Sidelobe Level Reduction in the ACF of NLFM Signals Using the Smoothing Spline Method

TL;DR

This paper introduces a smoothing spline approach to reduce sidelobe levels in the autocorrelation function of NLFM signals, achieving significant improvements over traditional polynomial fitting methods.

Contribution

The paper presents a novel application of the smoothing spline method for obtaining the frequency function of NLFM signals, leading to better sidelobe suppression.

Findings

10 dB to 20 dB reduction in peak sidelobe level

Improved autocorrelation properties of NLFM signals

Demonstrated effectiveness over polynomial curve fitting

Abstract

The high level of sidelobes in the autocorrelation function of the nonlinear frequency modulation signal is a challenge. One of the conventional methods to reduce the sidelobe levels is to use the principle of stationary phase. In this method, the frequency function is calculated using a selection window. The signal frequency function cannot be obtained in closed form and numerical methods must be used to find it. This is usually done using the polynomial curve fitting. In this paper, the frequency function of the signal has been obtained using the smoothing spline method. The simulation results show an improvement of 10 dB to 20 dB in the peak sidelobe level of the autocorrelation function of the nonlinear frequency modulation signal compared to the previous methods.