A Quasi-Coherent Detection Framework for Mobile Multi-Agent Networks
2021
Coherent processing in cooperative multi-agent networks can achieve significant performance gain via accurate alignment of observed signals. However, the inaccessibility of phase information in mobile scenes prevents the acquisition of a high degree of coherence for target detection. This paper presents a quasi-coherent mobile detection framework for cooperative multi-agent networks, which exploits the phase information inherent in the carrier wave of direct-path signals. Specifically, we derive the quasi-coherent detector with the aid of phase calibration by incorporating the maximum likelihood estimation of phase-related parameters obtained from direct-path signals. Next, we characterize the detection performance degradation induced by the mismatch of initial phase, transmitter position, orientation and clock. We further demonstrate the near-optimal detection capability of the proposed detector compared with generic coherent detectors and validate the effectiveness of phase information exploitation via numerical simulations.
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