MCPC signal waveform optimization method based on multi-target particle swarm optimization

The invention discloses an MCPC signal waveform optimization method based on a multi-target particle swarm algorithm, which can solve the problem of MCPC signal waveform optimization in a wide-area random sparse array detection scene. The method comprises the following steps: constructing a particle swarm, and randomly generating the initial position and speed of each particle; calculating fitness function values, namely PMEPR and PSLL, corresponding to each particle in the population; updating a non-inferior solution set; carrying out particle optimal updating; updating the particle speed and position; and judging whether a set number of iterations is reached or not, and outputting a non-inferior solution set after iteration is completed. According to the method, the signal subcarrier weight is optimized under the dual constraints of the signal PMEPR and PSLL by using the multi-target particle swarm algorithm, so that the detection performance of the signal can be improved, and the linear requirement of the