Abstract
The existing direct sequence spread spectrum (DSSS) communications interference detection algorithms are confined to the high sampling rate. In order to solve this problem, algorithm for DSSS communications interference detection was designed based on compressive sensing (CS). First of all, the orthogonal matching pursuit (OMP) algorithm was applied to the interference detection in DSSS communications, the advantages and weaknesses of the algorithm were analyzed; Secondly, according to the weaknesses of the OMP algorithm, a joint interference detection method based on the OMP algorithm and cell average constant false alarm rate (CA-CFAR) was proposed. The theoretical analyze and computer simulation all proved the effectiveness of the new algorithm. The simulation results show that the new method not only could achieve the interference detection, but also could estimate the interference quantity effectively.
Highlights
Interference detection is an important part of communication anti-jamming technology; it provides the necessary information for the interference suppression
The description of the interference detection algorithm based on the orthogonal matching pursuit (OMP) algorithm was as follows
In order to overcome the weakness of the algorithm based on the OMP algorithm, we proposed a joint interference detection algorithm based on the OMP algorithm and cell average constant false alarm rate (CA-CFAR)
Summary
Interference detection is an important part of communication anti-jamming technology; it provides the necessary information for the interference suppression. The commonly transform domains include the frequency domain [2], the wavelet domain [3], the fractional Fourier transform domain [4], etc These methods achieve interference detection successfully, but with the development of technologies, the signal bandwidth is growing, large bandwidth leads to a sharp increase of the sampling rate, the existing methods are confined to the high sampling rate. The study of signal processing based on CS are mainly focus on the precisely reconstruct of the original signal from compressed signal. It is not necessary in many cases, such as signal detection [6]. The theoretical basis of the method were analyzed, the effectiveness of the method was verified by computer simulation
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