Investigation of Noise Immunity of Nonparametric Signal Detection Methods in Radio Communication Systems

The article is devoted to the issues of signal detection in a radio communication system. As a rule, such tasks are solved in two ways – adaptive and nonparametric. The adaptive method is to adjust the structure and parameters of the detection system in accordance with the parameters of signals and noise. Nonparametric methods are used when it is necessary to ensure that the system is insensitive to changes in the properties of signals and noise, in particular in the absence of a priori information about the probabilistic properties of the measured signals and noise. Nonparametric methods of signal detection are based on the use of nonparametric methods of statistical hypothesis testing theory. Nonparametric methods are effectively used in radio electronic systems due to the need to stabilize the frequency of false alarms with unknown noise properties. The invariant properties of nonparametric procedures are based on the independence of the statistical properties of nonparametric functions from the statistical properties of the measured signals. One of the most effective nonparametric methods is the use of ranks, which are formed as a result of ranking the input samples of the measured signal either in ascending or descending order. Ranks have many useful properties for practice and are the most suitable for the purposes of forming various statistical hypotheses. The article is devoted to the criterion of post-detector rank signal processing based on minimizing the RMS error of measuring the situation parameter. The article considers the noise immunity of this criterion in comparison with optimal rank detection methods based on the Neumann -Pearson criterion.