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Direction of arrival estimation using parametric signal models

机译:使用参数信号模型的到达方向估计

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We consider the problem of estimating the directions-of-arrival (DOAs) of narrowband sources with known center frequency. The paper evaluates the potential improvement in estimation accuracy by using spatial-temporal processing for signals obeying a deterministic parametric model. One would expect that prior information about the temporal structure of the signals will yield some gain in performance. By deriving the Cramer-Rao bound (CRB) on the DOA estimates, we quantify this gain and identify the cases for which the gain is significant. We show that for the single-source case, spatial-temporal processing does not yield any gain in performance relative to conventional spatial processing. For multiple noncoherent signals, incorporating temporal processing can achieve the single-source performance, yielding a significant gain for the case of multiple sources with small spatial separation relative to the beamwidth of the array. However, spatial-temporal processing cannot yield any gain in performance for multiple coherent signals.
机译:我们考虑估计中心频率已知的窄带源的到达方向(DOA)的问题。本文通过对信号服从确定性参数模型进行时空处理来评估估计精度的潜在提高。可以预料,有关信号的时间结构的先验信息将在性能上有所提高。通过推导DOA估计值的Cramer-Rao界(CRB),我们可以量化此增益并确定增益显着的情况。我们表明,对于单源情况,相对于常规空间处理,时空处理不会在性能上产生任何收益。对于多个非相干信号,合并时间处理可以实现单源性能,对于多个源(相对于阵列的波束宽度而言空间间隔较小)的情况,可获得显着的增益。但是,时空处理不能为多个相干信号带来任何性能提升。

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