Error assessment is one of the great considerations in any position-finding (PF) system. In this paper it is assumed that a single moving sensor measures the Angle Of Arrival (AOA) of the signals emitted by a stationary source. These AOA measurements are used to find true position of the source. Regarding such a scenario, source estimated location error is analyzed and a lower bound of error is extracted regarding Cramer-Rao criteria.
In this paper a new passive imaging method is introduced that is mainly suitable for Geo-locating LPI radars. The method uses two Electronic Support (ES) receivers located on a fast moving platform (e.g. an airplane or a satellite). The proposed method has a high processing gain which makes it absolutely suitable against very weak LPI signals. It is also capable in radar location finding against complex radars and complicated electromagnetic environment.
In this paper, a framework for localization of multiple co-channel transmitters using phase difference measurements between two antennas mounted on sensors of a sensor network is proposed. To pursue localization, we equip each sensor with two antennas and we use temporal cross-correlations between the received signals of the two antennas to extract the phase differences between each antenna pairs, named as phase interferometry measurements (PIMs), provoked by each transmitters using tensor decomposition. We calculate Cramer-Rao lower bound of error of localization using PIMs. Our simulation results show that highly accurate estimations can be achieved using PIMs. We also compare the accuracy of our proposed technique with a sensor network that exploits highly directional linear array antennas and show that our proposed technique can perform similar to a network that employs very large antenna arrays.
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