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This study presents a novel method for time–frequency (TF) signal analysis and chirp rate estimation dedicated for electromagnetic spectrum sensing, electronic warfare, electronic intelligence and/or passive bistatic radar purposes in which frequency modulated signals occur. The approach is based on the double‐adaptive chirplet transform, providing optimal analysis window parameters, which is a crucial problem during TF processing. The presented methodology is based on a Gaussian window with two degrees of freedom, which results in a strong concentration of energy on the TF plane around the main component, even if the initial window parameters were mismatched. As an example of the method's usefulness, different types of real‐life radar pulses were processed: firstly, two types of non‐linear frequency‐modulated waveforms were examined as a suitable illustration of the changeability of the analysis window parameters. Secondly, the linear frequency modulated signals were analysed in the presence of strong interference and multipath propagation. The waveforms were processed and compared, creating individual radar signatures, which may allow transmitter classification and signal reconstruction to be carried out in further processing. Moreover, the estimation limitations were compared to the Cramer‐Rao lower bound, and an appendix organising mathematical fundamentals for the analysed methods is provided. [ABSTRACT FROM AUTHOR]

This paper presents a novel approach to fast and accurate non-linear pulse signal reconstruction dedicated for electromagnetic sensors and their applications such as ELectronic INTelligence (ELINT), electronic warfare (EW), electronic reconnaissance (ER) systems, as well as for passive bistatic radar purposes in which other pulse radars are used as a source of illumination. The method is based on the instantaneous chirp rate (CR) estimation in the time-frequency (TF) domain providing a calculation of the frequency rate between every two consecutive samples. Such a new method allows for the precise reconstruction of the non-linear frequency modulated (NLFM) signal to be carried out in significantly shorter time in comparison to methods known in the literature. The presented approach was tested and validated using both simulated and real-life radar signals proving the usability of the proposed solution in practical applications. The results were compared with the precise extended generalized chirp transform (EGCT) method as a reference technique, using optimal matched filtration as the main concept. [ABSTRACT FROM AUTHOR]