Polyphase Sequences with Good Correlation Properties and Merit Factor Based on Cyclic Algorithm Approach


Polyphase Pn n=1,2,3,4,x, Frank, Golomb, and the Chu are examples of sequences with good autocorrelation qualities. They are used in RADAR, SONAR, and communication. Performance indicators such as the Merit Factor (MF) and the ISL (Integrated Sidelobe Level) are used to assess the quality of any sequence. Polyphase sequences with lengths ranging from 102 to 103 are generated using a cyclic algorithm approach in this study. These cyclic algorithm techniques exceed the usual situation in terms of merit factor and correlation. For lengths of 100 and 1000, the average merit factor was found to be 40.39 and 92.02, respectively. The cyclic approach is used to compare the correlation graphs of polyphase sequences to the typical case. This method was used to create P2 sequences with a greater merit factor for odd integer square length. Four consecutive even and odd integer squared length sequences were examined in terms of merit factor values and correlation plots. In MATLAB, a cyclic algorithmic approach for gathering design metrics has been devised for these Polyphase sequences.

Author (S) Details

Rajasekhar Manda
Department of Electronics and Communication Engineering, PACE Institute of Technology & Sciences (A), Ongole, India.

P. Rajesh Kumar
Department of Electronics and Communication Engineering, Andhra University College of Engineering (A), Visakhapatnam, India.

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