Zhengjie LiJunwei XieHaowei Zhang
Collocated multiple‐input multiple‐output radar can track multiple targets simultaneously by transmitting multiple orthogonal beams and adopting the digital beamforming technology. In this scenario, the authors propose a joint power and time width allocation approach, which combines a cognitive tracking model based on the posterior Cramér‐Rao lower bound (PCRLB) and the square‐root cubature Kalman filter. The aim of the optimisation model is to improve the velocity estimation accuracy by minimising the sum of the PCRLBs of the velocity of multiple targets, which are predicted based on the feedback information from the cognitive tracking model. However, there are two finite working resources in the optimisation model: the total transmit power of multiple beams and the total effective time width of each corresponding signal. The resource allocation problem can be transformed into a non‐convex optimisation problem, which can be converted into a standard convex optimisation problem by the linear relationship between the optimal power and the optimal time width. In this way, the joint power and time width allocation scheme is established as an adaptive closed‐loop system. Numerical results demonstrate that the velocity tracking accuracy can be improved efficiently by the proposed algorithm.
Haowei ZhangBinfeng ZongJunwei Xie
J. S. HuangJunwei XieZiqing YangHaowei ZhangZhengjie LiWeike Feng
Hao JiaoPeng ZhangJunkun YanXudong DangBo JiuHongwei Liu
Zhengjie LiJunwei XieWeijian LiuHaowei ZhangHouhong Xiang
Zhengjie LiJunwei XieHaowei ZhangHouhong XiangZhaojian Zhang