| Angle-only target tracking has become a hot topic for the domestic and foreign scholars because the observation platforms can locate and track target without emitting electromagnetic waves or other signals,they only need to passively receive the objective radiation information or the reflection energy of targets to other light sources.The angle-only tracking system possesses strong concealment and survivability,and the multi-motion observation platform angle-only target tracking system has the characteristics of large search range,far distance and high reliability,and is especially suitable for wide sea and airspace monitoring.In this paper,the angle-only target tracking fusion algorithm with multi-motion observation platform is deeply studied,and some new ideas and methods are presented.The work and achievements are as follows:First,the system framework of multi-observation platform angle-only target tracking system in three-dimensional space is studied.Several typical target motion models and the measurement model are established.Based on the established system model,the Monte Carlo method is discussed,and the target tracking performance evaluation index,such as root mean square error(RMSE),is defined.Second,the formula system of multi-observation platform direction finding cross location least square algorithm for 3D space is derived.The geometric dilution of precision(GDOP)is introduced to describe the positioning accuracy.The GDOP analytical expression of the target location with multi-observation platform in the 3D space is given.The simulation results of cross locating and tracking for non-maneuvering targets and maneuvering targets are analyzed respectively,and the GDOP distribution graphs are drawn.The results show that the proposed algorithm can effectively track the target.Third,the performance of the extended Kalman filter(EKF)and unscented Kalman filter(UKF)are compared and analyzed,and the square root unscented Kalman filter(SR-UKF)algorithm is proposed for the multi-observation platform angle-only fusion tracking system.Based on SR-UKF,a distributed fusion tracking algorithm is proposed,which is firstly measurement fusion and then trajectory fusion.Compared with EKF and UKF,this algorithm can adapt to the target tracking system with higher tracking precision and stability.Experimental results verify the effectiveness of the proposed algorithm.Fourth,aiming at sensor network observation system,an optimal selection method of observation platforms based on minimum GDOP is proposed.At each time,roughly position is obtained by cross location method firstly.Then,the PSO algorithm is used to search the optimal sensor combination quickly by minimizing GDOP.Based on the measurements of these selected sensors,SR-UKF algorithm is used to solve more accurate location of the target.The sensors involved in the observation change dynamically to adjust the change of the target trajectory.Theoretical analysis and simulation experiments verify the feasibility and effectiveness of this method,and it is suitable for sensor optimal scheduling in large scale sensor network target tracking system.Finally,a maneuvering strategy based on the minimum GDOP is proposed for mobile observation platforms.The maneuvering strategy of mobile observation platform is given respectively for the stationary and moving targets.Simulation results show that the maneuvering strategy proposed in this paper improves the robustness and stability of the target tracking system.Under the sea-to-air,air-to-air and ground-to-air with path constraints tracking scenarios,all the targets can be effectively tracked and the tracking performance is better than that of the static observation platform tracking system. |
