Open Access Open Access  Restricted Access Subscription or Fee Access

Improved Kalman Filter Based LAR in Vehicular Ad Hoc Network

(*) Corresponding author

Authors' affiliations



Vehicular Ad hoc Network (VANET) is a subclass of ad hoc networks and a special type of mobile ad hoc network (MANET). Due to the highly dynamic and ever-changing topology and multi-path challenges of the Global Positioning System (GPS), accurate prediction is often difficult, especially when ignoring the movement of nodes in VANETs. This research proposes a Kalman filter based Location Aided Routing (KALAR) to improve prediction accuracy in VANET. The aim of the article is to improve the accuracy of Kalman by adding an awareness component to the nature of the vehicle maneuver prediction in VANET environments.  A location prediction model for VANET, incorporating the constraint of vehicle movement was developed. Simulation results showed that the KALAR improved prediction accuracy. Packet Delivery Ratio (PDR) was at 95% with a smaller network overhead. In addition to this, KALAR was compared to other experiments: Location-aided routing (LAR) with and without a model driven tracer. Results showed that the KALAR significantly outperformed the other experiments.
Copyright © 2016 Praise Worthy Prize - All rights reserved.


Kalman Filter; Location Aided Routing; Predication Accuracy; Vehicular Ad Hoc Network

Full Text:



F. Cunha, L. Villas, A. Boukerche, G. Maia, A. Viana, R. A. F. Mini, and A. A. F. Loureiro, “Data communication in VANETs: Protocols, applications and challenges,” Ad Hoc Networks, vol. 44, pp. 90–103, 2016.

Abbas, M., Taharem, N., Al-Jemeli, M., Vehicle’s Direction Determination Protocol via VANET, (2016) International Review of Automatic Control (IREACO), 9 (3), pp. 161-166.

Hosam, O., Car License Plate Localization Using Hole Filling and Support Vector Machine Approach, (2014) International Review on Computers and Software (IRECOS), 9 (10), pp. 1760-1766.

Mesmoudi, A., Feham, M., Labraoui, N., Bekara, C., An Efficient Area-Based Localization Algorithm for Wireless Sensor Networks, (2015) International Review on Computers and Software (IRECOS), 10 (10), pp. 1062-1070.

H. Feng, C. Liu, Y. Shu, and O. W. W. Yang, “Location Prediction of Vehicles in VANETs Using A Kalman Filter,” Wirel. Pers. Commun., vol. 80, no. 2, pp. 543–559, 2014.

Nemri, N., Ghayoula, R., Badri, H., Trabelsi, H., Gharsallah, A., Wireless Localization Using TDOA-DOA, (2015) International Journal on Communications Antenna and Propagation (IRECAP), 5 (6), pp. 354-361.

G. Xue, Y. Luo, J. Yu, and M. Li, “A novel vehicular location prediction based on mobility patterns for routing in urban VANET,” EURASIP J. Wirel. Commun. Netw., vol. 2012, p. 222, 2012.

N. Drawil, “Improving the VANET Vehicles ’ Localization Accuracy Using GPS Receiver in Multipath Environments,” Master thesis, University of Waterloo, 2007.

Sassi, H., Najeh, T., Liouane, N., The Hybrid Technique for Improvement DV-Hop Localization Algorithms, (2016) International Journal on Communications Antenna and Propagation (IRECAP), 6 (2), pp. 96-102.

D. Deb, S. Roy, and N. Chaki, “LACBER: a new location aided routing protocol for GPS scarce MANET,” Int. J. Wirel. Mob. Networks, vol. 1, no. 1, pp. 22–36, 2009.

Kumar, K., Kanthavel, R., Road Extraction from Satellite Images Using Unscented Kalman Filter and Gauss-Hermite Kalman Filter, (2013) International Review on Computers and Software (IRECOS), 8 (9), pp. 2102-2112.

Ramachandran, P., Murukanantham, D., A Location Based-Energy Aware Routing Approach for Mobile Ad Hoc Networks, (2014) International Journal on Communications Antenna and Propagation (IRECAP), 4 (4), pp. 114-123.

Y. Zhao, GPS / IMU Integrated System for Land Vehicle Navigation based on MEMS, no. September. 2011.

T. Anagnostopoulos, C. Anagnostopoulos, S. Hadjiefthymiades, M. Kyriakakos, and A. Kalousis, “Predicting the location of mobile users: a machine learning approach,” Proc. 2009 Int. Conf. Pervasive Serv., pp. 65–72, 2009.

H. Menouarand, M. Lenardi, and F. Filali, “Movement Prediction-based Routing (MOPR) concept for position-based routing in vehicular networks,” IEEE Veh. Technol. Conf., pp. 2101–2105, 2007.

A. Husain, B. Kumar, and A. Doegar, “A Study of Location Aided Routing ( LAR ) Protocol for Vehicular Ad Hoc Networks in Highway Scenario,” Int. J. Eng., vol. 2, no. 2, pp. 118–124, 2010.

Y. Mo, D. Yu, J. Song, K. Zheng, and Y. Guo, “Vehicle Position Updating Strategy Based on Kalman Filter Prediction in VANET Environment,” Discret. Dyn. Nat. Soc., vol. 2016, 2016.

J. Meng, H. Wu, H. Tang, and X. Qian, “An Adaptive Strategy for Location-Aided Routing Protocol in Vehicular Ad Hoc Networks,” 2013 Seventh Int. Conf. Innov. Mob. Internet Serv. Ubiquitous Comput., pp. 405–410, 2013.

A. Fakharian, T. Gustafsson, and M. Mehrfam, “Adaptive Kalman filtering based navigation: an IMU/GPS integration approach,” Networking, Sens. …, no. April, pp. 11–13, 2011.

M. Wu, W. K. G. Seah, and L. W. C. Wong, “A Link-Connectivity-Prediction-Based Location-Aided Routing Protocol for Hybrid Wired-Wireless Networks”, Second International Conference on Mobile Computing and Ubiquitous Networking (ICMU 2005), April 13 - 15, 2005, Osaka, JAPAN.

Arulaalan, M., Nithyanandan, L., Dual Band Triangular Microstrip Antenna for WLAN/WiMAX Applications, (2016) International Journal on Communications Antenna and Propagation (IRECAP), 6 (3), pp. 132-137.

Nandakumar, S., Khara, S., Velmurugan, T., Preetha, K., Priority Based Call Admission Control in Integrated 3G/WLAN Mixed Cell, (2015) International Journal on Communications Antenna and Propagation (IRECAP), 5 (2), pp. 98-105.

Samarah, K., Mobile Positioning Technique Based on Timing Advance and Microcell Zone Concept for GSM Systems, (2016) International Journal on Communications Antenna and Propagation (IRECAP), 6 (4), pp. 211-221.


Please send any question about this web site to
Copyright © 2005-2024 Praise Worthy Prize