This article investigates the application of ground-based frequency diverse array (FDA) radar in detecting aerial high-speed maneuvering targets that move across range units. Existing detection methods that primarily focus on the range-dependent phase differences between FDA radar elements fail to fully exploit the spatio-temporal coherent gain. In response to this limitation, a detection method combining long-time coherent integration (LTCI) and range-angle beamforming is proposed, enabling range compression, multipulse accumulation, and array-based digital beamforming to enhance detection performance. In this process, it is essential to compensate for the phase differences and envelope shifts between multiple elements and pulses. In this work, we present a 4-D FDA radar echo signal model that incorporates the Doppler spreading effect by jointly considering the transmit and receive dimensions, as well as the slow-time (multipulse) and fast-time (range) dimensions. Then, based on a binary hypothesis test, a closed-form expression for the detection statistic is derived, combining LTCI and range-angle beamforming. Finally, the detection process is efficiently implemented using the chirp-Z transform and the fast Fourier transform. Numerical simulation results demonstrate that the proposed method not only achieves efficient spatio-temporal energy accumulation but also leverages the FDA radar's high-resolution capabilities in both the range and Doppler domains, enabling precise detection of densely distributed, highly maneuvering, and blind-speed targets.


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    Titel :

    Long-Time Coherent Integration and Range-Angle Beamforming for Detecting High-Speed Maneuvering Targets Using FDA Radar


    Beteiligte:
    Jia, Wenkai (Autor:in) / Jian, Jiangwei (Autor:in) / Li, Ping (Autor:in) / Fu, Mingcheng (Autor:in) / Huang, Bang (Autor:in) / Wang, Wen-Qin (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    01.08.2025


    Format / Umfang :

    5996440 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch