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

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.