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On the Design of Constant Modulus Probing Waveforms With Good Correlation Properties for MIMO Radar via Consensus-ADMM Approach

机译:基于共识-ADMM方法的MIMO雷达具有良好相关性的恒模探测波形设计

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In this paper, we design constant modulus probing waveforms with good correlation properties for collocated multi-input multi-output radar systems. The main content is as follows: first, we formulate the design problem as a fourth-order polynomial minimization problem with constant modulus constraints. Then, by exploiting introduced auxiliary variables and their inherent structures, the polynomial optimization model is equivalent to a non-convex consensus minimization problem. Second, a customized alternating direction method of multipliers (ADMM) algorithm is proposed to solve the non-convex problem approximately. In the algorithm, all the subproblems can be solved analytically. Moreover, all subproblems except one subproblem can be performed in parallel. Third, we prove that the customized ADMM algorithm is theoretically guaranteed convergent if proper parameters are chosen. Finally, two variant ADMM algorithms, based on stochastic block coordinate descent and accelerated gradient descent, are proposed to reduce computational complexity and speed up the convergence rate. Numerical examples show the effectiveness of the proposed consensus-ADMM algorithm and its variants.
机译:在本文中,我们为并置的多输入多输出雷达系统设计了具有良好相关性的恒定模数探测波形。主要内容如下:首先,我们将设计问题公式化为具有恒定模量约束的四阶多项式最小化问题。然后,通过利用引入的辅助变量及其固有结构,多项式优化模型等效于非凸共识最小化问题。其次,提出了一种定制的乘数交替方向法(ADMM)算法,以近似地解决非凸问题。在该算法中,所有子问题都可以解析解决。而且,可以并行执行除一个子问题以外的所有子问题。第三,我们证明,如果选择适当的参数,则定制的ADMM算法在理论上可以保证收敛。最后,提出了两种基于随机块坐标下降和加速梯度下降的变型ADMM算法,以降低计算复杂度并加快收敛速度​​。数值算例表明了所提出的共识ADMM算法及其变体的有效性。

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