Anti-jamming Navigation Receiver When Empty Joint Processing Algorithm Of Dimension Reduction Technology Research

Global navigation satellite system has been widely applied in military and civilian fields. The power of navigation signal received by airborne or ground equipment is usually under the noise level due to the navigation signal using direct spread spectrum technology. Navigation receivers are vulnerable to all types of interferences, which seriously affects the access to navigation information. Therefore, the study on navigation receiver interference suppression has very important practical significance.The traditional adaptive beamforming technology can’t impose effective suppression on multiple interferences due to the restriction of array degrees of freedom. Joint space-time interferences suppression technology greatly increases the ability to suppress interferences on the premise that the number of array elements is unchanged, by adding some time delay units behind each array element.This dissertation focuses on the study of joint space-time interference suppression technology for navigation receivers. STAP technology based on power-minimization is utilized to suppress interferences on the premise that the arrival directions of navigation signal and interferences are unknown prior, the power of navigation signal is significantly under interferences and noise floor. Through concrete theoretical analysis and simulation, a conclusion can be drawn that this method can suppress more non-full band interferences than single spacial processing and has a better output SINR.The joint space-time processing greatly increases the ability to suppress interferences, but also brings a huge computational complexity and lower convergence speed. Then reduced-dimension joint space-time processing algorithms are studied in this paper. Theoretical analysis and performance simulation are thoroughly carried out for several frequently used reduced-dimension methods, especially for the reduced-rank multistage nested wiener filter which is based on subspace decomposition and Orthogonal projection. Reduced-rank MWF can receive superior performances under low snapshot environment and have a very important practical value.Reduced-rank multistage Wiener filter is required to work at the best rank to achieve the desired interference suppression performance. The process of determining the rank is defined as rank-selection. To improve the real-time performance of rank-selection, this paper introduces the simplified data-level iterative MWF first, then proposes two simplified rank-selection algorithms on the basises of CSA-MWF and subspace decomposition theory. Those two rank-selection algorithms can finished in only forward process and have advantages of low computational complexity and high real-time performance. Simulation results demonstrates that the rank-selection algorithms based on power of observed signal and cross-correlation coefficient of the adjacent desired signals have superior reliability and robustness. It is suitable for application in the environment of interference suppression for navigation receivers.