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Direct cartesian localization in active MIMO radar networks

机译:主动MIMO雷达网络中的直接笛卡尔定位

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This paper extends prior work on target position and velocity estimation in active multiple-input multiple-out (MIMO) radar networks by introducing multichannel receivers into the problem formulation. The maximum likelihood estimate (MLE) of target position and velocity is derived assuming all received time-series can be aggregated at a central processor. This is in contrast to methods that first make range, Doppler, and/or angle-of-arrival (AoA) estimates at each receiver. The corresponding Cramér-Rao lower bound (CRLB) is also derived for this problem. Monte Carlo simulations demonstrate that the MLE can attain the CRLB at reasonable signal-to-noise ratios (SNRs) and position/velocity estimation accuracy is improved with respect to the single-channel receiver case.
机译:通过将多通道接收器引入问题公式中,本文扩展了主动多输入多出(MIMO)雷达网络中目标位置和速度估计的现有工作。假设可以在中央处理器处汇总所有接收到的时间序列,则得出目标位置和速度的最大似然估计(MLE)。这与首先​​在每个接收器进行距离,多普勒和/或到达角(AoA)估计的方法形成对比。对于此问题,也导出了相应的Cramér-Rao下界(CRLB)。蒙特卡洛仿真表明,MLE可以在合理的信噪比(SNR)下获得CRLB,并且相对于单通道接收器而言,位置/速度估计的精度得到了提高。

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