Performance Analysis of LMS Filter Using Barker and Chaotic Sequences for Radar Target Detection

Keywords: RADAR, chaotic maps, barker codes, MATLAB Simulink, LMS-RTD, Xilinx FPGA, RMSE


Target detection and tracking play a very foremost role in space and underwater scenario. In this paper, we presented a new Least Mean Square based Radar Target Detection (LMS-RTD) model is proposed to de-noising of continuous wave radar transmitted signal. In target detection, radio frequency (RF) energy is transmitted to and reflected from the reflecting object which has a status of target information. Signal generation and target detection of Radar model is designed and simulated using MATLAB 2017a Simulink. The study of performance analysis of signal generation model using binary chaos phase sequences using different chaotic maps, barker codes, combined barker code sequences and the de-noising algorithm using adaptive LMS filter is also presented in this paper. Implementation of an adaptive LMS filter using Verilog HDL and its analyses using Xilinx FPGA tool. In FPGA analysis, the number of LUT’s and used flip flops are improved in proposed LMS-RTD method than conventional methods.

Author Biography

Jami Venkata Suman, Department of ECE, GMR Institute of Technology, India



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How to Cite
J. Venkata Suman, “Performance Analysis of LMS Filter Using Barker and Chaotic Sequences for Radar Target Detection”, Proc. eng. technol. innov., vol. 8, pp. 01-08, Apr. 2018.