Airborne Single Station Passive Location Is The Key Technology Research

The traditional active location system is threatened easily by the electronic counter measures and anti-radiation missiles. The target could be positioned with passive location technology which utilizes electromagnetic information and do not radiate electromagnetic wave. The technique is remarkable for its excellent self-hiding, remote detection and anti-interference capability and it has become a popular issue in passive location field for its outstanding flexibility.According to the requirements of the project funded by Aviation Science, the passive location of single airborne observe method is discussed in the paper and the main content is summarized as follows:Firstly, the existing varieties of traditional single observer passive localization method are introduced, and the two methods of classical airborne single-observer passive location based on the phase difference rate-of-change and Doppler rate-of-change information are researched, including principle, observation condition and location precision. Besides, the simulation to the fixed radiation source is completed and the location error is analyzed.Secondly, an improved method which integrates the advantages of the two methods discussed in the first part is proposed. The difficulty on engineering implement could be lessened by avoiding the measurement angle change rate. The analysis and simulation of the method on location principle and precision are discussed at the end of this part.Lastly, nonlinear filtering algorithm in the system of passive location is researched. Classical algorithms EKF and its derivative algorithm MGEKF and UKF are introduced. Divergent character and the strict initial values of EKF are overcome by UKF which is improved to EKF. The improved method to process passive location with EKF and UKF is studied. The simulation results show that the UKF has better precision and convergence rate than EKF. Finally the Kalman filter algorithm which is used to calculate the phase difference rate-of-change is researched. The simulation shows that the accuracy of phase difference rate using the Kalman filter algorithm is better than the difference method, and the data of phase difference is smoothed with the Kalman filter algorithm.