ACSER RESEARCH SEMINAR: Interference Detection, Characterization, and Mitigation Techniques for GNSS Receivers

2 November 2016 - 1:00pm
Seminar Room G3, Electrical Engineering Building (map G17), UNSW Kensington

With the increasing use of global navigation satellite systems (GNSS) in myriad applications, ensuring the integrity of the GNSS signals has become of paramount importance. However, the low received power level makes the GNSS signals vulnerable to either unintentional or intentional (jamming) radio frequency interference (RFI). Therefore, interference detection, characterization, and mitigation technologies should be envisaged in the GNSS receivers. Several relevant techniques based on time-frequency analysis have been proposed.

Firstly, two interference detection algorithms have been developed for detecting both narrow- and wide-band interferences in low JNR environments. The first algorithm is based on time-frequency (TF) and statistical inference techniques. Instantaneous frequency (IF) estimation is completed based on pseudo Wigner-Ville distribution. A two-population F-test is then applied to the two variances of the IF estimates obtained from the received GNSS signal and a known interference-free signal. The second algorithm is based on statistical analysis in the TF domain. A goodness-of-fit test is applied to each frequency slice in the spectrogram (square modulus of canonical or block-wise short time Fourier transform) of the received signal.

Typically, for in-car jammers, large sweep bandwidth within a short sweep time makes it difficult to accurately characterize their IFs with a view to excising them from the received signal. Then, an improved jammer characterization method has been proposed. For the most common chirp-type jammers with a saw-tooth function, short-term Renyi entropy is introduced to provide useful information of turning points in the IF function, which are then used to generate the improved IF estimates. Moreover, considering the time-varying characteristics, an algorithm for an adaptive time-domain window in the smoothed pseudo Winger-Ville distribution with a separable time-lag kernel has also been proposed. The time-domain window length can be adaptively adjusted based on the jammer IF characteristics.

In the previous literature, accurate IF estimation was generally assumed for the performance analysis of various interference mitigation approaches. However, for in-car jammers, impulsive-nature IF estimation errors cannot be completely eliminated in the characterization stage due to the rapid changes in the IF function within a short sweep time. Three solutions based on the existing mitigation techniques have been explored to resolve the IF estimation error issue. The first solution is to apply a segment-by-segment correction of the average phase residual in time-domain subtraction method.  The second solution is partitioned subspace projection. In the third solution, a general IF estimation-based mitigation unit is cascaded with a pulse blanker to mitigate the pulsed jammer residual.

Presented by Pai Wang, ACSER Practicum Student