GPS interference detection and identification using multicorrelator receivers

The interference is among the most feared events in civil aviation use of GNSS. A large number of techniques were designed to alleviate the sensitivity of modern receivers to this perturbation. Most of these techniques are either based on spatial discrimination like adaptive antennas, on spectral selectivity such as notch filters or on amplitude detection. The advent of multicorrelator receivers widens the range of postcorrelation methods that can be considered to tackle this problem. In particular, this enables the characterization of interference effects on the tracking loops through the analysis of the shape of the correlation peak. The aim of this paper is to present the technique we have developed to detect and identify the interference parameters using a multicorrelator receiver and to detail the results obtained during testing with CW and FM jammers. T he paper starts with the theoretical derivation of the effect of CW interference on the code and phase tracking loops I and Q samples for a typical receiver. Results of CW interference tests are described for different test configurations. Correlation peaks are collected for different CW interferer frequencies and power levels. These observations were used to validate the theoretical derivations mentioned above, therefore demonstrating the feasibility of interference detection with multicorrelator techniques. These tests were further extended to FM type interference with different bandwidths and power levels and yielded similar results. The paper goes on describing the processing steps implemented to estimate interference characteristics (central frequency, bandwidth and power) using different parametric methods (Prony Covariance, truncated SVD and ESPRIT). Performance of these techniques is then assessed on data collected using a multicorrelator receiver connected to a GPS signal RF generator and affected by several CW and FM interferers with different power levels, bandwidth and central frequency. Finally, a real time tool allowing interference detection and estimation is presented.