GyroCopter: Differential Bearing Measuring Trajectory Planner for Tracking and Localizing Radio Frequency Sources

Abstract

Autonomous aerial vehicles can provide efficient and effective solutions for radio frequency (RF) source tracking and localizing problems with applications ranging from wildlife conservation to search and rescue operations. Existing lightweight, low-cost, bearing measurements-based methods with a single antenna-receiver sensor system configurations necessitate in situ rotations, leading to substantial measurement acquisition times restricting searchable areas and number of measurements. We propose a GyroCopter for the task. Our approach plans the trajectory of a multi-rotor unmanned aerial vehicle (UAV) whilst utilizing UAV flight dynamics to execute a constant gyration motion to derive "pseudo-bearing" measurements to track RF sources. The gyration-based pseudo-bearing approach: i) significantly reduces the limitations associated with in situ rotation bearing; while ii) capitalizing on the simplicity, affordability, and lightweight nature of signal strength measurement acquisition hardware to estimate bearings. This method distinguishes itself from other pseudo-bearing approaches by eliminating the need for additional hardware to maintain simplicity, lightweightness and cost-effectiveness. To validate our approach, we derived the optimal rotation speed and conducted extensive simulations and field missions with our GyroCopter to track and localize multiple RF sources. The results confirm the effectiveness of our method, highlighting its potential as a practical and rapid solution for RF source localization tasks.

Figures (9)

• Figure 1: Our proposed Gyrocopter, trajectory planning for tracking and localizing radio frequency (RF) sources. The robotic system integrates a single directional antenna undergoing gyrations. This presents different poses of the antenna--from time $t$ to $t+k$---to the RF source to detect changes in received signal strength indicator (RSSI) values to acquire the (pseudo-) bearing of an RF source. Importantly, we rely on the differences in a set of RSSI measurements, for example, collected from $t$ to $t+k$; therefore, we can remove the impact of environment-dependent parameters on RSSI---often difficult to model/obtain for unknown, complex terrains. See our GyroCopter demo video is at https://youtu.be/OkmmQjD74Us.
• Figure 2: (a) Experiment settings for finding optimal rotation speed; (b) antenna gain pattern of a typical directional H-antenna
• Figure 3: Theoretical analysis of performance. (a) Determinant of CRLB curves over time with different UAV rotation speed; (b) Determinant of CRLB from the GyroCopter compared with Dual-antenna-bearing method's CRLB.
• Figure 4: (a) Terrain and RF source placements for the simulation experiments. The initial GyroCopter and radio sources' locations are marked by $\Box/\ocircle$, respectively. (b) Visualization of the RSSI value generated from the ITU propagation model for a receiver at $\Box$. We can see the impact of the terrain on attenuating the RSSI value. (c) An instance of RF sources' trajectories at different process noise levels, moving from low mobility to high mobility.
• Figure 5: Simulation results comparing the performance of our proposed method for progressing fast-moving radio sources, indicated by higher dynamic model's process noise $\sigma_{Q}$, averaging over $30$ set of randomly generated tracks (with $35$ MC runs each track).