Detection algorithm of big bandwidth chirp signals based on STFT

Jinzhen Wang; Juhong Wu; Shaoying Su; Zengping Chen

doi:10.1117/12.2066127

7 October 2014 Detection algorithm of big bandwidth chirp signals based on STFT

Jinzhen Wang, Juhong Wu, Shaoying Su, Zengping Chen

Proceedings Volume 9252, Millimetre Wave and Terahertz Sensors and Technology VII; 92520M (2014) https://doi.org/10.1117/12.2066127
Event: SPIE Security + Defence, 2014, Amsterdam, Netherlands

Abstract

Aiming at solving the problem of detecting the wideband chirp signals under low Signal-to-Noise Ratio (SNR) condition, an effective signal detection algorithm based on Short-Time-Fourier-Transform (STFT) is proposed. Considering the characteristic of dispersion of noise spectrum and concentration of chirp spectrum, STFT is performed on chirp signals with Gauss window by fixed step, and these frequencies of peak spectrum obtained from every STFT are in correspondence to the time of every stepped window. Then, the frequencies are binarized and the approach similar to mnk method in time domain is used to detect the chirp pulse signal and determine the coarse starting time and ending time. Finally, the data segments, where the former starting time and ending time locate, are subdivided into many segments evenly, on which the STFT is implemented respectively. By that, the precise starting and ending time are attained. Simulations shows that when the SNR is higher than -28dB, the detection probability is not less than 99% and false alarm probability is zero, and also good estimation accuracy of starting and ending time is acquired. The algorithm is easy to realize and surpasses FFT in computation when the width of STFT window and step length are selected properly, so the presented algorithm has good engineering value.

Citation Download Citation

Jinzhen Wang, Juhong Wu, Shaoying Su, and Zengping Chen "Detection algorithm of big bandwidth chirp signals based on STFT", Proc. SPIE 9252, Millimetre Wave and Terahertz Sensors and Technology VII, 92520M (7 October 2014); https://doi.org/10.1117/12.2066127

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KEYWORDS

Signal detection

Signal to noise ratio

Interference (communication)

Detection and tracking algorithms

Radar

Fourier transforms

Frequency modulation

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