Spectrum data contains a large number of signals in radio monitoring. Accurate extraction of these signals is conducive to mastering the spectrum usage of the whole frequency band. Due to the interference of noise, several energy values of frequency points in the signal spectrum bandwidth will be lower than the detection threshold, then the traditional threshold detection algorithm will misestimate the signal as multiple signals and generate multiple false adjacent signal intervals, resulting in a decline of the spectrum signal extraction accuracy. To tackle this problem, an algorithm of spectrum signal extraction for estimating the signal number adaptively is proposed according to the characteristics of false adjacent signal intervals. The new method can estimate the number of electromagnetic signals in the spectrum monitoring data, and extract the corresponding signal and spectrum information accurately and automatically. The experimental result shows that the new method is adaptive, strongly robust and accurate, effectively improves the accuracy of spectrum signal extraction. It can provide basic electromagnetic signal data for supporting the identification of electromagnetic environment in military and civil spectrum monitoring.