Algorithm for Designing PCFM Waveforms for Simultaneously Polarimetric Radars

F Wang, N Li, C Pang, Y Li… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
F Wang, N Li, C Pang, Y Li, X Wang
IEEE Transactions on Geoscience and Remote Sensing, 2023ieeexplore.ieee.org
Simultaneous polarimetric radars (SPRs) are powerful tools for measuring the polarization
scattering matrix of targets in a single pulse. However, a major challenge associated with
SPRs is the design of orthogonal waveforms that can effectively minimize the interference
arising from simultaneous transmission and reception. Currently, frequency modulation (FM)
and phase-coded modulation are the most commonly used signal structures. However,
these signal structures suffer from certain limitations that necessitate the development of …
Simultaneous polarimetric radars (SPRs) are powerful tools for measuring the polarization scattering matrix of targets in a single pulse. However, a major challenge associated with SPRs is the design of orthogonal waveforms that can effectively minimize the interference arising from simultaneous transmission and reception. Currently, frequency modulation (FM) and phase-coded modulation are the most commonly used signal structures. However, these signal structures suffer from certain limitations that necessitate the development of new orthogonal waveforms that are both well-suited to high-power transmitters and maximally free in design. This article proposes an approach that leverages polyphase-coded FM waveforms to design orthogonal structures that combine the benefits of FM and phase-coded waveforms. A mathematical model for designing such waveforms is established considering a matched filter at the receiver. The model unifies the parameters of orthogonality and sidelobe level into a fraction expressed in terms of the sidelobe integral level, main-lobe integral level of autocorrelation functions, and entire-lobe integral level of cross correlation functions. This fraction accurately characterizes the orthogonality and sidelobe level of a pair of waveforms. The optimal waveform group can be obtained using a binary gradient descent algorithm, with peak sidelobe levels and isolation levels simultaneously approaching −30 dB. Finally, this article describes the implementation of the proposed orthogonal waveforms on hardware and verifies their performance by presenting experimental results that confirm the effectiveness of the proposed method.
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