Abstract
Under the condition of impulsive noise., the traditional methods about identification and parameter estimation of linear frequency modulation (LFM) signals are degraded or ineffective. This paper presents a process flow for the identification and parameter estimation of LFM signals under impulsive noise conditions. First., the impulsive noise is suppressed by nonlinear transformation. Then., the LFM signal is recognized by fractional Fourier transform (FRFT) and the rough estimation of the parameters is completed according to the peak coordinates. Last., the accurate estimation of parameters is completed by two-dimensional particle swarm optimization (PSO). Simulation results demonstrate the effectiveness of the algorithm.
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