Side lobe supression techniques for polyphase codes in radar

The present thesis aims to make an in-depth study of Radar pulse compression. Pulse compression (PC) is an important module in many of the modern radar systems. It is used to overcome major problem of a radar system that requires a long pulse to achieve large radiated energy but simultaneously a short pulse for range resolution .Range resolution is an ability of the receiver to detect nearby targets. The performance measures of PC techniques are PSL, ISL, SNR loss and Doppler shift. The major advantages of PC are resulting gain in SNR and relative tolerance to jammers. PC can also lift small target signals out of clutter. In this thesis we compare the merit factors of different sidelobe reduction techniques with a novel technique, using P4 code of length 1000. The amplitude weighting technique in which the code signal is multiplied with the window coefficients and the weighted code and the transmitted signal are applied to correlation in the receiver side .The tradeoff in reducing the PSL is spreading of the compressed pulse. Woo filter technique is that which uses two correlation filters to produce a single discrete filter, It reduces PSL and ISL at sacrifice of mainlobe splitting and 3 [dB] SNR loss. The modified forms of Woo filter reduce the PSL further and also the mainlobe splitting present in Woo filter is removed. Asymmetrical weighting is a technique in which amplitude of the Woo filter is taken as the weighting function to the incoming signal. This method enables to suppress PSL beyond Barker codes levels while other performance degradations are minimized. In the proposed technique amplitude weighting is applied to a combination of the incoming signal and one-bit shifted version of the incoming signal. This technique produces better peak side lobe ratio (PSL) and integrated side lobe ratio (ISL) than all other conventional sidelobe reduction techniques. Main lobe splitting which is the main disadvantage in Woo filter is eliminated in this techniques and it is easy to implement and incurs a minimal signal to noise ratio SNR loss