VEHICLE KINEMATIC PARAMETERS ESTIMATION USING MODIFIED LINEAR KALMAN FILTER
Published In: INTERNATIONAL CONFERENCE ON RECENT TRENDS IN COMPUTING AND COMMUNICATION ENGINEERING
Author(s): DNYANESHWAR V AVATIRAK , N.S.JADHAV , S.L. NALBALWAR
Abstract: This paper proposes a system that can estimate kinematic parameters of the target vehicle like location, velocity, and acceleration to avoid possible vehicle collision. Kinematic parameters are extracted from radar signal with appropriate waveform modulation. Hybridlinearfrequencymodulation (LFM) and frequency- shiftkeying(FSK) is used in radar so that more than one target is detected with high range resolution and high time update. Extracted kinematic parameters are than process using Modified Linear Kalman Filter (MLKF) along with trilateration process. Extended Kalman Filter (EKF) is also use to compare response of the two systems. Sensor network is useful for 360 degree protection of individual car. Sensors used in sensor network are 77GHz wide range radar and 24GHz ultra-wide band (UWB) short range radar (SRR).
- Publication Date: 21-Apr-2013
- DOI: 10.15224/978-981-07-6184-4-45
- Views: 0
- Downloads: 0
A NUMERICAL SOLUTION OF BURGERS\' EQUATION BASED ON MULTIGRID METHOD
Published In: INTERNATIONAL CONFERENCE ON RECENT TRENDS IN COMPUTING AND COMMUNICATION ENGINEERING
Author(s): DEBASISH PRADHAN , MURARI SHARAN
Abstract: In this article we discussed the numerical solution of Burgers’ equation using multigrid method. We used implicit method for time discritization and Crank-Nicolson scheme for space discritization for fully discrete scheme. For improvement we used Multigrid method in fully discrete solution. And also Multigrid method accelerates convergence of a basics iterative method by global correction. Numerical results confirm our theoretical results
- Publication Date: 21-Apr-2013
- DOI: 10.15224/978-981-07-6184-4-46
- Views: 0
- Downloads: 0