A Localization Algorithm Based on Weighted Least Squares with Cramér-Rao Bound for GNSS Jammer
Low earth orbit(LEO)satellites are capable of conducting rapid geolocation of global navi-gation satellite system(GNSS)interference sources with Doppler measurement data.However,the highly dynamic characteristics of LEO satellites limit the quantity of acquired Doppler observations,consequently restricting the localization accuracy achievable through conventional least squares algorithms.To enhance the accuracy,a weighted least squares localization algorithm based on Doppler measurement Cramér-Rao bound(CRB)is proposed in this paper.This method incorporates a signal-to-noise ratio(SNR)lookup ta-ble for Doppler sampling instances to ascertain the Cramér-Rao bound(CRB),thereby standardizing the noise across various Doppler observation moments through weighting.This adjustment ensures that the least squares solution for the interference source location is made close to the optimal estimation.The ef-fectiveness of the proposed algorithm was verified by simulation under different sampling rates,SNRs and sampling durations.The FPGA-based GNSS interference acquisition and localization system was also con-structed and tested in real scenarios.The simulation and experiment results show that the proposed algo-rithm significantly improves the localization accuracy by 17.43％,compared with the least squares algorithm.
Cramér-Rao bound(CRB)global navigation satellite system(GNSS)interference source localizationweighted least squares
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