Error Correction of Radar Long Distance Data using Kalman Filter for Autonomous Vehicle Movement
Ch. Varun1, K. Rama Krishna2, S.P.V. Subba Rao3
1Ch. Varun, Department of Electronics and Communication Engineering, Sreenidhi Institute of Science and Technology, Hyderabad, India.
2K. Rama Krishna, Department of Electronics and Communication Engineering, Sreenidhi Institute of Science and Technology, Hyderabad, India.
3S.P.V. Subba Rao, Department of Electronics and Communication Engineering, Sreenidhi Institute of Science and Technology, Hyderabad, India.
Manuscript received on 22 April 2019 | Revised Manuscript received on 27 May 2019 | Manuscript published on 30 May 2019 | PP: 2555-2558 | Volume-8 Issue-1, May 2019 | Retrieval Number: A2224058119/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: A novel method is proposed for reducing the errors in distance measuring sensors namely Radar to accurately detect the relative distance of any Autonomous vehicle in a surface movement scenario. Sensor distance outputs are proposed to be taken with appropriate signal conditioning as input to the well known Kalman filter and an appropriate program is proposed to be written in Mathematica-11 on a Broad-Com2837 based Linux Operating system. The distance sensor namely radar data is simulated using Mathematica-11 real random variable built in function. This data is applied as input to the scalar Kalman filter and error corrected data is obtained at the output. The measured values and error corrected values and true values of the radar are plotted along with error reduction scenario. It is observed that the considerable error reduction was obtained through this method.
Index Terms: Radar Sensor, Kalman Filter, Broad-Com2837R, Linux, Mathematica-11.
Scope of the Article: Radar and Satellite