Evolutionary and Hybrid Optimization Techniques for Orthogonal Polyphase Code Design: A Comprehensive Review for ONRS and MIMO Radar Applications

This paper presents a comprehensive review of optimization techniques for generating orthogonal polyphase codes in Multiple-Input Multiple-Output (MIMO) and Orthogonal Netted Radar Systems (ONRS). We examine the progression from traditional matrix-based methods to advanced hybrid optimization approaches. Our analysis demonstrates that hybrid methods combining global and local search strategies consistently out-perform single-algorithm approaches, achieving autocorrelation sidelobe peak levels of -18.9 dB and crosscorrelation peak levels of -14.3 dB for practical code lengths. We provide quantitative insights into fundamental trade-offs, establishing that doubling code length typically yields approximately 2 dB improvement in correlation properties, while doubling set size results in 1.7 dB degradation. The review also addresses critical implementation considerations, including Doppler sensitivity, phase quantization effects, and hardware complexity considerations, providing practical guidelines for system designers. Our findings indicate that memetic algorithms with greedy code search offer the optimal balance of autocorrelation and crosscorrelation performance and computational efficiency for radar applications.