Performance analysis of poly-semantic sequence for high resolution Doppler radar

Superiority of poly-alphabetic sequences (PAS) for pulse compression radar over the binary and ternary sequences was established earlier. However, the enlarged alphabets in poly-alphabetic sequences deteriorate the noise and Doppler robustness at higher lengths in High Resolution Radar (HRR) systems. In this paper, poly-semantic sequences (PSS) with restricted alphabets {+1,-1} are considered and their performance is analyzed in order to achieve superior detection performance for high resolution Doppler radar system in presence of high density additive noise and Doppler shift. The poly-semantic sequences are optimized by employing modified Hamming scan algorithm called Hamming Backtrack algorithm (HBT) by taking figure of merit as the measure of goodness. The detection capability of poly-semantic sequences is further improved through coincidence detection of the return signal. The simulation results show that the proposed sequences give improved robustness of noise and Doppler shift for HRR target detection compared to conventional pulse compression sequences.