Use of Hazard Function for Signal Detection on Ionograms

Abstract

This letter considers a new method for sample detection of ionospheric propagation modes at the receiver output of a chirp ionosonde. The method is based on the use of the hazard function. Within the framework of the two-component mixture model, it is shown that the hazard function can be used to detect samples of the second component in the mixture when the corresponding fraction of samples in the total number is small. The implementation of the method is carried out using training sets. An average normalized hazard function is constructed for the training set not containing the signal. Normalization is carried out in such a way that the hazard function can be considered as a probability density function of a certain random variable. We used Pearson’s statistic to test the agreement between the average normalized hazard function of samples that do not contain the signal and an arbitrary normalized hazard function. The critical value of the statistic was determined using the Neyman–Pearson criterion. The effectiveness of the proposed method has been tested for the determination of the lowest and maximum observed frequencies of radio paths from oblique ionospheric sounding ionograms obtained in the Russian network of circumpolar radio paths. The method suggested in this letter can be used not only when processing ionograms but also for the detection of samples of signals of arbitrary nature against a background noise, provided that statistical signal-to-noise ratios are similar to those considered here.