@article{MAKHILLJEAS201813615829,
    title = {Performance Analysis of LMS Filter Using Chaotic and Barker Codes for
Radar Target Detection},
    journal = {Journal of Engineering and Applied Sciences},
    volume = {13},
    number = {6},
    pages = {1537-1543},
    year = {2018},
    issn = {1816-949x},
    doi = {jeasci.2018.1537.1543},
    url = {https://makhillpublications.co/view-article.php?issn=1816-949x&doi=jeasci.2018.1537.1543},
    author = {Jami and},
    keywords = {root mean square error,Xilinx FPGA ISE,adaptive LMS filter,MATLAB Simulink,barker codes,chaotic codes,target detection,Radar signal processing,signal to noise ratio},
    abstract = {Target detection and tracking play a very foremost role in space and underwater scenario. In this
study, we presented a Least Mean Square filter based Radar Target Detection (LMS-RTD) Model is proposed
to de-noising of pulse radar transmitted signal. In target detection, Radio Frequency (RF) energy is transmitted
to and reflected from the reflecting object which has target status information. Signal generation and target
detection of radar model is designed and simulated using MATLAB 2017a Simulink. Study of performance
analysis of adaptive LMS filter using barker codes, combined barker codes, different binary chaotic sequences
is also presented in this study. Implementation of an adaptive LMS filter using Verilog HDL and its analyses
using Xilinx FPGA tool. On FPGA analysis, parameters such as total number of used LUT’s and flips flops are
reduced in the proposed adaptive LMS filter and improve the hardware and circuit computational complexity
as compared with other existing methods.}
    }