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Exploiting cross ambiguity function properties for data compression in emitter location systems

机译:利用交叉歧义函数属性进行发射器定位系统中的数据压缩

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In classical emitter location methods, pairs of sensors share the received data to compute the CAF and extract the ML estimates of TDOA/FDOA (time/frequency-difference-of-arrival). The TDOA/FDOA estimates are then transmitted to a common site where they are used to estimate the emitter location. In some recent methods, it has been proposed that rather than sending the TDOA/FDOA estimates, it is better to send the entire CAFs to the common site. Thus, it is desirable to use some methods to compress the data of the CAFs. In this paper, we will derive some beneficial properties and features of CAF that we then exploit to achieve a better CAF compression. Simulation results show that by exploiting these properties it is possible to improve the performance of the compression of CAFs and consequently the performance of location estimation.
机译:在经典的发射器定位方法中,成对的传感器共享接收到的数据以计算CAF并提取TDOA / FDOA(到达时间/频率差)的ML估计值。然后,将TDOA / FDOA估计值传输到公共站点,在该站点中使用它们来估计发射器位置。在最近的一些方法中,已经提出,与其发送TDOA / FDOA估计值,不如将整个CAF发送到公共站点更好。因此,期望使用一些方法来压缩CAF的数据。在本文中,我们将得出CAF的一些有益特性和特征,然后利用它们来实现更好的CAF压缩。仿真结果表明,通过利用这些属性,可以提高CAF的压缩性能,从而提高位置估计的性能。

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