OFDM-Based UAV Swarm Cooperative Positioning Design and Optimization

Accurate relative positioning is fundamental to the coordination and safety of uncrewed aerial vehicle (UAV) swarms. In many practical missions, however, global navigation satellite system (GNSS) support can be blocked or degraded, motivating GNSS-free cooperative positioning solutions, which leverage inter-UAV signals. In this paper, we propose an orthogonal frequency-division multiplexing (OFDM)-based cooperative positioning scheme for GNSS-denied environments. UAVs transmit dedicated positioning waveforms in a time-sequenced manner; each receiver estimates propagation delays via multiple signal classification (MUSIC), and the resulting inter-UAV delays are aggregated into a distance matrix. Multidimensional scaling (MDS) is then applied to reconstruct the swarm's relative coordinates. Beyond the end-to-end pipeline, we analyze how reconstruction error depends on the length of the transmitted delay data and cast the design as an optimization that balances accuracy against timeliness. Simulations quantify the impact of the number of UAVs, relative velocity, and signal-to-noise ratio (SNR) on the reconstruction error, and reveal a unique optimal data length that minimizes the error by trading data-quantization and latency-induced components. The proposed framework provides a practical reference for robust swarm positioning in complex, GNSS-denied scenarios.