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Bounds on Passive Tdoa Estimation in Mixtures

机译:混合中被动Tdoa估计的界

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We consider the problem of Time Difference of Arrival (TDOA) estimation in mixtures, namely when several sources are received by several receivers, possibly with different delays and attenuations. Under the assumption that the sources are stationary Gaussian with known spectra (a semi-blind scenario), we derive the Cramér-Rao Lower Bound on the Mean Squared Error (MSE) in unbiased joint estimation of the delays and of the mixing coefficients. We then analyze the results, drawing conclusions on the effects of the different model parameters (mixing coefficients, delay differences, signal to noise ratio) on the resulting bound, pointing out essential differences from the classical cases of static mixtures (with no delays) on one hand, and of single-source TDOA estimation on the other hand.
机译:我们考虑混合中到达时间差(TDOA)估计的问题,即当多个接收器接收到多个源时,可能具有不同的延迟和衰减。在假设源是已知光谱的平稳高斯条件下(半盲场景),我们在延迟和混合系数的无偏联合估计中,推导了均方误差(MSE)上的Cramér-Rao下界。然后,我们分析结果,得​​出不同模型参数(混合系数,延迟差异,信噪比)对结果界限的影响的结论,指出与经典静态混合情况(无延迟)的本质区别。一方面,另一方面是单源TDOA估计。

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