A significant problem in radio communications is the detection and differentiation of signals at an increased level of interference. The current electromagnetic environment is too dynamic and the compatibility of electronic communications must be adapted to the changing parameters of interference. This involves interference analysis and selection of the most appropriate signals in order to ensure good resistance of the communication system against interference. Correlation analysis is a powerful tool in detecting or recognizing signals in conditions of intense disturbance, and there are many such studies in the literature. In signal synthesis tasks, the most common goal is to obtain autocorrelation function. But the correlation between two variables can also be established through dependencies on mathematical statistics. The task of synthesizing signals resistant to the interference is statistical a priory because of the random nature of the interference.
In the present work, an algorithm for identifying the useful signal from interference by determining the Spearman rank coefficient is proposed.
For this purpose, the measured values of the signal and the interference are replaced by their rank numbers. Ranks are obtained by assigning a different degree of possession of the observed quality to a number from 1 to n.
In order for the signal and interference to be independent, the ranking factor must be equal to 0, or minimal. Based on this, after determining the Spearman's coefficient for the reported values of the signal and the interference, a rearrangement is performed in the reports of the signal which ensures a reduction in the correlation between them.
The authors plan to apply the algorithm in in-situ experiments using remote sensing wireless sensor network based on the experience in the Remote Sensing Systems Department at the Space Research and Technology Institute at the Bulgarian Academy of Sciences.
