Range Sidelobe Level Reduction With a Train of Diverse LFM Pulses
Nadav Neuberger, Risto Vehmas
Abstract
Target masking is a pervasive problem in radar signal processing: the range sidelobes of the waveform’s matched filter response may cause a strong target to prevent the detection of nearby weaker targets. Common solutions to sidelobe level reduction for frequency-modulated waveforms result in a signal-to-noise ratio (SNR) loss. In this correspondence, we propose a novel method using pulse diversity to reduce the range sidelobes while avoiding an SNR loss. The proposed approach is based on shaping the power spectrum of the summation of a train of constant-amplitude linearly frequency-modulated pulses to resemble a Gaussian function. We present a numerical example demonstrating a drastic sidelobe level reduction. Importantly, our approach avoids any processing SNR loss.