Unauthorized UAV Detection Using Bistatic MIMO-OFDM ISAC Under Static Clutter

Abstract

This paper investigates unauthorized unmanned aerial vehicle (UAV) detection in a bistatic multi-inputmulti- output (MIMO)-orthogonal frequency-division multiplexing (OFDM) integrated sensing and communication (ISAC) system comprising one UAV and multiple static objects. One base station (BS) transmits a dual-functional OFDM waveform, while a spatially separated BS receives the direct BS-to-BS signal, UAV echo, and static-clutter components. A UAV detection framework is developed to suppress the direct-link and static-clutter components by exploiting their temporal invariance over the OFDMsymbol dimension, followed by transformation of the residual channel into the delay–Doppler (DD) domain. An average-power decision statistic is formulated, and its distribution under H0 is characterised to derive the probability of false alarm and the corresponding detection threshold. The statistical stability of the detection statistic is also assessed for varying numbers of OFDM symbols and subcarriers by comparing theoretical and simulated probability density functions (PDFs). The theoretical false-alarm probability is validated through simulations, and UAV detection performance is evaluated for prescribed false-alarm probabilities over various received signal-to-noise ratios (SNRs).