A Hybrid Adaptive Technique for Barker Code Matched Filter Sidelobe Cancellation

Barker phase coding is a well-known technique utilized in pulse compression radars employing binary phase-coded waveforms. Despite its effectiveness, a common issue associated with this method is the generation of undesired sidelobes in the output of the sub-pulse matched filter. These sidelobes have the potential to obscure the reflected echoes from nearby weak targets, consequently hampering the radar's detection capabilities. To address this challenge, this study introduces an innovative approach that combines the use of an Adaptive Normalized Least Mean Square (NLMS) filter for noise reduction and a Recursive-Least-Square (RLS) filter to mitigate the sidelobes produced by the matched filter. The integration of the RLS filter with the NLMS filter presents a promising strategy for combating radar active jamming. Through extensive simulation testing, the performance of this hybrid filtering technique is assessed in comparison to an optimal filter. The results indicate that both filters exhibit robust performance under high signal-to-noise ratios (SNRs). However, the proposed adaptive filter demonstrates superior performance over the optimal filter, especially in environments characterized by low signal-to-noise ratios (SNRs). This capability is particularly advantageous for detecting targets with low SNR levels, such as small Radar Cross Section (RCS) targets.