The effective design of orthogonal waveforms is critical for the realisation and optimisation of Multiple-Input, Multiple-Output (MIMO) radars. Traditional approaches frequently fail to balance the optimisation of Autocorrelation (Acr) and Cross-correlation sidelobe (Ccr) levels. To solve this difficulty, a unique technique based on the Multi-Objective Particle Swarm Optimisation (MOPSO) algorithm is proposed. The MOPSO method effectively discovers the optimal solution by minimising both total Acr and Ccr sidelobe energies. This MOPSO approach combines the PSO variation with the convex optimisation method for solution discovery. Furthermore, a novel environmental selection strategy significantly improves the rate of convergence. Finally, a dynamic weights are updated based on frontier surface shape correction fine-tunes the overall distribution. Experimental results show that MOPSO produces higher orthogonality than existing approaches, resulting in reduced overall Acr and Ccr peak energies.