The cross ambiguity function (CAF) has been commonly used to find time difference of arrival (TDOA) and frequency difference of arrival (FDOA). In most cases, direct computation of the CAF by using a conventional method such as fast Fourier transform is too computationally intensive. Thus, a two-stage approach consisting of a coarse mode to find rough TDOA/FDOA estimates and a fine mode for precise estimation was introduced. However, there has been no methodology for selecting an interpolation factor determined by the sampling frequency and target precision which significantly affects the computational complexity. In addition, even if the computational complexity can be reduced by using the optimal interpolation factor, the huge transmission data through the datalink between sensors and the central station still remains to be an obstacle for an electronic warfare (EW) system. In this respect, we derive an optimal interpolation factor and then propose a new two-stage TDOA/FDOA estimation algorithm using a resampling block to reduce the computational complexity and the data size simultaneously in EW systems. In the proposed method, the optimal interpolation factor can be used irrespective of the sampling frequency and the target precision. Simulation results show that the optimal interpolation factor efficiently reduces the computational burden without the loss of estimation performance.


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    Title :

    Computationally Efficient TDOA/FDOA Estimation for Unknown Communication Signals in Electronic Warfare Systems


    Contributors:


    Publication date :

    2018-02-01


    Size :

    1476954 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



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