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Weighted least squares algorithm for target localization in distributed MIMO radar

机译:分布式MIMO雷达目标定位的加权最小二乘算法。

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In this paper, we address the problem of locating a target using multiple-input multiple-output (MIMO) radar with widely separated antennas. Through linearizing the bistatic range measurements, which correspond to the sum of transmitter-to-target and target-to-receiver distances, a quadratically constrained quadratic program (QCQP) for target localization is formulated. The solution of the QCQP is proved to be an unbiased position estimate whose variance equals the Cramer-Rao lower bound. A weighted least squares ; algorithm is developed to realize the QCQP. Simulation results are included to demonstrate the high accuracy of the proposed MIMO radar positioning approach.
机译:在本文中,我们解决了使用天线分开的多输入多输出(MIMO)雷达定位目标的问题。通过线性化双站距离测量值,该值对应于发射器到目标距离和目标到接收器距离之和,制定了用于目标定位的二次约束二次程序(QCQP)。 QCQP的解被证明是一个无偏位置估计,其方差等于Cramer-Rao下界。加权最小二乘;开发了实现QCQP的算法。仿真结果包括在内,以证明所提出的MIMO雷达定位方法的高精度。

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