The availability of accurate estimates of the delay or time of arrival of the incoming signals is of paramount importance for the position estimation in passive radars with multiple receivers. This correspondence aims at improving estimation of the delays by multiple detectors exploiting the cross-correlation between the cross-correlation estimates (say cross-cross-correlation) of the received signals. The resulting equation system is formulated as a least squares minimization problem, whose solution is efficiently found computing the pseudoinverse of the model matrix. In fact, the cross-cross-correlation implicitly performs a filtering operation on the considered signal, approximating the generalized cross-correlator behavior, without using statistical information about the signal spectra. The proposed method is numerically validated in comparison with classic counterparts and theoretical bounds.
Pallotta, L., Giunta, G. (2022). Accurate Delay Estimation for Multisensor Passive Locating Systems Exploiting the Cross-Correlation Between Signals Cross-Correlations. IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, 58(3), 2568-2576 [10.1109/TAES.2021.3116927].
Accurate Delay Estimation for Multisensor Passive Locating Systems Exploiting the Cross-Correlation Between Signals Cross-Correlations
Pallotta L.;Giunta G.
2022-01-01
Abstract
The availability of accurate estimates of the delay or time of arrival of the incoming signals is of paramount importance for the position estimation in passive radars with multiple receivers. This correspondence aims at improving estimation of the delays by multiple detectors exploiting the cross-correlation between the cross-correlation estimates (say cross-cross-correlation) of the received signals. The resulting equation system is formulated as a least squares minimization problem, whose solution is efficiently found computing the pseudoinverse of the model matrix. In fact, the cross-cross-correlation implicitly performs a filtering operation on the considered signal, approximating the generalized cross-correlator behavior, without using statistical information about the signal spectra. The proposed method is numerically validated in comparison with classic counterparts and theoretical bounds.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.