Localization for GNSS interference sources based on weighted K-Means combined with DRSS positioning

The carrier to noise ratio (CNR) based interference positioning in Global Navigation Satellite System (GNSS) has the problem of high localization difficulty and the low localization precision under the scenarios with multiple interference sources, multi-path transmission and long distance between receivers. Aiming at this problem, a multi-interference localization scheme that combines the weighted K-Means clustering with different receiver signal strength (DRSS) and equation solving based method is proposed in this paper. Assuming that the number of interference sources is determined and a single receiver is only affected by one interference source, the improved weighted K-Means clustering algorithm is designed to realize the initial estimation for multiple interference sources. In order to reduce the positioning error of the weighted K-Means clustering when the distance between receives is long, the receiving CNR affected more obviously by interference within each cluster are used to build the localization equations based on DRSS after clustering processing. To solve the equations can obtain the more accurate localization results. Simulation results demonstrate that the proposed scheme can realize the multi-interference localization. Compared with the scheme only including weighted K-Means, the average positioning errors of the proposed method involving DRSS parameters can be reduced by more than 19% and 38% under the two cases of single source and two single-tone sources, respectively.