Statistical Inference Technique in Pre-Correlation Interference Detection in GPS Receivers

Narrowband interference can severely degrade the performance of GPS receivers. Detecting the interference and then characterizing it can lead to its removal. Knowledge that can be useful is: the location of the source or direction of arrival of the interference (spatial-directional characteristics), the time specification and frequency and power of the interference (temporal-spectral characteristics). The focus in this work is on the second type. In a power spectral density fluctuation detection technique [1], statistical inference has been used in detecting the narrowband CW interference in the GPS signal after being captured by the RF front-end. In this technique, an assessment window of data is first divided into some data blocks and then analyzed to get the statistical parameter of the signal without interference, and then by comparing these parameters as null hypothesis with the parameters extracted from another window at the period where the presence of interference is to be examined, the existing of interference is tested. The effect of assessment window size on the level of confidence of this test has been already analyzed. In this work, using a property of the fast Fourier transform (FFT) and the effect of the number of FFT points on the test statistic mean, it is theoretically shown that by choosing an appropriate data block size and window size simultaneously it is possible to achieve a given optimal solution to detect "minimum power detectable interference". Then this theoretical result is proved by real experiments.