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Joint power and time width allocation in collocated MIMO radar for multi-target tracking

机译:用于多目标跟踪的连接MIMO雷达中的接合电源和时间宽度分配

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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 Cramer-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.
机译:通过传输多个正交波束并采用数字波束成形技术,可以同时跟踪多个目标并采用数字波束形成技术可以同时跟踪多个目标。在这种情况下,作者提出了一种关节功率和时间宽度分配方法,该方法将基于后克拉姆-RAO下限(PCRLB)和平方根Cucature Kalman滤波器相结合的认知跟踪模型。优化模型的目的是通过最小化多个目标的速度的PCRLB之和基于来自认知跟踪模型的反馈信息来提高速度估计精度。然而,优化模型中有两个有限的工作资源:多个光束的总发射功率和每个对应信号的总有效时间宽度。资源分配问题可以转换为非凸优化问题,可以通过最佳功率和最佳时间宽度之间的线性关系转换为标准凸优化问题。以这种方式,建立接合功率和时间宽度分配方案作为自适应闭环系统。数值结果表明,通过所提出的算法可以有效地提高速度跟踪精度。

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