Cooperative Localization And Tracking Of Airborne Passive Sensors Under Distance-dependent Noises

Passive sensors have the advantages of good concealment and wide coverage.They have been widely used in target location,tracking,surveillance,navigation and other fields.Multi-passive sensor measurement information fusion can achieve better performance of target location and tracking.At present,in most passive cooperative positioning and tracking problems,the variance of sensor measurement noise is assumed to be constant.The actual passive sensor angle measurement and ranging measurement noise variance varies with distance,so it is necessary to solve whether the measurement accuracy of the sensor is more consistent with the actual situation when the variance changes,and the influence of distance correlation characteristics on the sensor-target geometric position.In this thesis,the problem of cooperative localization and tracking of airborne passive sensors with distance-dependent noises is studied.The multi-passive sensor fusion tracking algorithm with distance-dependent noises is designed.The optimal geometric configuration of multi-passive sensor with distancedependent noises is analyzed.The path of airborne platform is optimized to obtain the optimal observation of passive sensors,so as to improve the performance of cooperative localization and tracking of airborne passive sensors.The main work is as follows:1.According to the distance-dependent characteristics of passive sensor the Angleof-Arrival(AOA)measurement noise,an airborne AOA collaborative positioning and path planning algorithm under distance-dependent noises is proposed.Firstly,an AOA fusion tracking algorithm based on maximum likelihood estimation and variable gain unscented Kalman filter is designed.In order to adapt to the variation characteristics of AOA measurement noises with distance.Subsequently,the generalized Cramer-Rao lower bound(GCRLB)under the distance-dependent noises AOA localization is derived.Taking the trace minimization of GCRLB as the optimization index,and the optimal geometric configuration of passive angle sensor cooperative localization is analyzed.Then,the path planning model of UAVs AOA cooperative positioning based on angle measurement GCRLB is established,which is solved by penalty function and L-M algorithm.Finally,a large number of simulated are carried out.The performance of different positioning and tracking algorithms,the AOA collaborative positioning error under different sensor numbers,and the path optimization performance under the same or different angle measurement accuracy sensor AOA collaborative positioning are compared.The emulation proofs the validity of the proposed algorithm.2.For the distance-dependent characteristics of passive sensor Time-ofArrival(TOA)measurement noises,an airborne TOA cooperative localization and path planning algorithm under distance-dependent noises is proposed.Firstly,according to the characteristics of TOA measurement noise changing with distance,a TOA fusion tracking algorithm based on weighted least squares estimation and variable gain extended Kalman filter is designed.Subsequently,the GCRLB index under TOA positioning of distance-dependent noises is derived,and the optimal position of passive sensor under TOA collaborative positioning is analyzed.Finally,the TOA cooperative positioning path planning model of UAVs based on ranging GCRLB is established,and the penalty function and gradient descent method are used for iterative optimization.A large number of simulated analysis shows that this algorithm can improve the performance of target location and tracking through airborne passive sensor location and tracking algorithm and sensor location optimization.3.Aiming at the path planning problem of airborne passive sensor cooperative tracking under the above measurement noise distance correlation,a multi-step UAV path planning algorithm based on long-term benefits is proposed to avoid the “shortsighted” optimization.The algorithm aims at maximizing the overall tracking revenue,considering both the current revenue and the future forward revenue.The path planning models of multi-step UAVs under distance-dependent noises AOA tracking,TOA tracking and AOA/TOA cooperative tracking are established respectively,and the trajectory of UAVs is obtained by using the improved branch and bound algorithm.Finally,the target tracking performance,cooperative tracking performance and obstacle avoidance ability of airborne passive sensors under different optimization strategies are compared by simulated.