Adaptive pulse edge detection algorithm based on short-time Fourier transforms and difference of box filter

Abstract

Precise radar pulse detection is of great significance for estimating parameters in electronic countermeasure and reconnaissance. An adaptive detection algorithm is proposed, which considers short-time Fourier transforms (STFT), constant false alarm rate (CFAR) in frequency domain, and difference of box (DOB) filter. First, STFT with the Gaussian window is used to acquire the time-frequency spectrum of the radar pulse signal. Second, in order to determine the existence of the pulse, CFAR detector is introduced into the frequency domain to generate an adaptive threshold, and then the rough pulse edges are obtained by mn method. Finally, the data where the rough pulse edges locate are processed by the refined STFT and DOB filter to get the precise pulse edges. The proposed algorithm is processed in the time-frequency domain, which cannot only adapt to low signal-to-noise ratio, but also has a high measurement accuracy. We also draw parallels to the conventional energy-based detection method, the results validate that the proposed algorithm is more robust and effective in practice. Simulations via various noisy input pulse data demonstrate the viability and validity of our proposed algorithm. The algorithm has been implemented in a spaceborne radar receiver.