Research On Key Techniques Of Anti-spoofing In GPS/INS Deep Integrated System

Spoofing is the research hotspot on area of jamming and anti-jamming in satellite navigation in recent years, which utilizes signal has the same structure with the authentic GPS signal as the spoofing signal so that it can fool receiver to track spoofing signal without being noticed and degrade the anti-jamming performance of receiver. Additionally, it may set its power similar to the authentic GPS signal to avoid being detected by power metric and decrease the cost of jamming. In actual application, such as military area, receiver always faced with complex and ever-changing environment like high dynamic, weak signal power, strong jamming or signal blockage, which would force receiver to lose lock and then track the spoofing signal or boost the interference caused by spoofing signal in tracking process and thus interference the whole system.GPS and INS are complementary to each other. Combination of two fully take advantages of navigation precision of GPS not drifting along the time and stand-along feature of INS, which is considered as an relative ideal integration navigation system. GPS/INS deep integration system is a frontier of integration navigation, which deeply exploiting and utilizing information from INS, makes GPS and INS deeply assist each other to implement a more precise and robust navigation system.The thesis mainly investigates the detail effects of spoofing on some aspects of deep integration system like tracking, integration filter and loop feedback control, and proposes spoofing countermeasures from improving the structure of deep integration and integration filter algorithm based on the previous investigation.For the structure of deep integration, the thesis mainly researches on loop control based on mean value prediction and tracking strategy based on CADLL, which would increase the precision and stability of loop control, and at the same time decrease interference on signal parameter estimation caused by other signal components, thus improving the parameter estimation precision. For the integration filter algorithm, the thesis mainly studies on utilizing Robust Estimation to defend outliers in measurement result from spoofing and proposed anti-spoofing integration filter algorithm based on AR-SRCKF. The new algorithm utilizes Adaptive Robust Filter as the frame of the algorithm to improve system robustness to spoofing. Meanwhile, for avoiding filter performance decreasing caused by linearization, the method uses Square-Root Cubature Kalman Filter to solve the non-linear filtering problem and make sure the symmetry and positive semidefinite of the covariance matrix.Finally, the thesis proposed an complete scheme on anti-spoofing in deep integration system based on previous research achievements, which fully exploits the characteristics of deep integration navigation system, and makes each aspect of system assist others to form an unite anti-spoofing system, thus increases system robustness to spoofing. Simulation based on deep integration system indicates that the new designed system possesses considerable robustness to spoofing.