Phase information is seen to be important and decisive for the performance of a variety of signal processing tasks, including biometric data processing and robotics/navigational applications which require correct localization of objects or events. Existing approaches to system identification ignore phase information, under the minimum-phase assumption; yet, it is argued that improved performance can be obtained if phase information is retained. Modelling the impulse response of an unknown system from the observed output signal comprised of periodic input excitations, has traditionally been undertaken in the time domain. A novel method for system identification is proposed here, by undertaking the analysis in the frequency domain and utilizing the properties of the root cepstrum, which is a phase-retaining coefficient. We are able to demonstrate, that by warping the z-plane, the system impulse response will be separated from the problematic excitation. Hence, by moving the excitation zeros 'away' from the unit circle, the system impulse response may be extracted and modelled. Potential applications of our method include processing of biometric signals, where improved speaker identification/verification depends critically on an accurate vocal tract model of the speaker, as well as robotic/autonomous navigation applications, where correct automatic localization of items and/or events depends on the signal or system phase information. (5 pages)