. Dalam pengujian, diambil 15 sampel dengan jarak tempuh masing-masing 10m, 20m, dan 30m.
Eksperimen diawali dengan uji kehandalan sensor akselerometer. Pada penelitian ini, sebuah ponsel dengan sampling rate 63.79 Hz dan standar deviasi 1.293 digunakan untuk merekam akselerasi. Kemudian, pada data akselerasi dilakukan deteksi langkah dan estimasi perpindahan menggunakan beberapa metode. Deteksi langkah mampu menghasilkan rata-rata kesalahan sebesar 2.925%, sedangkan estimasi perpindahan yang paling akurat adalah dengan menggunakan metode Scarlet yang mampu menghasilkan kesalahan estimasi rata-rata 1.39m pada semua jarak tempuh.

Kata Kunci— pedestrian dead reckoning, teknik penentuan posisi berbasis sensor, ponsel cerdas.


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References


Dulya, B., “GSM-Positioning - Outdoorpositioning: Technologies, Characteristics, and Limitations,” April 2012. [Online]. Available: http://www.ks.uni-freiburg.de/

S. Beauregard and H. Haas, “Pedestrian Dead Reckoning : A Basis for Personal Positioning,” in Proceedings of the 3rd Workshop on Positioning, Navigation and Communication, pp. 27-35, 2006.

A. R. Jimenez, F. Seco, C. Prieto, and J. Guevara, “A comparison of Pedestrian Dead-Reckoning algorithms using a low-cost MEMS IMU,” in 6th IEEE International Symposium on Intelligent Signal Processing, 2009.

J. W. Kim, H. J. Jang, D-H. Hwang, and C. Park, “A Step, Stride and Heading Determination for the Pedestrian Navigation System,” Journal of Global Positioning Systems, pp. 273-279, 2004.

Y. Jin, H-S. Toh, W-S. Soh, and W-C. Wong, “A Robust Dead-Reckoning Pedestrian Tracking System with Low Cost Sensors,” in IEEE International Conference on Pervasive Computing and Communications, pp. 222-230, 2011.

I. Bylemans, M. Weyn, and M. Klepal, “Mobile Phone-based Displacement Estimation for Opportunistic Localisation Systems,” in Third International Conference on Mobile Ubiquitous Computing, Systems, Services and Technologies, 2009.

S. Ayub, X. Zhou, S. Honary, A. Bahraminasab, and B. Honary, “Indoor Pedestrian Displacement Estimation Using Smart phone Inertial Sensors,” Int. J. Innovative Computing and Applications., vol. 4, pp. 35-42, 2012.

S. H. Shin, C. G. Park, J. W. Kim, H. S. Hong, J. M. Lee, “Adaptive Step Length Estimation Algorithm Using Low-Cost MEMS Inertial Sensors,” in IEEE Sensors Applications Symposium, 2007.

H. Weinberg, “Using the ADXL202 in Pedometer and Personal Navigation Applications,” Analog Devices AN-602 Application Note, 2002.

J. Scarlet, “Enhancing the Performance of Pedometers Using a Single Accelerometer,” Analog Devices AN-900 Application Note, 2005.




DOI: http://dx.doi.org/10.22146/jnteti.v2i3.76

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