Integrated Sensing and Communication enabled Multiple Base Stations Cooperative UAV Detection
arxiv(2024)
摘要
Integrated sensing and communication (ISAC) exhibits notable potential for
sensing the unmanned aerial vehicles (UAVs), facilitating real-time monitoring
of UAVs for security insurance. Due to the low sensing accuracy of single base
stations (BSs), a cooperative UAV sensing method by multi-BS is proposed in
this paper to achieve high-accuracy sensing. Specifically, a multiple signal
classification (MUSIC)-based symbol-level fusion method is proposed for UAV
localization and velocity estimation, consisting of a single-BS preprocessing
step and a lattice points searching step. The preprocessing procedure enhances
the single-BS accuracy by superposing multiple spectral functions, thereby
establishing a reference value for subsequent lattice points searching.
Furthermore, the lattice point with minimal error compared to the preprocessing
results is determined as the fusion result. Extensive simulation results reveal
that the proposed symbol-level fusion method outperforms the benchmarking
methods in localization and velocity estimation.
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