Abstract
Estimating the parameters of the enemy's threat signal is an essential task in electronic warfare support systems. Among the parameters, time of arrival (TOA) and pulse width (PW) are commonly used to estimate carrier frequency and pulse amplitude (PA). It is indisputable that the estimation performance of the carrier frequency and PA depends on the TOA and PW accuracy. Therefore, it is crucial to estimate TOA and PW accurately. Recently, a method using wavelet denoising has been studied to increase the estimation accuracy of signal parameters. However, using wavelet denoising has a performance deterioration problem due to signal distortion when a wideband signal is intercepted. Thus, in this paper, we analyse the cause of distortion and propose a denoising technique with a sinc filter bank-based constant false alarm rate (CFAR) detection. In addition, we propose an estimator exploiting a differential moving average filter to improve the estimation performance even in a low signal-to-noise ratio (SNR). Simulation results show that the proposed denoising method performs better than the conventional method.
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