Research On Adaptive Anti-jamming Technology Of High Dynamic Beidou Navigation

Beidou navigation satellition system has been widely utilized in the military and civil applications.Due to the vulnerability of navigation signal and complexity of the electromagnetic environment,the research on anti-jamning technique has become more and more important.In high-dynamic receiving environment,conventional interference suppression techniques cannot be directly adapted due to the rapid change of interference direction related to the receiver.Hence,it is significant to develop specific anti-jamming technique in high-dynamic environment.This thesis mainly focuses on the interference suppression in high-dynamic environment from the view of widening nulling and improving the update rate of weightings.The main content are as follows:1.The Laplace-nulling widening(L-NW)algorithm is studied.The effect of disturbance parameter on the algorithm is investigated with linear array and planar array.The effectiveness of the algorithm in high-dynamic environment is analyzed.The results show that the algorithm can increase the width of adaptive nulling,while the depth of nulling is shallowed.2.The Laplace-nulling widening and deepening(L-NWD)algorithm is proposed then.The effects of disturbance parameter and deepening coefficient are investigated.The effectiveness of the algorithm in high-dynamic environment is analyzed.The results show that the algorithm can increase the nulling depth with the nulling widened.And the robustness of the algorithm is superior to the L-NW algorithm when interference power fluctuations,3.The iterative diagonal loading(IDL)algorithm for small snapshots is studied.The effects of snapshot number and loading value are investigated.The effectiveness of the algorithm in high-dynamic environment is analyzed.The results show that the algorithm can improve the update rate of weighting,and make the nulling angle deviation smaller in high-dynamic environment.By combining EDL and L-NW algorithms,not only the nulling is widened,but also the update rate of weighting is increased.Finally,the performance of the joint algorithm is superior to the original L-NW algorithm.