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The search for binary sequences with low peak sidelobe level value representsa formidable computational problem. To locate better sequences for thisproblem, we designed a stochastic algorithm that uses two fitness functions. Inthese fitness functions, the value of the autocorrelation function has adifferent impact on the final fitness value. It is defined with the value ofthe exponent over the autocorrelation function values. Each function is used inthe corresponding optimization phase, and the optimization process switchesbetween these two phases until the stopping condition is satisfied. Theproposed algorithm was implemented using the compute unified devicearchitecture and therefore allowed us to exploit the computational power ofgraphics processing units. This algorithm was tested on sequences with lengths$L = 2^m - 1$, for $14 \le m \le 20$. From the obtained results it is evidentthat the usage of two fitness functions improved the efficiency of thealgorithm significantly, new-best known solutions were achieved, and theachieved PSL values were significantly less than $\sqrt{L}$.

Two-phase Optimization of Binary Sequences with Low Peak Sidelobe Level Value