1 Introduction
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We have proposed an innovative architecture that consists of the EDAC method for the nanosatellites. It has analyzed six camera images simultaneously with the assistance of FPGA.
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We have analyzed, and compared the satellites’ error detection and correction algorithms. We have also developed our proposed hybrid approach for EDAC.
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We have identified the number of erroneous bits. Based on that, we have developed a syntactic analysis for the error correction method.
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We have implemented the scheme for the LDPC, BCH, Turbo, Convolutional, and Shannon’s theorem. The scheme shows that the BER ratio gradually decreases from 10−1 to 10−6; on the other hand, system performance increases significantly.
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We have discussed the limitations of existing error detection and correction algorithms. We have proposed future work to introduce an advanced error detection method based on satellite-transmitted data using machine learning techniques and to implement the ASIC architecture in Spartan 6 FPGA, a novel approach to improving the accuracy and reliability of nanosatellite data transmission systems.
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Finally, we have analyzed the performance of five different EDAC algorithms with AWGN and Rayleigh channels in MATLAB.