Detection of weak monocycle sinusoidal signals with a low constant false alarm rate based on the support vector machine

Abstract

The detection of weak monocycle sinusoidal signals is the abstract problem of the weak transient signal detection in many engineering applications. A low constant false alarm rate is often required on some occasions with serious false alarm consequences, such as the relay protection and the weapon trigger. The weak monocycle sinusoidal signal means a low signal-to-noise ratio (SNR), only one sinusoidal period, and an unknown initial phase. The support vector machine (SVM) is applied to detect the weak monocycle sinusoidal signal. The false alarm performance of the built SVM is attractive. The characteristics of the built SVM in white Gaussian noise are as follows. Firstly, the probability of false alarm is 0 and the probability of detection is 1 when the SNR is over −11 dB. Secondly, different unknown initial phases cannot influence the performance. Thirdly, the probability of false alarm is always 0, when the SNR is over −25 dB. Furthermore, the experimental results show that this method is also effective in coloured noise. When the SNR of coloured noise is −0.28 dB, the weak monocycle sinusoidal signal can be detected. When the SNR of coloured noise is over −60 dB, the probability of false alarm is always 0.

Keywords

• support vector machines
• Gaussian noise
• signal detection
• probability
• coloured noise
• probability of false alarm
• white Gaussian noise
• SVM
• false alarm consequences
• weak monocycle sinusoidal signal detection
• false alarm performance
• low signal-to-noise ratio
• weak transient signal detection
• support vector machine
• low constant false alarm rate