Research On Single-base Angle Measurement Passive Positioning Technology

The single-based angle-measurement passive positioning technology is to use the angle-measurement system on a single airborne platform to detect the same radiation source target on the ground at multiple observation points of the flight trajectory.The measured pitch and yaw angle information is measured according to non-The linear filtering algorithm performs processing to obtain the estimated value of the position coordinate of the radiation source target.This positioning method is the core technology of anti-radiation radar and has become a military technology that has been developed by major powers.In this paper,based on data,performance simulation research on target positioning algorithm and performance,anti-radar shutdown performance,etc.are carried out.The specific work carried out is as follows:Established a single base angle measurement passive positioning mathematical model,studied the EKF?UKF?AEKF?FDEKF algorithms,developed corresponding software,through a large number of matlab simulation experiments,respectively analyzed and evaluated several Kalman filter algorithms,Parameter optimization,summed up their respective advantages and disadvantages.According to the analysis of the initial state value,angle measurement error and other factors,a method to enhance the adaptability of the positioning algorithm and shorten the convergence time of the positioning algorithm is proposed.The anti-radiation missile anti-shutdown performance was simulated and analyzed.To simulate the situation where the target radar shuts down during the last phase of the flight,several Kalman filter algorithms are simulated and compared under this background.An optimized positioning algorithm based on pattern search method is proposed,and a mathematical model of the optimized positioning algorithm is established.Simulate and verify the proposed new algorithm.Simulation experiments show that the algorithm can use short-term measurement data to find an optimal target point,can quickly locate the target,and can effectively resist radar shutdown.A target positioning algorithm based on optimization-Kalman filtering is proposed.The Kalman series filtering algorithm and the optimization positioning algorithm are combined.The optimization algorithm is used to estimate the position of the ground target.The estimated result is used as the Kalman filter algorithm.The initial value of the filter is further processed.Simulation experiments prove that this method is easy to implement,has high positioning target accuracy,and can reduce the algorithm convergence time,and has practical application value.A set of dimensionality reduction filter processing method is proposed for a set of measured data with large observation noise.This method can reduce the impact of measurement data error and improve positioning accuracy.Simulation experiments prove that this method is feasible.The three new methods proposed in this paper are feasible and effective after simulation analysis.They have their own advantages in different thinking points of the positioning problem,and have practical reference value in the field of single-based angle measurement passive positioning.