The Research On Passive Location Technology Of A Single Aiborne Observer

With the merits self-hiding, far distance detection, strong anti-interference ability, Passive location system plays an increasingly important role in the modern information war because it does not radiate electromagnetic wave. The technology of the single airborne observer passive location has good flexibility and mobility as the hotspot of the passive location field. The location principle, observability conditions, position error analysis, tracking filter algorithms are researched and discussed extensively, arounding the key problems of single airborne observer passive location in this paper.First of all, the basic principle and observability analysis of the single observer passive location are introduced based on phase difference rate-of-change and Doppler rate-of-change information. Aim at the original algorithm'shortcomings and the insufficiency, we replace angle variation by phase difference rate and reconstruct observation equations so that an improved composite localization method is gotten. The system burden about measuring angle variation is avoided, and design difficulty of hardware platform is reduced, while improving the algorithm of real-time and practicability.In chapter 3, the model of single airborne observer passive location system is built, the single localization algorithm is studied and single orientation of expression is derived using phase difference rate and Doppler frequency variation. Single positioning random error analysis is given and simulation obtained main factors that influence single positioning accuracy.Passive target tracking is in essence the problem of nonlinear optimal filtering, i.e., the aim is to estimate the state (including position, velocity, and acceleration etc) of the target based on nonlinear measurements. The location and tracking algorithm is studied in chapter 4. For emphasizing the robustness of algorithm, SR-SPKF algorithm is proposed by the square root filtering thoughts based on extended Kalman filter and its derivative algorithms and Sigma point Kalman filtering algorithms. SVD-SRSPKF algorithm is put forward in the condition that the updating covariance matrix is negative so that algorithm is not stable. The simulation experiments results demonstrate that the two methods have better stability.The results of this thesis are meaningfull in improvement of single airborne observer passive location technology.