In this paper we propose a new denoising method of RADAR reflected signals. Using signal processing techniques such as the short-time Fourier transform (STFT) and the chirplet transform, various parameters of signal can be extract. In this paper we can obtain the signal's parameter by using the chirplet transformation as a tool to denoise the signals. We have already tested this algorithm on the real data and have obtained chirplet transformation has the perfect results on system identification by denoising returned signal.

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In order to detect targets upon sea surface or near it, marine radars should be capable of distinguishing target reflections from the sea clutter. Our proposed method in this paper relates to detection of dissimilar marine targets in an inhomogeneous environment with clutter and non-stationary noises, and is based on adaptive thresholding determination methods. Variation and mean vales of the noise have been estimated in this paper, based on non-stationary, statistical methods and thresholding has been carried out using the suggested two-pole recursive filter. Fixating the rate of false alarm, the concerned threshold resolves the assumption problem of existence or absence of the signal. Performance of the mentioned algorithm has been compared with method known as CA-CFAR in terms of decreasing the losses and increasing calculation speed. The algorithm provided for detection of signal has been implemented at the end of signalprocessing algorithms of sea marine radars. The results obtained from the algorithm performance in a real environment indicate appropriate workability of this method in heterogeneous environment and non-stationary interference.

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