An Improved Multiple Hypothesis Solution Separation Algorithm for GNSS Anti-Spoofing
| Autor: | Zun Niu, Bocheng Zhu, Xin Meng, Junren Sun, Ping Nie, Lin Tao |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
020301 aerospace & aeronautics
Spoofing attack Computer science business.industry Electromagnetic environment Real-time computing Stability (learning theory) 020206 networking & telecommunications Satellite system 02 engineering and technology 0203 mechanical engineering Anti spoofing GNSS applications 0202 electrical engineering electronic engineering information engineering Global Positioning System business |
| Zdroj: | 2019 2nd International Conference on Information Systems and Computer Aided Education (ICISCAE). |
| DOI: | 10.1109/iciscae48440.2019.221617 |
| Popis: | Global Navigation Satellite System (GNSS) has penetrated into many civil applications from the original customized military navigation and positioning services, which has resulted tremendous improvements in the corresponding fields. At the same time, the growing complexity of the electromagnetic environment has continuously challenged the stability of the GNSS. Therefore, anti-spoofing technology has triggered increasing research enthusiasm. In this paper, we propose an anti-spoofing algorithm that improves multiple hypothesis solution separation (MHSS) method and integrates the least square residual (LSR) method. In our improved MHSS (IMHSS) algorithm, we first apply LSR to determine whether the potential spoofing signal exists, then we divide the satellites into different subsets and design the relative vertical protection level (VPL) value of each subset to identify the spoofing signal by selecting the optimal subset. Not only has the IMHSS algorithm reduced the computational complexity, but also it guarantees the success of removing the spoofing signal. We experimentally show the IMHSS algorithm compared to strong baseline of suggestion range consensus (S-RANCO) algorithm is effective in both single-satellite spoofing and multi-satellite spoofing scenarios. |
| Databáze: | OpenAIRE |
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