The system architecture for cognitive radar-communication (CRC) transceiver is proposed. A cognitive waveforms design approach, which is suitable for simultaneously performing both data communication and target detection, is presented. This approach aims at estimating target scattering coefficient (TSC) from the radar scene and facilitating high data rate communications. In order to minimize the mean square error (MSE) of the TSC, a convex cost function is established. The peak to average power ratio- (PAPR-) constrained optimal solution is achieved by applying the Kalman filtering-based strategy to design the set of ultra-wideband (UWB) transmission pulses and embed into them the information data with the M-ary position phase shift keying modulation technique. In addition to theoretical considerations, the simulation results show an improvement in target scattering coefficient (TSC) estimation and target detection probability as the number of iterations increases, while still transmitting data rates in the range of several Mbps with low bit error rates between CRC transceivers.


    Access

    Download


    Export, share and cite



    Title :

    Cognitive Waveform Design for Radar-Communication Transceiver Networks


    Contributors:
    Yu Yao (author) / Lenan Wu (author)


    Publication date :

    2018




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    Unknown





    Construction of Waveform Library in Cognitive Radar

    Yongqiang Guo / Yumin Wu / Hui Liu | DOAJ | 2017

    Free access

    Construction of Waveform Library in Cognitive Radar

    Yongqiang, Guo / Yumin, Wu / Hui, Liu | Online Contents | 2017


    Unimodular Waveform Design With Desired Ambiguity Function for Cognitive Radar

    Esmaeili-Najafabadi, Hamid / Leung, Henry / Moo, Peter W. | IEEE | 2020


    Minimization of Internally Reflected Power Via Waveform Design in Cognitive MIMO Radar

    Abouelfadl, Ahmed A. / Psaromiligkos, Ioannis / Champagne, Benoit | IEEE | 2023