A Novel Parameter Estimation Method Based on Piecewise Nonlinear Amplitude Transform for the LFM Signal in Impulsive Noise

Abstract

In a complex electromagnetic environment, any noise present generally exhibits strong impulsive characteristics. The performance of existing parameter estimation methods carried out in Gaussian white noise for the linear frequency modulation (LFM) signal degrades or even fails under impulsive noise. This paper proposes a novel parameter estimation method to address this problem. Firstly, the properties of the piecewise nonlinear amplitude transform (PNAT) are derived. This manuscript verifies that the PNAT can retain phase information of the LFM signal while suppressing the impulsive noise. Subsequently, a new concept known as piecewise nonlinear amplitude transform parametric symmetric instantaneous autocorrelation function (PNAT-PSIAF) is proposed. Based on this concept, a novel method called piecewise nonlinear amplitude transform Lv’s distribution (PNAT-LVD) is proposed to estimate the centroid frequency and chirp rate of the LFM signal. The simulations show that the proposed algorithm can effectively suppress the impulsive noise without prior knowledge of the noise for both the single-component and double-component LFM signal. In addition, two parameters of the LFM signal can be precisely estimated by the proposed method under low generalized signal-to-noise ratios (GSNR). The stronger the impulsive characteristics of the noise, the better the performance of the algorithm.

Parameter Estimation of LFM Signals Based on FOTD-CFRFT under Impulsive Noise

“…In order to better demonstrate the performance of parameter estimation under the impulsive noise, the proposed method is compared with the three newly proposed parameter estimation methods, i.e., Sigmoid-FPSD [7], PANT-LVD [8] and FTD-FRFT [9]. For α = 1.2 and GSNR = 0 dB, the fractional spectrums of the noisy signal are built and shown in Figure 7, the search step size for parameter p is 0.002.…”

“…In order to better demonstrate the performance of parameter estimation under the impulsive noise, the proposed method is compared with the three newly proposed parameter estimation methods, i.e., Sigmoid-FPSD [7], PANT-LVD [8] and FTD-FRFT [9]. For…”

“…To address the parameter estimation under impulsive noise environment, scholars have proposed many methods, such as, fractional lower-order statistics [3][4][5], nonlinear transform [6][7][8], tracking differentiator [9,10], convolutional neural networks [11,12]. In [3], an improved fractional lower order LVD (FLO-LVD) for the impulsive noise is proposed, which can overcome the influence of cross-terms and achieve higher estimation accuracy.…”

“…In [7], the Sigmoid-FPSD method is proposed to effectively suppress impulsive noise, which has certain adaptability to changes in impulsive noise parameter. In [8], a piecewise nonlinear amplitude transformation (PNAT) function was designed to suppress impulsive noise, and combined with LVD to form a new LFM signal parameter estimation method, named PANT-LVD. However, these methods based on nonlinear transform also present certain drawbacks including poor stability under low GSNR and extensive computational requirements.…”