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相比于常规的“测向+位置估计”两步定位模式,以Weiss等提出的目标直接位置确定(DPD)算法具有估计精度高、分辨能力强和无需数据关联等诸多优点。基于该类定位算法的基本理念,提出了一种利用单个运动天线阵列对恒模(即相位调制)信号的DPD算法。首先,依据最大似然(ML)准则以及恒模信号的恒包络特征,建立了相应的直接定位优化模型;接着,根据优化函数的代数特征提出了一种有效的多参量交替迭代算法,用以获得ML估计器的最优数值解;此外,推导了针对恒模信源的位置直接估计方差的克拉美罗界(CRB),从而为新算法的定位精度提供定量的理论下界。仿真实验表明:相比于已有的基于单个运动天线阵列的直接定位算法以及传统的两步定位算法,通过利用恒模信号的恒包络特征可以明显提高目标直接定位的估计精度。
Compared with the conventional two-step positioning mode of “direction + position estimation”, the DPD algorithm proposed by Weiss has many advantages such as high precision of estimation, strong resolution and no need of data association. Based on the basic idea of this type of localization algorithm, a DPD algorithm using a single antenna array for constant mode (ie, phase modulation) signals is proposed. Firstly, based on the maximum likelihood (ML) criterion and the constant envelope feature of the constant mode signal, a corresponding direct positioning optimization model is established. Then, an efficient alternative iteration algorithm based on the algebraic features of the optimization function is proposed. In order to obtain the optimal numerical solution of the ML estimator, the authors also derive the Cramer-Rao boundary (CRB) which directly estimates the variance of the position of the constant-mode source, so as to provide a quantitative theoretical lower bound for the positioning accuracy of the new algorithm. Simulation results show that compared with the existing direct positioning algorithm based on a single moving antenna array and the traditional two-step positioning algorithm, the estimation accuracy of the target direct location can be significantly improved by using the constant envelope feature of the constant mode signal.