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                <term xml:lang="en">white non-Gaussian input</term>
                <term xml:lang="en">phase estimation</term>
                <term xml:lang="en">polyspectrum slices</term>
                <term xml:lang="en">nonminimum phase identification</term>
                <term xml:lang="en">method consistency</term>
                <term xml:lang="en">linear time invariant system</term>
                <term xml:lang="en">higher order spectrum slices</term>
                <term xml:lang="en">band-limited systems</term>
                <term xml:lang="en">asymptotic unbiasedness</term>
                <term xml:lang="en">Fourier phase reconstruction</term>
                <term xml:lang="en">time-varying systems</term>
                <term xml:lang="en">spectral analysis</term>
                <term xml:lang="en">signal reconstruction</term>
                <term xml:lang="en">linear systems phase estimation</term>
                <term xml:lang="en">Fourier analysis</term>
                <term xml:lang="en">Single Input Single Output (SISO)</term>
                <term xml:lang="en">polyspectra</term>
                <term xml:lang="en">blind deconvolution</term>
                <term xml:lang="en">Non-minimum phase system identification</term>
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              <p>A new family of methods, named PEP (Phase Estimation using Polyspectrum slices), for the reconstruction of the Fourier phase of a complex LTI system excited by a white non-Gaussian input is proposed. More precisely, we propose two subfamilies of methods, the q-PEP (q&gt;2) and (q1, q2)-PEP (q2&gt;q1&gt;2) algorithms. The q-PEP methods exploit the best Two-Dimensional (2D) slice of the data q-th order spectrum. The originality of the (q1, q2)-PEP methods consists of exploiting simultaneously one 1D slice of the q1-th order spectrum and one 2D slice of the q2-th order spectrum. These new algorithms are easy both to implement and to use. Moreover, the asymptotic unbiasedness and consistency of these methods are demonstrated. Eventually, computer simulations show that the PEP algorithms exhibit in general better performances than classical methods especially for band-limited systems.</p>
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