Detection and Parameter Estimation of Multicomponent LFM Signal based on Nonlinear Transformation under the Impulsive Noise

Abstract

The linear frequency modulated (LFM) signal has been widely implemented in broadband wireless communications in high-speed vehicles, such as internet of vehicles(IoV), because of its excellent characteristic of long time interval and wide frequency band. In this paper, a novel method, which employs the fractional Fourier transform and the Tuneable-Sigmoid transform, is proposed to estimate parameters of multicomponent LFM signals in Internet of Vehicles(IoV) under the impulsive noise environment. For the optimization in the fractional Fourier domain, an algorithm based on peak searching is proposed. And for multicomponent signals, we further propose a signal separation technique in the fractional Fourier domain which can effectively suppress the interferences on the detection of the weak components brought by the stronger components, and estimate parameters of LFM signals. Moreover, boundedness and the complexity analysis of Tuneable-Sigmoid-FFRT to the noise are presented to evaluate the performance of the proposed method. In additional, the Cramér–Rao bound for parameter estimation is derived and computed in closed form, which shows that better performance has been achieved. Both theoretical analysis and simulations demonstrate the superior performances of the proposed approach over other existing methods.