Research On Sensor Resource Management For Multi-Radar Collaborative Tracking System

With the development of military electronic equipment and communication technology,the overall performance of the networked radar system can be improved by collaborative tracking of multiple radars with different frequency bands and operation modes in different platforms.Although the number of radars and their transmit power contribute the tracking accuracy of multi-radar system theoretically,the multi-radar system may not have sufficient resources to satisfy all the tracking tasks due to the limited sensor resources,computational and communication capacities in practical applications.Thus,how to allocate the limited resources to collaborative tracking targets has become a key problem in multi-radar systems.The thesis focuses on the sensor resource optimization of multiple cognitive radar systems,multi-static radar systems(MSRS)and airborne passive coherent location(APCL)radar systems.The main contributions are summarized as follows:1.The resource optimization of multiple cognitive radar systems is studied.A joint sensor selection and power allocation algorithm is proposed with limited radar transmit power and signal bandwidth.Firstly,the total Posterior Cramer-Rao Lower Bound(PCRLB)in multiple targets tracking of multiple cognitive radar systems is derived.Then,the corresponding joint sensor selection and power allocation optimization problem to minimize the trace of total PCRLB is formulated,which is solved by cyclic minimization algorithm based on convex relaxation.Finally,simulation results show that the tracking performance is improved through joint sensor selection and power allocation algorithm compared to the scheme without optimal allocation.2.The resource optimization of MSRS is studied.A joint path planning and sensor selection algorithm is proposed since the location of mobile radar emitter has a great influence on the tracking accuracy of MSRS.Firstly,the PCRLB of multiple targets tracking of MSRS is derived.Then,the corresponding joint path planning and sensor selection optimization problem based on PCRLB is established considering the airborne platform motion constraints and data processing capabilities.A two-stage optimization algorithm is proposed to solve the non-convex optimization problem with two independent vectors.Finally,Simulation results show that the target tracking accuracy is improved by jointly optimizing path planning and sensor selection in the MSRS.3.The resource optimization of bi-static APCL radar systems is studied.The error covariance of measurement obtained by the mobile radar receiver is affected by the geometric relationship among emitter-target-receiver in the APCL radar systems.Firstly,the PCRLB of the APCL radar system is derived based on the relationship between PCRLB and the geometric relationship among emitter-target-receive.Then,a nonlinear path planning optimization problem based on PCRLB for the APCL radar receiver with airborne motion constraints is formulated,which is solved optimally by the interior point method.Finally,the validity of the proposed algorithm is demonstrated with the simulation results.