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首页> 外文期刊>IEEE Transactions on Aerospace and Electronic Systems >Coarse quantization for data compression in coherent location systems
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Coarse quantization for data compression in coherent location systems

机译：粗量化用于相干定位系统中的数据压缩

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摘要

When emitter location systems measure time-difference-of-arrival (TDOA) and differential Doppler (DD) by coherently cross-correlating the signal pairs, data compression techniques are needed to facilitate data transfer of one of the signals to the receiving site of the other signal. Two block-adaptive quantization schemes are analyzed here to determine their impact on the signal-to-noise ratio (SNR) of the quantized signal as well as on the post-correlation SNR. Comparisons are made between two approaches: quantization of the real/imaginary (R/I) components or the magnitude/phase (M/P) components. For the M/P approach, a rule is derived for optimally allocating the bits between the magnitude and phase. The M/P approach provides better post-quantization/precorrelation SNR for most signals; however, when the SNR of the signal not being quantized is small, the post-correlation SNR can be largely unaffected by the quantization. In that case, there is little difference between R/I and M/P, even under the most favorable scenario for M/P.
机译：当发射器定位系统通过对信号对进行相干互相关来测量到达时间差（TDOA）和差分多普勒（DD）时，就需要数据压缩技术来促进信号之一向数据接收点的数据传输。其他信号。这里分析了两种块自适应量化方案，以确定它们对量化信号的信噪比（SNR）以及对后相关SNR的影响。比较两种方法：实/虚（R / I）分量或幅值/相位（M / P）分量的量化。对于M / P方法，导出了一个规则，用于在幅度和相位之间最佳地分配位。 M / P方法为大多数信号提供了更好的量化后/预相关SNR。然而，当未量化的信号的SNR较小时，相关后的SNR在很大程度上不受量化的影响。在那种情况下，即使在最有利于M / P的情况下，R / I和M / P之间也几乎没有区别。

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